diff --git a/openbb_terminal/core/session/current_system.py b/openbb_terminal/core/session/current_system.py
index 77403e9842f..62ec09037cf 100644
--- a/openbb_terminal/core/session/current_system.py
+++ b/openbb_terminal/core/session/current_system.py
@@ -3,7 +3,8 @@ from copy import deepcopy
 
 # IMPORTS INTERNAL
 from openbb_terminal.core.models import SystemModel
-from openbb_terminal.core.session.system_handler import handle_system, save_system
+from openbb_terminal.core.session.env_handler import read_env
+from openbb_terminal.core.session.utils import load_dict_to_model
 
 
 def get_current_system() -> SystemModel:
@@ -14,8 +15,8 @@ def get_current_system() -> SystemModel:
 def set_current_system(system: SystemModel):
     """Set current system."""
     global __system  # pylint: disable=global-statement
-    save_system(system)
     __system = system
 
 
-__system = handle_system()
+__env_dict = read_env()
+__system = load_dict_to_model(__env_dict, SystemModel)
diff --git a/openbb_terminal/core/session/system_handler.py b/openbb_terminal/core/session/system_handler.py
deleted file mode 100644
index 3c80c80e4f7..00000000000
--- a/openbb_terminal/core/session/system_handler.py
+++ /dev/null
@@ -1,86 +0,0 @@
-import atexit
-import json
-import os
-from pathlib import Path
-
-from pydantic.json import pydantic_encoder
-
-from openbb_terminal.core.config.paths import (
-    SETTINGS_DIRECTORY,
-)
-from openbb_terminal.core.models import SystemModel
-from openbb_terminal.core.session.env_handler import read_env
-from openbb_terminal.core.session.utils import load_dict_to_model
-
-SYSTEM_FILE_PATH = SETTINGS_DIRECTORY / "system.json"
-
-
-def handle_system(file_path: Path = SYSTEM_FILE_PATH) -> SystemModel:
-    """
-    Handle the system.
-
-    Reads system data from file if it exists, else reads environment variable data.
-    Returns a system model built from the loaded data.
-
-    Parameters
-    ----------
-    file_path (Path): The file path.
-
-    Returns
-    -------
-        SystemModel: The system model.
-    """
-
-    try:
-        if os.path.isfile(file_path):
-            system_data = {}
-            with open(file_path) as f:
-                system_data = json.load(f)
-            if system_data:
-                return load_dict_to_model(system_data, SystemModel)
-    except Exception:
-        pass
-
-    __env_dict = read_env()
-    system = load_dict_to_model(__env_dict, SystemModel)
-    save_system(system=system, file_path=file_path)
-    subscribe_delete_system_on_exit(file_path=file_path)
-    return system
-
-
-def save_system(system: SystemModel, file_path: Path = SYSTEM_FILE_PATH):
-    """
-    Write system to file.
-
-    Parameters
-    ----------
-    system (SystemModel): The system model.
-    file_path (Path): The file path.
-
-    Returns
-    -------
-        system (SystemModel): The system model.
-    """
-
-    try:
-        with open(file_path, "w") as f:
-            json_content = json.dumps(system, default=pydantic_encoder)
-            f.write(json_content)
-    except Exception:
-        pass
-
-
-def subscribe_delete_system_on_exit(file_path: Path):
-    """
-    Deletes the system file on exiting the application.
-
-    Parameters
-    ----------
-    file_path (Path): The file path.
-    """
-
-    def delete_file(file_path: Path):
-        if os.path.isfile(file_path):
-            os.remove(file_path)
-
-    atexit.register(delete_file, file_path=file_path)
diff --git a/openbb_terminal/dashboards/dashboards_controller.py b/openbb_terminal/dashboards/dashboards_controller.py
index 760478a0512..1b282b0174c 100644
--- a/openbb_terminal/dashboards/dashboards_controller.py
+++ b/openbb_terminal/dashboards/dashboards_controller.py
@@ -18,7 +18,6 @@ import dotenv
 import numpy as np
 import psutil
 
-import openbb_terminal.config_terminal as cfg
 from openbb_terminal.base_helpers import load_env_vars, strtobool
 from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY, SETTINGS_ENV_FILE
 from openbb_terminal.core.plots.backend import plots_backend
@@ -199,7 +198,6 @@ class DashboardsController(BaseController):
                 cmd += " --theme=dark"
 
             if ns_parser.input or response.lower() == "y" and not process_check:
-                cfg.change_logging_suppress(new_value=True)
                 self.processes.append(
                     psutil.Popen(
                         f"{cmd} --no-browser --port {port}"
@@ -211,7 +209,6 @@ class DashboardsController(BaseController):
                         env=os.environ,
                     )
                 )
-                cfg.change_logging_suppress(new_value=False)
                 atexit.register(self.kill_processes)
 
                 console.print(
diff --git a/openbb_terminal/dashboards/stream/Forecasting.py b/openbb_terminal/dashboards/stream/Forecasting.py
index 21645d161e0..3bc792e0b8d 100644
--- a/openbb_terminal/dashboards/stream/Forecasting.py
+++ b/openbb_terminal/dashboards/stream/Forecasting.py
@@ -9,10 +9,17 @@ import streamlit as st
 import yfinance as yf
 from rich.table import Table
 
+import openbb_terminal.config_terminal as cfg
 from openbb_terminal.core.plots.plotly_helper import OpenBBFigure
 from openbb_terminal.forecast import helpers
 from openbb_terminal.rich_config import console
-from openbb_terminal.sdk import openbb
+
+# Suppressing sdk logs
+cfg.change_logging_suppress(new_value=True)
+
+# Import the OpenBB SDK
+# pylint: disable=wrong-import-position
+from openbb_terminal.sdk import openbb  # noqa: E402
 
 st.set_page_config(
     layout="wide",
diff --git a/openbb_terminal/dashboards/stream/pages/Indicators.py b/openbb_terminal/dashboards/stream/pages/Indicators.py
index ad088fd094d..e17bcca9506 100644
--- a/openbb_terminal/dashboards/stream/pages/Indicators.py
+++ b/openbb_terminal/dashboards/stream/pages/Indicators.py
@@ -8,11 +8,18 @@ import pandas as pd
 import streamlit as st
 from streamlit.delta_generator import DeltaGenerator
 
+import openbb_terminal.config_terminal as cfg
 from openbb_terminal.common.technical_analysis import ta_helpers
 from openbb_terminal.core.plots.plotly_helper import OpenBBFigure
 from openbb_terminal.core.plots.plotly_ta.ta_class import PlotlyTA
 from openbb_terminal.rich_config import console
-from openbb_terminal.sdk import openbb
+
+# Suppressing sdk logs
+cfg.change_logging_suppress(new_value=True)
+
+# Import the OpenBB SDK
+# pylint: disable=wrong-import-position
+from openbb_terminal.sdk import openbb  # noqa: E402
 
 pd.options.plotting.backend = "plotly"
 st.set_page_config(
diff --git a/openbb_terminal/dashboards/voila/forecast.ipynb b/openbb_terminal/dashboards/voila/forecast.ipynb
index ffbb5f42fee..fefbb37e62c 100644
--- a/openbb_terminal/dashboards/voila/forecast.ipynb
+++ b/openbb_terminal/dashboards/voila/forecast.ipynb
@@ -1,361 +1,374 @@
 {
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e9ad60bc",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from datetime import datetime, timedelta\n",
-    "from typing import Callable, Any\n",
-    "from inspect import signature\n",
-    "import warnings, logging\n",
-    "\n",
-    "import ipywidgets as widgets\n",
-    "import yfinance as yf\n",
-    "import pandas as pd\n",
-    "from IPython.display import display\n",
-    "\n",
-    "from openbb_terminal.sdk import openbb, theme\n",
-    "\n",
-    "theme.apply_style()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "beb36881",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "try:\n",
-    "    has_forecast = True\n",
-    "    model_opts = {\n",
-    "        \"expo\": openbb.forecast.expo_chart,\n",
-    "        \"theta\": openbb.forecast.theta_chart,\n",
-    "        \"linregr\": openbb.forecast.linregr_chart,\n",
-    "        \"regr\": openbb.forecast.regr_chart,\n",
-    "        \"rnn\": openbb.forecast.rnn_chart,\n",
-    "        \"brnn\": openbb.forecast.brnn_chart,\n",
-    "        \"nbeats\": openbb.forecast.nbeats_chart,\n",
-    "        \"tcn\": openbb.forecast.tcn_chart,\n",
-    "        \"trans\": openbb.forecast.trans_chart,\n",
-    "        \"tft\": openbb.forecast.tft_chart,\n",
-    "        \"nhits\": openbb.forecast.nhits_chart,\n",
-    "    }\n",
-    "\n",
-    "    feat_engs = {\n",
-    "        \"ema\": openbb.forecast.ema,\n",
-    "        \"sto\": openbb.forecast.sto,\n",
-    "        \"rsi\": openbb.forecast.rsi,\n",
-    "        \"roc\": openbb.forecast.roc,\n",
-    "        \"mom\": openbb.forecast.mom,\n",
-    "        \"atr\": openbb.forecast.atr,\n",
-    "        \"delta\": openbb.forecast.delta,\n",
-    "        \"signal\": openbb.forecast.signal,\n",
-    "    }\n",
-    "except AttributeError as e:\n",
-    "    print(e)\n",
-    "    has_forecast = False\n",
-    "    model_opts = {}\n",
-    "    feat_engs = {}\n",
-    "\n",
-    "interval_opts = [\n",
-    "    \"1m\",\n",
-    "    \"2m\",\n",
-    "    \"5m\",\n",
-    "    \"15m\",\n",
-    "    \"30m\",\n",
-    "    \"60m\",\n",
-    "    \"90m\",\n",
-    "    \"1h\",\n",
-    "    \"1d\",\n",
-    "    \"5d\",\n",
-    "    \"1wk\",\n",
-    "    \"1mo\",\n",
-    "    \"3mo\",\n",
-    "]\n",
-    "\n",
-    "\n",
-    "def format_df(df: pd.DataFrame) -> pd.DataFrame:\n",
-    "    if len(df.columns) != 6:\n",
-    "        df.columns = [\"_\".join(col).strip() for col in df.columns.values]\n",
-    "    df.reset_index(inplace=True)\n",
-    "    df.columns = [x.lower() for x in df.columns]\n",
-    "    return df\n",
-    "\n",
-    "\n",
-    "def has_parameter(func: Callable[..., Any], parameter: str) -> bool:\n",
-    "    params = signature(func).parameters\n",
-    "    parameters = params.keys()\n",
-    "    return parameter in parameters"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f8c2f65c",
-   "metadata": {
-    "tags": [
-     "parameters"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "class Chart:\n",
-    "    def __init__(self):\n",
-    "        self.last_tickers = \"\"\n",
-    "        self.last_interval = \"1d\"\n",
-    "        self.df = pd.DataFrame()\n",
-    "        self.result = pd.DataFrame()\n",
-    "        self.infos = {}\n",
-    "\n",
-    "    def handle_changes(\n",
-    "        self,\n",
-    "        past_covariates,\n",
-    "        start,\n",
-    "        end,\n",
-    "        interval,\n",
-    "        tickers,\n",
-    "        target_column,\n",
-    "        model,\n",
-    "        naive,\n",
-    "        forecast_only,\n",
-    "    ):\n",
-    "        ticker_list = tickers.split(\",\")\n",
-    "        if ticker_list:\n",
-    "            if tickers != self.last_tickers or interval != self.last_interval:\n",
-    "                if interval in [\"1d\", \"5d\", \"1wk\", \"1mo\", \"3mo\"]:\n",
-    "                    self.df = yf.download(\n",
-    "                        tickers, period=\"max\", interval=interval, progress=False\n",
-    "                    )\n",
-    "                else:\n",
-    "                    end_date = end + timedelta(days=1)\n",
-    "                    self.df = yf.download(\n",
-    "                        tickers,\n",
-    "                        start=start,\n",
-    "                        end=end_date,\n",
-    "                        interval=interval,\n",
-    "                        progress=False,\n",
-    "                    )\n",
-    "                self.df = format_df(self.df)\n",
-    "                self.last_tickers = tickers\n",
-    "                self.last_interval = interval\n",
-    "            forecast_model = model_opts[model]\n",
-    "            self.forecast_model = forecast_model\n",
-    "            contains_covariates = has_parameter(forecast_model, \"past_covariates\")\n",
-    "\n",
-    "            # Update Inputs\n",
-    "            if list(target_widget.options) != [\n",
-    "                x for x in self.df.columns if x != \"date\"\n",
-    "            ]:\n",
-    "                target_widget.options = [x for x in self.df.columns if x != \"date\"]\n",
-    "                return\n",
-    "            if list(past_covs_widget.options) != [\n",
-    "                x for x in self.df.columns if x != \"date\"\n",
-    "            ]:\n",
-    "                past_covs_widget.options = [x for x in self.df.columns if x != \"date\"]\n",
-    "                past_covs_widget.disabled = not contains_covariates\n",
-    "                return\n",
-    "            if past_covs_widget.disabled == contains_covariates:\n",
-    "                past_covs_widget.disabled = not contains_covariates\n",
-    "            column_widget.options = [x for x in self.df.columns if x != \"date\"]\n",
-    "\n",
-    "            start_n = datetime(start.year, start.month, start.day)\n",
-    "            end_n = datetime(end.year, end.month, end.day)\n",
-    "            calcs = self.df\n",
-    "            if interval in [\"1d\", \"5d\", \"1wk\", \"1mo\", \"3mo\"]:\n",
-    "                result = calcs.loc[\n",
-    "                    (calcs[\"date\"] >= start_n) & (calcs[\"date\"] <= end_n)\n",
-    "                ]\n",
-    "            else:\n",
-    "                result = calcs\n",
-    "            if not target_column:\n",
-    "                target_column = self.df.columns[0]\n",
-    "            kwargs = {}\n",
-    "            if contains_covariates and past_covariates != ():\n",
-    "                kwargs[\"past_covariates\"] = \",\".join(past_covariates)\n",
-    "            if has_parameter(forecast_model, \"naive\"):\n",
-    "                kwargs[\"naive\"] = naive\n",
-    "            if has_parameter(forecast_model, \"forecast_only\"):\n",
-    "                kwargs[\"forecast_only\"] = forecast_only\n",
-    "            # This sets up everything to run the function on button click\n",
-    "\n",
-    "            self.result = result\n",
-    "            self.target_column = target_column\n",
-    "            self.n_predict = 5\n",
-    "            self.kwargs = kwargs\n",
-    "\n",
-    "    def handle_click(self, to_run):\n",
-    "        if to_run:\n",
-    "            run_widget.value = False\n",
-    "        else:\n",
-    "            df = self.result.dropna()\n",
-    "            if not df.empty:\n",
-    "                self.forecast_model(\n",
-    "                    self.result,\n",
-    "                    target_column=self.target_column,\n",
-    "                    n_predict=5,\n",
-    "                    **self.kwargs\n",
-    "                )\n",
-    "\n",
-    "    def handle_eng(self, target, feature):\n",
-    "        self.feature_target = target\n",
-    "        self.feature_model = feat_engs[feature]\n",
-    "\n",
-    "    def handle_click2(self, to_run):\n",
-    "        if to_run:\n",
-    "            add_widget.value = False\n",
-    "        else:\n",
-    "            kwargs = {}\n",
-    "            if has_parameter(self.feature_model, \"target_column\"):\n",
-    "                kwargs[\"target_column\"] = self.feature_target\n",
-    "            self.df = self.feature_model(self.df, **kwargs)\n",
-    "            past_covs_widget.options = self.df.columns"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e0d4de31-1b4f-4c1f-8467-ca314a578d56",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "w_auto = widgets.Layout(width=\"auto\")\n",
-    "model_value = list(model_opts)[0] if model_opts else None\n",
-    "model_widget = widgets.Select(\n",
-    "    options=list(model_opts),\n",
-    "    value=model_value,\n",
-    "    layout=widgets.Layout(\n",
-    "        width=\"8%\",\n",
-    "    ),\n",
-    ")\n",
-    "past_covs_widget = widgets.SelectMultiple(\n",
-    "    options=[\"\"],\n",
-    "    value=[\"\"],\n",
-    "    layout=widgets.Layout(\n",
-    "        width=\"8%\",\n",
-    "    ),\n",
-    ")\n",
-    "\n",
-    "base_date = (datetime.today() - timedelta(days=365)).date()\n",
-    "start_widget = widgets.DatePicker(value=base_date, layout=w_auto, description=\"Start\")\n",
-    "end_widget = widgets.DatePicker(\n",
-    "    value=datetime.today().date(), layout=w_auto, description=\"End\"\n",
-    ")\n",
-    "\n",
-    "target_widget = widgets.Dropdown(options=[\"\"], value=\"\", description=\"Target\")\n",
-    "interval_widget = widgets.Dropdown(\n",
-    "    options=interval_opts, value=\"1d\", layout=w_auto, description=\"Interval\"\n",
-    ")\n",
-    "tickers_widget = widgets.Textarea(\n",
-    "    value=\"TSLA,\", layout=widgets.Layout(width=\"auto\", height=\"100%\")\n",
-    ")\n",
-    "\n",
-    "# Output box\n",
-    "naive_widget = widgets.ToggleButton(value=False, description=\"Show Naive\")\n",
-    "forecast_only_widget = widgets.ToggleButton(value=False, description=\"Forecast Only\")\n",
-    "run_widget = widgets.ToggleButton(value=False, description=\"Run Model\")\n",
-    "\n",
-    "# feat_box\n",
-    "feat_value = list(feat_engs.keys())[0] if feat_engs else None\n",
-    "column_widget = widgets.Dropdown(options=[\"\"], value=\"\", description=\"Target\")\n",
-    "feat_widget = widgets.Dropdown(\n",
-    "    options=list(feat_engs.keys()), value=feat_value, description=\"Feature\"\n",
-    ")\n",
-    "add_widget = widgets.ToggleButton(\n",
-    "    value=False, description=\"Add Feature\", layout=widgets.Layout(align=\"flex_end\")\n",
-    ")  # get this to work\n",
-    "\n",
-    "selection_box = widgets.VBox([tickers_widget, target_widget])\n",
-    "date_box = widgets.VBox([start_widget, end_widget, interval_widget])\n",
-    "output_box = widgets.VBox([naive_widget, forecast_only_widget, run_widget])\n",
-    "feat_box = widgets.VBox([column_widget, feat_widget, add_widget])\n",
-    "controls = widgets.HBox(\n",
-    "    [selection_box, model_widget, past_covs_widget, date_box, output_box, feat_box],\n",
-    ")\n",
-    "if has_forecast:\n",
-    "    chart = Chart()\n",
-    "    widgets.interactive_output(\n",
-    "        chart.handle_changes,\n",
-    "        {\n",
-    "            \"past_covariates\": past_covs_widget,\n",
-    "            \"start\": start_widget,\n",
-    "            \"end\": end_widget,\n",
-    "            \"interval\": interval_widget,\n",
-    "            \"tickers\": tickers_widget,\n",
-    "            \"target_column\": target_widget,\n",
-    "            \"model\": model_widget,\n",
-    "            \"naive\": naive_widget,\n",
-    "            \"forecast_only\": forecast_only_widget,\n",
-    "        },\n",
-    "    )\n",
-    "\n",
-    "    widgets.interactive_output(\n",
-    "        chart.handle_eng, {\"target\": column_widget, \"feature\": feat_widget}\n",
-    "    )\n",
-    "    widgets.interactive_output(chart.handle_click2, {\"to_run\": add_widget})\n",
-    "\n",
-    "    stocks_view = widgets.interactive_output(chart.handle_click, {\"to_run\": run_widget})\n",
-    "\n",
-    "    title_html = \"<h1>Timeseries Forecasting Dashboard</h1>\"\n",
-    "    warning_html = '<p style=\"color:red\"=>Use a comma after EVERY stock typed.</p>'\n",
-    "\n",
-    "    app_contents = [\n",
-    "        widgets.HTML(title_html),\n",
-    "        controls,\n",
-    "        widgets.HTML(warning_html),\n",
-    "        stocks_view,\n",
-    "    ]\n",
-    "    app = widgets.VBox(app_contents)\n",
-    "else:\n",
-    "    title_html = \"<h1>Timeseries Forecasting Dashboard</h1>\"\n",
-    "    warning_html = (\n",
-    "        '<p style=\"color:red\"=>The forecasting dependencies are not installed.</p>'\n",
-    "    )\n",
-    "    app = widgets.VBox([widgets.HTML(title_html), widgets.HTML(warning_html)])\n",
-    "display(app)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9dbf43a2-70e1-44e9-a524-be3e97008b58",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.6"
-  },
-  "metadata": {
-   "interpreter": {
-    "hash": "e896a00ead8b521528d79ac9ef24990696f2b751eb283ab8e0d078c9c4971ffc"
-   }
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "bd3088e2ce83c7406a082a5b650cfc74fd1480320510d276c9fa5780b96e5fae"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+    "cells": [
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e9ad60bc",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from datetime import datetime, timedelta\n",
+                "from typing import Callable, Any\n",
+                "from inspect import signature\n",
+                "import warnings, logging\n",
+                "\n",
+                "import ipywidgets as widgets\n",
+                "import yfinance as yf\n",
+                "import pandas as pd\n",
+                "from IPython.display import display\n",
+                "\n",
+                "theme.apply_style()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "404cb982",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Suppressing sdk logs\n",
+                "import openbb_terminal.config_terminal as cfg\n",
+                "cfg.change_logging_suppress(new_value=True)\n",
+                "\n",
+                "# Import the OpenBB SDK\n",
+                "from openbb_terminal.sdk import openbb, widgets"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "beb36881",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "try:\n",
+                "    has_forecast = True\n",
+                "    model_opts = {\n",
+                "        \"expo\": openbb.forecast.expo_chart,\n",
+                "        \"theta\": openbb.forecast.theta_chart,\n",
+                "        \"linregr\": openbb.forecast.linregr_chart,\n",
+                "        \"regr\": openbb.forecast.regr_chart,\n",
+                "        \"rnn\": openbb.forecast.rnn_chart,\n",
+                "        \"brnn\": openbb.forecast.brnn_chart,\n",
+                "        \"nbeats\": openbb.forecast.nbeats_chart,\n",
+                "        \"tcn\": openbb.forecast.tcn_chart,\n",
+                "        \"trans\": openbb.forecast.trans_chart,\n",
+                "        \"tft\": openbb.forecast.tft_chart,\n",
+                "        \"nhits\": openbb.forecast.nhits_chart,\n",
+                "    }\n",
+                "\n",
+                "    feat_engs = {\n",
+                "        \"ema\": openbb.forecast.ema,\n",
+                "        \"sto\": openbb.forecast.sto,\n",
+                "        \"rsi\": openbb.forecast.rsi,\n",
+                "        \"roc\": openbb.forecast.roc,\n",
+                "        \"mom\": openbb.forecast.mom,\n",
+                "        \"atr\": openbb.forecast.atr,\n",
+                "        \"delta\": openbb.forecast.delta,\n",
+                "        \"signal\": openbb.forecast.signal,\n",
+                "    }\n",
+                "except AttributeError as e:\n",
+                "    print(e)\n",
+                "    has_forecast = False\n",
+                "    model_opts = {}\n",
+                "    feat_engs = {}\n",
+                "\n",
+                "interval_opts = [\n",
+                "    \"1m\",\n",
+                "    \"2m\",\n",
+                "    \"5m\",\n",
+                "    \"15m\",\n",
+                "    \"30m\",\n",
+                "    \"60m\",\n",
+                "    \"90m\",\n",
+                "    \"1h\",\n",
+                "    \"1d\",\n",
+                "    \"5d\",\n",
+                "    \"1wk\",\n",
+                "    \"1mo\",\n",
+                "    \"3mo\",\n",
+                "]\n",
+                "\n",
+                "\n",
+                "def format_df(df: pd.DataFrame) -> pd.DataFrame:\n",
+                "    if len(df.columns) != 6:\n",
+                "        df.columns = [\"_\".join(col).strip() for col in df.columns.values]\n",
+                "    df.reset_index(inplace=True)\n",
+                "    df.columns = [x.lower() for x in df.columns]\n",
+                "    return df\n",
+                "\n",
+                "\n",
+                "def has_parameter(func: Callable[..., Any], parameter: str) -> bool:\n",
+                "    params = signature(func).parameters\n",
+                "    parameters = params.keys()\n",
+                "    return parameter in parameters"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "f8c2f65c",
+            "metadata": {
+                "tags": [
+                    "parameters"
+                ]
+            },
+            "outputs": [],
+            "source": [
+                "class Chart:\n",
+                "    def __init__(self):\n",
+                "        self.last_tickers = \"\"\n",
+                "        self.last_interval = \"1d\"\n",
+                "        self.df = pd.DataFrame()\n",
+                "        self.result = pd.DataFrame()\n",
+                "        self.infos = {}\n",
+                "\n",
+                "    def handle_changes(\n",
+                "        self,\n",
+                "        past_covariates,\n",
+                "        start,\n",
+                "        end,\n",
+                "        interval,\n",
+                "        tickers,\n",
+                "        target_column,\n",
+                "        model,\n",
+                "        naive,\n",
+                "        forecast_only,\n",
+                "    ):\n",
+                "        ticker_list = tickers.split(\",\")\n",
+                "        if ticker_list:\n",
+                "            if tickers != self.last_tickers or interval != self.last_interval:\n",
+                "                if interval in [\"1d\", \"5d\", \"1wk\", \"1mo\", \"3mo\"]:\n",
+                "                    self.df = yf.download(\n",
+                "                        tickers, period=\"max\", interval=interval, progress=False\n",
+                "                    )\n",
+                "                else:\n",
+                "                    end_date = end + timedelta(days=1)\n",
+                "                    self.df = yf.download(\n",
+                "                        tickers,\n",
+                "                        start=start,\n",
+                "                        end=end_date,\n",
+                "                        interval=interval,\n",
+                "                        progress=False,\n",
+                "                    )\n",
+                "                self.df = format_df(self.df)\n",
+                "                self.last_tickers = tickers\n",
+                "                self.last_interval = interval\n",
+                "            forecast_model = model_opts[model]\n",
+                "            self.forecast_model = forecast_model\n",
+                "            contains_covariates = has_parameter(forecast_model, \"past_covariates\")\n",
+                "\n",
+                "            # Update Inputs\n",
+                "            if list(target_widget.options) != [\n",
+                "                x for x in self.df.columns if x != \"date\"\n",
+                "            ]:\n",
+                "                target_widget.options = [x for x in self.df.columns if x != \"date\"]\n",
+                "                return\n",
+                "            if list(past_covs_widget.options) != [\n",
+                "                x for x in self.df.columns if x != \"date\"\n",
+                "            ]:\n",
+                "                past_covs_widget.options = [x for x in self.df.columns if x != \"date\"]\n",
+                "                past_covs_widget.disabled = not contains_covariates\n",
+                "                return\n",
+                "            if past_covs_widget.disabled == contains_covariates:\n",
+                "                past_covs_widget.disabled = not contains_covariates\n",
+                "            column_widget.options = [x for x in self.df.columns if x != \"date\"]\n",
+                "\n",
+                "            start_n = datetime(start.year, start.month, start.day)\n",
+                "            end_n = datetime(end.year, end.month, end.day)\n",
+                "            calcs = self.df\n",
+                "            if interval in [\"1d\", \"5d\", \"1wk\", \"1mo\", \"3mo\"]:\n",
+                "                result = calcs.loc[\n",
+                "                    (calcs[\"date\"] >= start_n) & (calcs[\"date\"] <= end_n)\n",
+                "                ]\n",
+                "            else:\n",
+                "                result = calcs\n",
+                "            if not target_column:\n",
+                "                target_column = self.df.columns[0]\n",
+                "            kwargs = {}\n",
+                "            if contains_covariates and past_covariates != ():\n",
+                "                kwargs[\"past_covariates\"] = \",\".join(past_covariates)\n",
+                "            if has_parameter(forecast_model, \"naive\"):\n",
+                "                kwargs[\"naive\"] = naive\n",
+                "            if has_parameter(forecast_model, \"forecast_only\"):\n",
+                "                kwargs[\"forecast_only\"] = forecast_only\n",
+                "            # This sets up everything to run the function on button click\n",
+                "\n",
+                "            self.result = result\n",
+                "            self.target_column = target_column\n",
+                "            self.n_predict = 5\n",
+                "            self.kwargs = kwargs\n",
+                "\n",
+                "    def handle_click(self, to_run):\n",
+                "        if to_run:\n",
+                "            run_widget.value = False\n",
+                "        else:\n",
+                "            df = self.result.dropna()\n",
+                "            if not df.empty:\n",
+                "                self.forecast_model(\n",
+                "                    self.result,\n",
+                "                    target_column=self.target_column,\n",
+                "                    n_predict=5,\n",
+                "                    **self.kwargs\n",
+                "                )\n",
+                "\n",
+                "    def handle_eng(self, target, feature):\n",
+                "        self.feature_target = target\n",
+                "        self.feature_model = feat_engs[feature]\n",
+                "\n",
+                "    def handle_click2(self, to_run):\n",
+                "        if to_run:\n",
+                "            add_widget.value = False\n",
+                "        else:\n",
+                "            kwargs = {}\n",
+                "            if has_parameter(self.feature_model, \"target_column\"):\n",
+                "                kwargs[\"target_column\"] = self.feature_target\n",
+                "            self.df = self.feature_model(self.df, **kwargs)\n",
+                "            past_covs_widget.options = self.df.columns"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e0d4de31-1b4f-4c1f-8467-ca314a578d56",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "w_auto = widgets.Layout(width=\"auto\")\n",
+                "model_value = list(model_opts)[0] if model_opts else None\n",
+                "model_widget = widgets.Select(\n",
+                "    options=list(model_opts),\n",
+                "    value=model_value,\n",
+                "    layout=widgets.Layout(\n",
+                "        width=\"8%\",\n",
+                "    ),\n",
+                ")\n",
+                "past_covs_widget = widgets.SelectMultiple(\n",
+                "    options=[\"\"],\n",
+                "    value=[\"\"],\n",
+                "    layout=widgets.Layout(\n",
+                "        width=\"8%\",\n",
+                "    ),\n",
+                ")\n",
+                "\n",
+                "base_date = (datetime.today() - timedelta(days=365)).date()\n",
+                "start_widget = widgets.DatePicker(value=base_date, layout=w_auto, description=\"Start\")\n",
+                "end_widget = widgets.DatePicker(\n",
+                "    value=datetime.today().date(), layout=w_auto, description=\"End\"\n",
+                ")\n",
+                "\n",
+                "target_widget = widgets.Dropdown(options=[\"\"], value=\"\", description=\"Target\")\n",
+                "interval_widget = widgets.Dropdown(\n",
+                "    options=interval_opts, value=\"1d\", layout=w_auto, description=\"Interval\"\n",
+                ")\n",
+                "tickers_widget = widgets.Textarea(\n",
+                "    value=\"TSLA,\", layout=widgets.Layout(width=\"auto\", height=\"100%\")\n",
+                ")\n",
+                "\n",
+                "# Output box\n",
+                "naive_widget = widgets.ToggleButton(value=False, description=\"Show Naive\")\n",
+                "forecast_only_widget = widgets.ToggleButton(value=False, description=\"Forecast Only\")\n",
+                "run_widget = widgets.ToggleButton(value=False, description=\"Run Model\")\n",
+                "\n",
+                "# feat_box\n",
+                "feat_value = list(feat_engs.keys())[0] if feat_engs else None\n",
+                "column_widget = widgets.Dropdown(options=[\"\"], value=\"\", description=\"Target\")\n",
+                "feat_widget = widgets.Dropdown(\n",
+                "    options=list(feat_engs.keys()), value=feat_value, description=\"Feature\"\n",
+                ")\n",
+                "add_widget = widgets.ToggleButton(\n",
+                "    value=False, description=\"Add Feature\", layout=widgets.Layout(align=\"flex_end\")\n",
+                ")  # get this to work\n",
+                "\n",
+                "selection_box = widgets.VBox([tickers_widget, target_widget])\n",
+                "date_box = widgets.VBox([start_widget, end_widget, interval_widget])\n",
+                "output_box = widgets.VBox([naive_widget, forecast_only_widget, run_widget])\n",
+                "feat_box = widgets.VBox([column_widget, feat_widget, add_widget])\n",
+                "controls = widgets.HBox(\n",
+                "    [selection_box, model_widget, past_covs_widget, date_box, output_box, feat_box],\n",
+                ")\n",
+                "if has_forecast:\n",
+                "    chart = Chart()\n",
+                "    widgets.interactive_output(\n",
+                "        chart.handle_changes,\n",
+                "        {\n",
+                "            \"past_covariates\": past_covs_widget,\n",
+                "            \"start\": start_widget,\n",
+                "            \"end\": end_widget,\n",
+                "            \"interval\": interval_widget,\n",
+                "            \"tickers\": tickers_widget,\n",
+                "            \"target_column\": target_widget,\n",
+                "            \"model\": model_widget,\n",
+                "            \"naive\": naive_widget,\n",
+                "            \"forecast_only\": forecast_only_widget,\n",
+                "        },\n",
+                "    )\n",
+                "\n",
+                "    widgets.interactive_output(\n",
+                "        chart.handle_eng, {\"target\": column_widget, \"feature\": feat_widget}\n",
+                "    )\n",
+                "    widgets.interactive_output(chart.handle_click2, {\"to_run\": add_widget})\n",
+                "\n",
+                "    stocks_view = widgets.interactive_output(chart.handle_click, {\"to_run\": run_widget})\n",
+                "\n",
+                "    title_html = \"<h1>Timeseries Forecasting Dashboard</h1>\"\n",
+                "    warning_html = '<p style=\"color:red\"=>Use a comma after EVERY stock typed.</p>'\n",
+                "\n",
+                "    app_contents = [\n",
+                "        widgets.HTML(title_html),\n",
+                "        controls,\n",
+                "        widgets.HTML(warning_html),\n",
+                "        stocks_view,\n",
+                "    ]\n",
+                "    app = widgets.VBox(app_contents)\n",
+                "else:\n",
+                "    title_html = \"<h1>Timeseries Forecasting Dashboard</h1>\"\n",
+                "    warning_html = (\n",
+                "        '<p style=\"color:red\"=>The forecasting dependencies are not installed.</p>'\n",
+                "    )\n",
+                "    app = widgets.VBox([widgets.HTML(title_html), widgets.HTML(warning_html)])\n",
+                "display(app)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "9dbf43a2-70e1-44e9-a524-be3e97008b58",
+            "metadata": {},
+            "outputs": [],
+            "source": []
+        }
+    ],
+    "metadata": {
+        "kernelspec": {
+            "display_name": "Python 3 (ipykernel)",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.9.6"
+        },
+        "metadata": {
+            "interpreter": {
+                "hash": "e896a00ead8b521528d79ac9ef24990696f2b751eb283ab8e0d078c9c4971ffc"
+            }
+        },
+        "vscode": {
+            "interpreter": {
+                "hash": "bd3088e2ce83c7406a082a5b650cfc74fd1480320510d276c9fa5780b96e5fae"
+            }
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 5
+}
\ No newline at end of file
diff --git a/openbb_terminal/reports/reports_controller.py b/openbb_terminal/reports/reports_controller.py
index 4116e2b6060..bea8bdd83ce 100644
--- a/openbb_terminal/reports/reports_controller.py
+++ b/openbb_terminal/reports/reports_controller.py
@@ -8,7 +8,6 @@ import os
 # pylint: disable=R1732, R0912
 from typing import Any, Dict, List, Optional
 
-import openbb_terminal.config_terminal as cfg
 from openbb_terminal.core.session.current_user import get_current_user
 from openbb_terminal.custom_prompt_toolkit import NestedCompleter
 from openbb_terminal.decorators import log_start_end
@@ -191,7 +190,6 @@ class ReportController(BaseController):
             ns_parser = self.parse_simple_args(parser, other_args)
 
             if ns_parser:
-                cfg.change_logging_suppress(new_value=True)
                 if report_name == "equity" and "." in ns_parser.symbol:
                     console.print(
                         "[red]Cannot currently handle tickers with a '.' in them[/red]\n"
@@ -203,7 +201,6 @@ class ReportController(BaseController):
                     input_path=str(reports_model.REPORTS_FOLDER / report_name),
                     args_dict=parameters,
                 )
-                cfg.change_logging_suppress(new_value=False)
 
         else:
             console.print("[red]Notebook not found![/red]\n")
diff --git a/openbb_terminal/reports/reports_model.py b/openbb_terminal/reports/reports_model.py
index f16f3782c31..2c323d12fb9 100644
--- a/openbb_terminal/reports/reports_model.py
+++ b/openbb_terminal/reports/reports_model.py
@@ -5,12 +5,12 @@ import logging
 
 # pylint: disable=R1732, R0912
 import os
-from ast import literal_eval
 from datetime import datetime
 from pathlib import Path
 from threading import Thread
 from typing import Any, Dict, List, Union
 
+import nbformat
 import pandas as pd
 import papermill as pm
 from ipykernel.kernelapp import IPKernelApp
@@ -85,6 +85,7 @@ REPORT_CHOICES = {
         "--symbol": {c: None for c in STOCKS_TICKERS + ETF_TICKERS},
     },
 }
+TARGET_TAG = "parameters"
 
 
 @log_start_end(log=logger)
@@ -157,43 +158,34 @@ def extract_parameters(input_path: str) -> Dict[str, str]:
 
     input_path = add_ipynb_extension(input_path)
 
-    with open(input_path, encoding="utf-8") as file:
-        notebook_content = file.read()
+    with open(input_path) as f:
+        nb = nbformat.read(f, as_version=nbformat.NO_CONVERT)
 
-    # Look for the metadata cell to understand if there are parameters required by the report
-    metadata_cell = """"metadata": {\n    "tags": [\n     "parameters"\n    ]\n   },\n   "outputs":"""
+    target_tag = TARGET_TAG
 
-    # Locate position of the data of interest and get parameters
-    if notebook_content.find(metadata_cell) >= 0:
-        position = notebook_content.find(metadata_cell)
-    else:
-        return {}
+    cell_lines = []
+    for cell in nb.cells:
+        # Filter cells by tag
+        if target_tag in cell.metadata.get("tags", []):
+            # Split cell source into separate lines
+            lines = cell.source.split("\n")
+            # Remove empty and commented lines
+            lines = [
+                line for line in lines if line.strip() and not line.startswith("#")
+            ]
+            cell_lines.extend(lines)
 
-    metadata = notebook_content[position:]  # noqa: E203
-    cell_start = 'source": '
-    cell_end = "]"
-    start_position = metadata.find(cell_start)
-    params = metadata[
-        start_position : metadata.find(cell_end, start_position) + 1  # noqa: E203
-    ]
+    parameters_dict = {}
+    for line in cell_lines:
+        # Extract key and value from each line
+        key, value = line.split("=")
+        key = key.strip()
+        value = value.strip()
+        # Add key-value pair to dictionary
+        parameters_dict[key] = value
 
-    # Make sure that the parameters provided are relevant
-    if "parameters" in notebook_content:
-        parameters_names = [
-            param.split("=")[0][:-1]
-            for param in literal_eval(params.strip('source": '))
-            if param[0] not in ["#", "\n"]
-        ]
-        parameters_values = [
-            param.split("=")[1][2:-2]
-            for param in literal_eval(params.strip('source": '))
-            if param[0] not in ["#", "\n"]
-        ]
-
-    if "report_name" in parameters_names:
-        parameters_names.remove("report_name")
-
-    parameters_dict = dict(zip(parameters_names, parameters_values))
+    if "report_name" in parameters_dict:
+        parameters_dict.pop("report_name")
 
     return parameters_dict
 
diff --git a/openbb_terminal/reports/templates/crypto.ipynb b/openbb_terminal/reports/templates/crypto.ipynb
index 1746dede123..e99939b124f 100644
--- a/openbb_terminal/reports/templates/crypto.ipynb
+++ b/openbb_terminal/reports/templates/crypto.ipynb
@@ -1,1148 +1,1160 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "70ba2c8a",
-   "metadata": {},
-   "source": [
-    "## Notebook setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "driven-billion",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "import io\n",
-    "import warnings\n",
-    "import datetime\n",
-    "import numpy as np\n",
-    "import base64\n",
-    "import pandas as pd\n",
-    "from typing import List\n",
-    "\n",
-    "from IPython.display import HTML\n",
-    "\n",
-    "import openbb_terminal.config_terminal as cfg\n",
-    "from openbb_terminal.reports import widget_helpers as widgets\n",
-    "from openbb_terminal.sdk import openbb\n",
-    "from openbb_terminal.helper_classes import TerminalStyle\n",
-    "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
-    "from openbb_terminal import OpenBBFigure\n",
-    "\n",
-    "\n",
-    "warnings.filterwarnings(\"ignore\")\n",
-    "\n",
-    "pd.set_option(\"display.float_format\", lambda x: \"%.5f\" % x)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from openbb_terminal.core.session.current_user import get_current_user\n",
-    "\n",
-    "user = get_current_user()\n",
-    "\n",
-    "cfg.theme = TerminalStyle(\n",
-    "    user.preferences.MPL_STYLE,\n",
-    "    user.preferences.PMF_STYLE,\n",
-    "    user.preferences.RICH_STYLE,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c52f83e1",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "stylesheet = widgets.html_report_stylesheet()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "807fda4e",
-   "metadata": {},
-   "source": [
-    "## Select Ticker"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "intended-sherman",
-   "metadata": {
-    "tags": [
-     "parameters"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "# Parameters that will be replaced when calling this notebook\n",
-    "# Do not leave parameters blank as notebook will not run otherwise\n",
-    "symbol = \"BTC\"\n",
-    "report_name = f\"Crypto Report for {symbol}\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2c46efb8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ticker = symbol"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d4897334",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "author = \"\"\n",
-    "report_title = f\"INVESTMENT RESEARCH REPORT ON {ticker.upper()}\"\n",
-    "report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
-    "report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
-    "report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
-    "report_title, report_date, report_time, report_timezone"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "35d9a943",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# basic info\n",
-    "\n",
-    "basic_info = openbb.crypto.dd.basic(ticker)\n",
-    "if not basic_info.empty:\n",
-    "    basic_info = basic_info.set_index(\"Metric\")\n",
-    "    basic_info"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "091d305e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "news = openbb.crypto.dd.news(symbol=ticker).head(10)\n",
-    "\n",
-    "if (isinstance(news, pd.DataFrame) and not news.empty) or (\n",
-    "    not isinstance(news, pd.DataFrame) and news\n",
-    "):\n",
-    "    news = news.set_index(\"published_at\")\n",
-    "    news.sort_index()\n",
-    "    news[\"link\"] = news[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
-    "    news\n",
-    "else:\n",
-    "    news = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "bd281ab8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "links = openbb.crypto.dd.links(ticker)\n",
-    "\n",
-    "if (isinstance(links, pd.DataFrame) and not links.empty) or (\n",
-    "    not isinstance(links, pd.DataFrame) and links\n",
-    "):\n",
-    "    links[\"Link\"] = links[\"Link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
-    "    links\n",
-    "else:\n",
-    "    links = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "07d09ce8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "five_year = datetime.datetime.now() - datetime.timedelta(days=1825)\n",
-    "three_year = datetime.datetime.now() - datetime.timedelta(days=1095)\n",
-    "one_year = datetime.datetime.now() - datetime.timedelta(days=365)\n",
-    "three_months = datetime.datetime.now() - datetime.timedelta(days=90)\n",
-    "\n",
-    "dates = {\n",
-    "    \"three_months\": three_months,\n",
-    "    \"one_year\": one_year,\n",
-    "    \"three_year\": three_year,\n",
-    "    \"five_year\": five_year,\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e6d6d43d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from tkinter.filedialog import Open\n",
-    "\n",
-    "\n",
-    "def get_historical_data(ticker, dict_of_dates, is_plot=True) -> List[pd.DataFrame]:\n",
-    "    list_of_historical_data = []\n",
-    "\n",
-    "    for date in dict_of_dates:\n",
-    "        data = openbb.crypto.load(\n",
-    "            symbol=ticker,\n",
-    "            to_symbol=\"usd\",\n",
-    "            start_date=dict_of_dates[date],\n",
-    "            source=\"YahooFinance\",\n",
-    "        )\n",
-    "\n",
-    "        if data.empty:\n",
-    "            continue\n",
-    "\n",
-    "        # we'll be using the adjusted close price as same as close price\n",
-    "        data[\"Adj Close\"] = data[\"Close\"]\n",
-    "\n",
-    "        if is_plot:\n",
-    "            fig = OpenBBFigure(yaxis_title=\"USDT\").set_title(\n",
-    "                f\"{date} historical data for {ticker.upper()}\"\n",
-    "            )\n",
-    "            fig.add_scatter(x=data.index, y=data[\"Adj Close\"], name=\"Close\")\n",
-    "\n",
-    "            plot_data = fig.to_html()\n",
-    "\n",
-    "            list_of_historical_data.append(plot_data)\n",
-    "        else:\n",
-    "            list_of_historical_data.append(data)\n",
-    "\n",
-    "    return list_of_historical_data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ed19a708",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "try:\n",
-    "    historical_data = get_historical_data(ticker, dates)\n",
-    "except Exception as e:\n",
-    "    raise KeyboardInterrupt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8f815dbc",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "historical_data_one_year = get_historical_data(ticker, {\"one_year\": one_year}, False)[0]\n",
-    "historical_data_one_year"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "081a4bb3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from openbb_terminal.cryptocurrency.cryptocurrency_helpers import show_quick_performance\n",
-    "\n",
-    "show_quick_performance(\n",
-    "    crypto_df=historical_data_one_year,\n",
-    "    symbol=ticker,\n",
-    "    current_currency=\"USDT\",\n",
-    "    source=\"YahooFinance\",\n",
-    "    exchange=\"binance\",\n",
-    "    interval=\"1440\",\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "88af0fbe",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "headlines = openbb.crypto.dd.headlines_chart(ticker, external_axes=True)\n",
-    "\n",
-    "if headlines:\n",
-    "    headlines = headlines.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e4509c6e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "candle_one_year = openbb.crypto.chart(\n",
-    "    historical_data_one_year,\n",
-    "    to_symbol=ticker,\n",
-    "    from_symbol=\"USDT\",\n",
-    "    source=\"YahooFinance\",\n",
-    "    exchange=\"binance\",\n",
-    "    interval=\"1440\",\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if candle_one_year:\n",
-    "    candle_one_year = candle_one_year.to_html()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "7f83daae",
-   "metadata": {},
-   "source": [
-    "## Due Diligence"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "93d66cf1",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# market cap dominance\n",
-    "mcapdom_df = openbb.crypto.dd.mcapdom(symbol=ticker)\n",
-    "\n",
-    "if (isinstance(mcapdom_df, pd.DataFrame) and not mcapdom_df.empty) or (\n",
-    "    not isinstance(mcapdom_df, pd.DataFrame) and mcapdom_df\n",
-    "):\n",
-    "    mcapdom = openbb.crypto.dd.mcapdom_chart(symbol=ticker, external_axes=True)\n",
-    "\n",
-    "    if mcapdom:\n",
-    "        mcapdom = mcapdom.to_html()\n",
-    "else:\n",
-    "    mcapdom_df = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "284b0586",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# roadmap\n",
-    "roadmap_model = openbb.crypto.dd.rm(symbol=ticker)\n",
-    "\n",
-    "if (isinstance(roadmap_model, pd.DataFrame) and not roadmap_model.empty) or (\n",
-    "    not isinstance(roadmap_model, pd.DataFrame) and roadmap_model\n",
-    "):\n",
-    "    roadmap_model = roadmap_model.set_index(\"Date\")\n",
-    "    roadmap_model.sort_index()\n",
-    "\n",
-    "    roadmap_view = openbb.crypto.dd.rm_chart(symbol=ticker, external_axes=True)\n",
-    "    if roadmap_view:\n",
-    "        roadmap_view = roadmap_view.to_html()\n",
-    "\n",
-    "else:\n",
-    "    roadmap_model = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9ddbc654",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "tokenomics_model = openbb.crypto.dd.rm(symbol=ticker)\n",
-    "\n",
-    "if (isinstance(tokenomics_model, pd.DataFrame) and not tokenomics_model.empty) or (\n",
-    "    not isinstance(tokenomics_model, pd.DataFrame) and tokenomics_model\n",
-    "):\n",
-    "    tokenomics_model = tokenomics_model.set_index(\"Date\")\n",
-    "    tokenomics_model.sort_index()\n",
-    "\n",
-    "    tokenomics_view = openbb.crypto.dd.tk_chart(symbol=ticker, external_axes=True)\n",
-    "    if tokenomics_view:\n",
-    "        tokenomics_view = tokenomics_view.to_html()\n",
-    "\n",
-    "else:\n",
-    "    tokenomics_model = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7d02fcc4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# fundraise\n",
-    "fundraise = openbb.crypto.dd.fr(symbol=ticker)  # this returns a tuple\n",
-    "\n",
-    "if fundraise:\n",
-    "    fundraise_info = fundraise[0]\n",
-    "    fundraise_df = fundraise[1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5e625a2e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "trading_pair_info = openbb.crypto.dd.trading_pair_info(f\"{ticker}-USDT\")\n",
-    "if (isinstance(trading_pair_info, pd.DataFrame) and not trading_pair_info.empty) or (\n",
-    "    not isinstance(trading_pair_info, pd.DataFrame) and trading_pair_info\n",
-    "):\n",
-    "    trading_pair_info = trading_pair_info.set_index(\"Metric\")\n",
-    "    trading_pair_info\n",
-    "else:\n",
-    "    trading_pair_info = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8f33b4d8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import openbb_terminal.cryptocurrency.due_diligence.pycoingecko_model as gecko\n",
-    "from openbb_terminal.cryptocurrency.cryptocurrency_helpers import get_coingecko_id\n",
-    "\n",
-    "ath = pd.DataFrame()\n",
-    "try:\n",
-    "    cg_id = get_coingecko_id(symbol=ticker)\n",
-    "    coin = gecko.Coin(ticker)\n",
-    "    ath = coin.get_all_time_high(currency=cg_id)\n",
-    "\n",
-    "except Exception as e:\n",
-    "    print(\"Reached coingecko API limit\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2a82e990",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import openbb_terminal.cryptocurrency.due_diligence.pycoingecko_model as gecko\n",
-    "from openbb_terminal.cryptocurrency.cryptocurrency_helpers import get_coingecko_id\n",
-    "\n",
-    "atl = pd.DataFrame()\n",
-    "try:\n",
-    "    cg_id = get_coingecko_id(symbol=ticker)\n",
-    "    coin = gecko.Coin(ticker)\n",
-    "    atl = coin.get_all_time_low(currency=cg_id)\n",
-    "\n",
-    "except Exception as e:\n",
-    "    print(\"Reached coingecko API limit\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e9e512e9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# market stats about loaded coin\n",
-    "\n",
-    "market = openbb.crypto.dd.mkt(ticker)\n",
-    "\n",
-    "if (isinstance(market, pd.DataFrame) and not market.empty) or (\n",
-    "    not isinstance(market, pd.DataFrame) and market\n",
-    "):\n",
-    "    market = market.set_index(\"exchange\")\n",
-    "\n",
-    "    market[\"market_url\"] = market[\"market_url\"].apply(\n",
-    "        lambda x: f'<a href=\"{x}\">{x}</a>'\n",
-    "    )\n",
-    "    market\n",
-    "else:\n",
-    "    market = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1d6e76cb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# all exchanges where loaded coin is listed\n",
-    "ex = openbb.crypto.dd.ex(ticker)\n",
-    "\n",
-    "if (isinstance(ex, pd.DataFrame) and not ex.empty) or (\n",
-    "    not isinstance(ex, pd.DataFrame) and ex\n",
-    "):\n",
-    "    ex = ex.set_index(\"id\")\n",
-    "    ex\n",
-    "else:\n",
-    "    ex = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1fcdbc67",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# last trades\n",
-    "trades = openbb.crypto.dd.trades(symbol=ticker, exchange_id=\"gemini\", to_symbol=\"USD\")\n",
-    "if (isinstance(trades, pd.DataFrame) and not trades.empty) or (\n",
-    "    not isinstance(trades, pd.DataFrame) and trades\n",
-    "):\n",
-    "    trades = trades.set_index(\"Date\")\n",
-    "    trades\n",
-    "else:\n",
-    "    trades = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "262d190a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# order book\n",
-    "order_book_raw = openbb.crypto.dd.ob(\n",
-    "    symbol=ticker, exchange=\"gemini\", to_symbol=\"USD\"\n",
-    ")  # this returns a dict\n",
-    "\n",
-    "if order_book_raw:\n",
-    "    order_book = openbb.crypto.dd.ob_chart(\n",
-    "        symbol=ticker, exchange=\"gemini\", to_symbol=\"USD\", external_axes=True\n",
-    "    )\n",
-    "    if order_book:\n",
-    "        order_book = order_book.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "679d0d79",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# price and supply related metrics for loaded coin\n",
-    "\n",
-    "ps = openbb.crypto.dd.ps(ticker)\n",
-    "if (isinstance(ps, pd.DataFrame) and not ps.empty) or (\n",
-    "    not isinstance(ps, pd.DataFrame) and ps\n",
-    "):\n",
-    "    ps = ps.set_index(\"Metric\")\n",
-    "    ps\n",
-    "else:\n",
-    "    ps = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "92e76d79",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# events\n",
-    "\n",
-    "events = openbb.crypto.dd.events(ticker)\n",
-    "\n",
-    "if (isinstance(events, pd.DataFrame) and not events.empty) or (\n",
-    "    not isinstance(events, pd.DataFrame) and events\n",
-    "):\n",
-    "    events = events.set_index(\"date\")\n",
-    "    events[\"link\"] = events[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
-    "else:\n",
-    "    events = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a14130db",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# social media\n",
-    "\n",
-    "from openbb_terminal.cryptocurrency.due_diligence.pycoingecko_view import display_social\n",
-    "\n",
-    "display_social(ticker)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8f89627f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# tweets for loaded coin\n",
-    "\n",
-    "tweets = openbb.crypto.dd.twitter(ticker)\n",
-    "tweets"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9bb75443",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# github activity over time\n",
-    "\n",
-    "gh_data = openbb.crypto.dd.gh(symbol=ticker)\n",
-    "\n",
-    "if (isinstance(gh_data, pd.DataFrame) and not gh_data.empty) or (\n",
-    "    not isinstance(gh_data, pd.DataFrame) and gh_data\n",
-    "):\n",
-    "    gh = openbb.crypto.dd.gh_chart(symbol=ticker, external_axes=True)\n",
-    "    if gh:\n",
-    "        gh = gh.to_html()\n",
-    "else:\n",
-    "    gh_data = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "fcaa973d",
-   "metadata": {},
-   "source": [
-    "## TA\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "477317b4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ticker_data = historical_data_one_year.copy()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7af3695c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# simple moving average\n",
-    "ticker_data.index.names = [\"date\"]\n",
-    "\n",
-    "sma = openbb.ta.ma_chart(\n",
-    "    data=ticker_data,\n",
-    "    ma_type=\"SMA\",\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if sma:\n",
-    "    sma = sma.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5d5089fa",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# exponential moving average\n",
-    "ema = openbb.ta.ma_chart(\n",
-    "    data=ticker_data,\n",
-    "    ma_type=\"EMA\",\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if ema:\n",
-    "    ema = ema.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5facfbf4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# zero lag exponential moving average\n",
-    "\n",
-    "zlma = openbb.ta.ma_chart(\n",
-    "    data=ticker_data,\n",
-    "    ma_type=\"ZLMA\",\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if zlma:\n",
-    "    zlma = zlma.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "df54f7ad",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# commodity channel index\n",
-    "\n",
-    "cci = openbb.ta.cci_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if cci:\n",
-    "    cci = cci.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f53469eb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# moving average convergence/divergence\n",
-    "\n",
-    "macd = openbb.ta.macd_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if macd:\n",
-    "    macd = macd.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dd79e6b6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# fisher transform\n",
-    "\n",
-    "fisher = openbb.ta.fisher_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if fisher:\n",
-    "    fisher = fisher.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b699e61f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# aroon indicator\n",
-    "\n",
-    "aroon = openbb.ta.aroon_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if aroon:\n",
-    "    aroon = aroon.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "79401027",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# bollinger bands\n",
-    "\n",
-    "bbands = openbb.ta.bbands_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if bbands:\n",
-    "    bbands = bbands.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0b5e2949",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# fibonacci retracement\n",
-    "\n",
-    "fib = openbb.ta.fib_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if fib:\n",
-    "    fib = fib.to_html()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "48847a7f",
-   "metadata": {},
-   "source": [
-    "## QA"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e77b373b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# summary\n",
-    "\n",
-    "summary = openbb.qa.summary(data=ticker_data)\n",
-    "summary"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3ecfc93e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# normality statistics and tests\n",
-    "\n",
-    "# openbb.qa.normality_chart(\n",
-    "#     data=ticker_data,\n",
-    "#     target=\"Close\",\n",
-    "# )\n",
-    "\n",
-    "normality = openbb.qa.normality(\n",
-    "    data=ticker_data[\"Close\"],\n",
-    ")\n",
-    "normality"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8abe96b0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# box and whisker plot\n",
-    "\n",
-    "bw = openbb.qa.bw(\n",
-    "    symbol=ticker,\n",
-    "    data=ticker_data,\n",
-    "    target=\"Close\",\n",
-    "    yearly=False,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if bw:\n",
-    "    bw = bw.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "66a7dccc",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# rolling mean and std deviation of prices\n",
-    "\n",
-    "rolling = openbb.qa.rolling_chart(\n",
-    "    symbol=ticker,\n",
-    "    data=ticker_data,\n",
-    "    target=\"Close\",\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if rolling:\n",
-    "    rolling = rolling.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d6b43dd7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# rolling kurtosis of distribution of prices\n",
-    "\n",
-    "kurtosis = openbb.qa.kurtosis_chart(\n",
-    "    symbol=ticker,\n",
-    "    data=ticker_data,\n",
-    "    target=\"Close\",\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if kurtosis:\n",
-    "    kurtosis = kurtosis.to_html()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
-   "metadata": {},
-   "source": [
-    "## Render the report template to a file"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "body = f\"\"\"\n",
-    "<style>\n",
-    "@font-face {{\n",
-    "    font-family: \"Fira Code\";\n",
-    "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
-    "    font-weight: 400 700;\n",
-    "    font-stretch: 50%;\n",
-    "}}\n",
-    "</style>\n",
-    "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
-    "\"\"\"\n",
-    "\n",
-    "\n",
-    "img = (\n",
-    "    str(REPOSITORY_DIRECTORY)\n",
-    "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
-    ")\n",
-    "floppy_disk_img = (\n",
-    "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
-    ")\n",
-    "body += widgets.header(\n",
-    "    img,\n",
-    "    floppy_disk_img,\n",
-    "    author,\n",
-    "    report_date,\n",
-    "    report_time,\n",
-    "    report_timezone,\n",
-    "    f\"<b>INVESTMENT RESEARCH REPORT:</b> {ticker}\",\n",
-    ")\n",
-    "\n",
-    "body += widgets.tablinks(\n",
-    "    [\n",
-    "        \"SUMMARY\",\n",
-    "        \"Due Diligence\",\n",
-    "        \"Technical Analysis\",\n",
-    "        \"Quantitative Analysis\",\n",
-    "    ]\n",
-    ")\n",
-    "\n",
-    "comment = \"\"\n",
-    "\n",
-    "# Summary tab\n",
-    "htmlcode = \"\"\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Basic information about loaded coin\") + basic_info.to_html()]\n",
-    ")\n",
-    "if not links.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Links\") + links.to_html(escape=False)])\n",
-    "\n",
-    "if not news.empty:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, \"Published news\") + news.to_html(escape=False)]\n",
-    "    )\n",
-    "\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Historical data\")])\n",
-    "for data in historical_data:\n",
-    "    htmlcode += widgets.row([data])\n",
-    "\n",
-    "htmlcode += widgets.row([widgets.h(3, \"1-year historical data candlestick chart\")])\n",
-    "htmlcode += widgets.row([candle_one_year])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Sentiment analysis\")])\n",
-    "htmlcode += widgets.row([headlines])\n",
-    "# TODO: print rich table\n",
-    "# htmlcode += widgets.row([widgets.h(3, \"Quick performance\")])\n",
-    "# htmlcode += widgets.row([quick_performance])\n",
-    "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
-    "\n",
-    "# # Due diligence tab\n",
-    "htmlcode = \"\"\n",
-    "if not trading_pair_info.empty:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, f\"Trading pair info {ticker}/USDT\") + trading_pair_info.to_html()]\n",
-    "    )\n",
-    "if not mcapdom_df.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Market cap dominance\")])\n",
-    "    htmlcode += widgets.row([mcapdom])\n",
-    "\n",
-    "if not roadmap_model.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Roadmap\") + roadmap_model.to_html()])\n",
-    "    htmlcode += widgets.row([roadmap_view])\n",
-    "\n",
-    "if not tokenomics_model.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Tokenomics\") + tokenomics_model.to_html()])\n",
-    "    htmlcode += widgets.row([tokenomics_view])\n",
-    "\n",
-    "if fundraise:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Fundraising Details\")])\n",
-    "    htmlcode += widgets.row([widgets.p(fundraise_info)])\n",
-    "    htmlcode += widgets.row([fundraise_df.to_html()])\n",
-    "\n",
-    "if not ath.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"All time high\")])\n",
-    "    htmlcode += widgets.row([ath.to_html()])\n",
-    "\n",
-    "if not atl.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"All time low\")])\n",
-    "    htmlcode += widgets.row([atl.to_html()])\n",
-    "\n",
-    "if not market.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"All markets\")])\n",
-    "    htmlcode += widgets.row([market.sample(n=20).sort_index().to_html(escape=False)])\n",
-    "\n",
-    "if not ex.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Exchanges where loaded coin is listed\")])\n",
-    "    htmlcode += widgets.row([ex.sample(n=20).sort_index().to_html()])\n",
-    "\n",
-    "if not trades.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Last trades\")])\n",
-    "    htmlcode += widgets.row([trades.tail(20).to_html()])\n",
-    "\n",
-    "if order_book_raw:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Order book\")])\n",
-    "    htmlcode += widgets.row([order_book])\n",
-    "\n",
-    "if not ps.empty:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, \"Price and supply related metrics for loaded coin\")]\n",
-    "    )\n",
-    "    htmlcode += widgets.row([ps.to_html()])\n",
-    "\n",
-    "if not events.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Events\")])\n",
-    "    htmlcode += widgets.row([events.to_html(escape=False)])\n",
-    "\n",
-    "# TODO: print rich table\n",
-    "# htmlcode += widgets.row([widgets.h(3, \"Tweets for loaded coin\")])\n",
-    "# htmlcode += widgets.row([tweets])\n",
-    "# htmlcode += widgets.row([widgets.h(3, \"Social media\")])\n",
-    "# htmlcode += widgets.row([social.to_html()])\n",
-    "\n",
-    "if not gh_data.empty:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Github activity over time\")])\n",
-    "    htmlcode += widgets.row([gh])\n",
-    "else:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Github activity over time\")])\n",
-    "    htmlcode += widgets.row([widgets.p(\"No data available.\")])\n",
-    "\n",
-    "body += widgets.add_tab(\"Due Diligence\", htmlcode)\n",
-    "\n",
-    "# Technical Analysis tab\n",
-    "htmlcode = \"\"\n",
-    "htmlcode = widgets.row([widgets.h(3, \"Simple moving average\")])\n",
-    "htmlcode += widgets.row([sma])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Exponential moving average\")])\n",
-    "htmlcode += widgets.row([ema])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Zero lag exponential moving average\")])\n",
-    "htmlcode += widgets.row([zlma])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Commodity channel index\")])\n",
-    "htmlcode += widgets.row([cci])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Moving average convergence/divergence\")])\n",
-    "htmlcode += widgets.row([macd])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Fisher transform\")])\n",
-    "htmlcode += widgets.row([fisher])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Aroon indicator\")])\n",
-    "htmlcode += widgets.row([aroon])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Bollinger bands\")])\n",
-    "htmlcode += widgets.row([bbands])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Fibonacci retracement\")])\n",
-    "htmlcode += widgets.row([fib])\n",
-    "body += widgets.add_tab(\"Technical Analysis\", htmlcode)\n",
-    "\n",
-    "# Quantitative Analysis tab\n",
-    "htmlcode = \"\"\n",
-    "htmlcode = widgets.row([widgets.h(3, \"Summary\") + summary.to_html()])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Normality statistics and tests\") + normality.to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Box and whisker plot\")])\n",
-    "htmlcode += widgets.row([bw])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Rolling mean and std deviation of prices\")])\n",
-    "htmlcode += widgets.row([rolling])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Rolling kurtosis of distribution of prices\")])\n",
-    "htmlcode += widgets.row([kurtosis])\n",
-    "body += widgets.add_tab(\"Quantitative Analysis\", htmlcode)\n",
-    "\n",
-    "body += widgets.tab_clickable_and_save_evt()\n",
-    "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
-    "\n",
-    "# # to save the results\n",
-    "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
-    "    fh.write(report)"
-   ]
-  }
- ],
- "metadata": {
-  "celltoolbar": "Tags",
-  "kernelspec": {
-   "display_name": "venv",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.8"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "id": "70ba2c8a",
+            "metadata": {},
+            "source": [
+                "## Notebook setup"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "driven-billion",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import os\n",
+                "import io\n",
+                "import warnings\n",
+                "import datetime\n",
+                "import numpy as np\n",
+                "import base64\n",
+                "import pandas as pd\n",
+                "from typing import List\n",
+                "\n",
+                "from IPython.display import HTML\n",
+                "\n",
+                "import openbb_terminal.config_terminal as cfg\n",
+                "from openbb_terminal.helper_classes import TerminalStyle\n",
+                "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
+                "from openbb_terminal import OpenBBFigure\n",
+                "\n",
+                "\n",
+                "warnings.filterwarnings(\"ignore\")\n",
+                "\n",
+                "pd.set_option(\"display.float_format\", lambda x: \"%.5f\" % x)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "24ed42f0",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Suppressing sdk logs\n",
+                "cfg.change_logging_suppress(new_value=True)\n",
+                "\n",
+                "# Import the OpenBB SDK\n",
+                "from openbb_terminal.sdk import openbb, widgets"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from openbb_terminal.core.session.current_user import get_current_user\n",
+                "\n",
+                "user = get_current_user()\n",
+                "\n",
+                "cfg.theme = TerminalStyle(\n",
+                "    user.preferences.MPL_STYLE,\n",
+                "    user.preferences.PMF_STYLE,\n",
+                "    user.preferences.RICH_STYLE,\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "c52f83e1",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "stylesheet = widgets.html_report_stylesheet()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "807fda4e",
+            "metadata": {},
+            "source": [
+                "## Select Ticker"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "intended-sherman",
+            "metadata": {
+                "tags": [
+                    "parameters"
+                ]
+            },
+            "outputs": [],
+            "source": [
+                "# Parameters that will be replaced when calling this notebook\n",
+                "# Do not leave parameters blank as notebook will not run otherwise\n",
+                "symbol = \"BTC\"\n",
+                "report_name = f\"Crypto Report for {symbol}\""
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "2c46efb8",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ticker = symbol"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "d4897334",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "author = \"\"\n",
+                "report_title = f\"INVESTMENT RESEARCH REPORT ON {ticker.upper()}\"\n",
+                "report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
+                "report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
+                "report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
+                "report_title, report_date, report_time, report_timezone"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "35d9a943",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# basic info\n",
+                "\n",
+                "basic_info = openbb.crypto.dd.basic(ticker)\n",
+                "if not basic_info.empty:\n",
+                "    basic_info = basic_info.set_index(\"Metric\")\n",
+                "    basic_info"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "091d305e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "news = openbb.crypto.dd.news(symbol=ticker).head(10)\n",
+                "\n",
+                "if (isinstance(news, pd.DataFrame) and not news.empty) or (\n",
+                "    not isinstance(news, pd.DataFrame) and news\n",
+                "):\n",
+                "    news = news.set_index(\"published_at\")\n",
+                "    news.sort_index()\n",
+                "    news[\"link\"] = news[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
+                "    news\n",
+                "else:\n",
+                "    news = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "bd281ab8",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "links = openbb.crypto.dd.links(ticker)\n",
+                "\n",
+                "if (isinstance(links, pd.DataFrame) and not links.empty) or (\n",
+                "    not isinstance(links, pd.DataFrame) and links\n",
+                "):\n",
+                "    links[\"Link\"] = links[\"Link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
+                "    links\n",
+                "else:\n",
+                "    links = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "07d09ce8",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "five_year = datetime.datetime.now() - datetime.timedelta(days=1825)\n",
+                "three_year = datetime.datetime.now() - datetime.timedelta(days=1095)\n",
+                "one_year = datetime.datetime.now() - datetime.timedelta(days=365)\n",
+                "three_months = datetime.datetime.now() - datetime.timedelta(days=90)\n",
+                "\n",
+                "dates = {\n",
+                "    \"three_months\": three_months,\n",
+                "    \"one_year\": one_year,\n",
+                "    \"three_year\": three_year,\n",
+                "    \"five_year\": five_year,\n",
+                "}"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e6d6d43d",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from tkinter.filedialog import Open\n",
+                "\n",
+                "\n",
+                "def get_historical_data(ticker, dict_of_dates, is_plot=True) -> List[pd.DataFrame]:\n",
+                "    list_of_historical_data = []\n",
+                "\n",
+                "    for date in dict_of_dates:\n",
+                "        data = openbb.crypto.load(\n",
+                "            symbol=ticker,\n",
+                "            to_symbol=\"usd\",\n",
+                "            start_date=dict_of_dates[date],\n",
+                "            source=\"YahooFinance\",\n",
+                "        )\n",
+                "\n",
+                "        if data.empty:\n",
+                "            continue\n",
+                "\n",
+                "        # we'll be using the adjusted close price as same as close price\n",
+                "        data[\"Adj Close\"] = data[\"Close\"]\n",
+                "\n",
+                "        if is_plot:\n",
+                "            fig = OpenBBFigure(yaxis_title=\"USDT\").set_title(\n",
+                "                f\"{date} historical data for {ticker.upper()}\"\n",
+                "            )\n",
+                "            fig.add_scatter(x=data.index, y=data[\"Adj Close\"], name=\"Close\")\n",
+                "\n",
+                "            plot_data = fig.to_html()\n",
+                "\n",
+                "            list_of_historical_data.append(plot_data)\n",
+                "        else:\n",
+                "            list_of_historical_data.append(data)\n",
+                "\n",
+                "    return list_of_historical_data"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "ed19a708",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "try:\n",
+                "    historical_data = get_historical_data(ticker, dates)\n",
+                "except Exception as e:\n",
+                "    raise KeyboardInterrupt"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "8f815dbc",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "historical_data_one_year = get_historical_data(ticker, {\"one_year\": one_year}, False)[0]\n",
+                "historical_data_one_year"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "081a4bb3",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from openbb_terminal.cryptocurrency.cryptocurrency_helpers import show_quick_performance\n",
+                "\n",
+                "show_quick_performance(\n",
+                "    crypto_df=historical_data_one_year,\n",
+                "    symbol=ticker,\n",
+                "    current_currency=\"USDT\",\n",
+                "    source=\"YahooFinance\",\n",
+                "    exchange=\"binance\",\n",
+                "    interval=\"1440\",\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "88af0fbe",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "headlines = openbb.crypto.dd.headlines_chart(ticker, external_axes=True)\n",
+                "\n",
+                "if headlines:\n",
+                "    headlines = headlines.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e4509c6e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "candle_one_year = openbb.crypto.chart(\n",
+                "    historical_data_one_year,\n",
+                "    to_symbol=ticker,\n",
+                "    from_symbol=\"USDT\",\n",
+                "    source=\"YahooFinance\",\n",
+                "    exchange=\"binance\",\n",
+                "    interval=\"1440\",\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if candle_one_year:\n",
+                "    candle_one_year = candle_one_year.to_html()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "7f83daae",
+            "metadata": {},
+            "source": [
+                "## Due Diligence"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "93d66cf1",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# market cap dominance\n",
+                "mcapdom_df = openbb.crypto.dd.mcapdom(symbol=ticker)\n",
+                "\n",
+                "if (isinstance(mcapdom_df, pd.DataFrame) and not mcapdom_df.empty) or (\n",
+                "    not isinstance(mcapdom_df, pd.DataFrame) and mcapdom_df\n",
+                "):\n",
+                "    mcapdom = openbb.crypto.dd.mcapdom_chart(symbol=ticker, external_axes=True)\n",
+                "\n",
+                "    if mcapdom:\n",
+                "        mcapdom = mcapdom.to_html()\n",
+                "else:\n",
+                "    mcapdom_df = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "284b0586",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# roadmap\n",
+                "roadmap_model = openbb.crypto.dd.rm(symbol=ticker)\n",
+                "\n",
+                "if (isinstance(roadmap_model, pd.DataFrame) and not roadmap_model.empty) or (\n",
+                "    not isinstance(roadmap_model, pd.DataFrame) and roadmap_model\n",
+                "):\n",
+                "    roadmap_model = roadmap_model.set_index(\"Date\")\n",
+                "    roadmap_model.sort_index()\n",
+                "\n",
+                "    roadmap_view = openbb.crypto.dd.rm_chart(symbol=ticker, external_axes=True)\n",
+                "    if roadmap_view:\n",
+                "        roadmap_view = roadmap_view.to_html()\n",
+                "\n",
+                "else:\n",
+                "    roadmap_model = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "9ddbc654",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "tokenomics_model = openbb.crypto.dd.rm(symbol=ticker)\n",
+                "\n",
+                "if (isinstance(tokenomics_model, pd.DataFrame) and not tokenomics_model.empty) or (\n",
+                "    not isinstance(tokenomics_model, pd.DataFrame) and tokenomics_model\n",
+                "):\n",
+                "    tokenomics_model = tokenomics_model.set_index(\"Date\")\n",
+                "    tokenomics_model.sort_index()\n",
+                "\n",
+                "    tokenomics_view = openbb.crypto.dd.tk_chart(symbol=ticker, external_axes=True)\n",
+                "    if tokenomics_view:\n",
+                "        tokenomics_view = tokenomics_view.to_html()\n",
+                "\n",
+                "else:\n",
+                "    tokenomics_model = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "7d02fcc4",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# fundraise\n",
+                "fundraise = openbb.crypto.dd.fr(symbol=ticker)  # this returns a tuple\n",
+                "\n",
+                "if fundraise:\n",
+                "    fundraise_info = fundraise[0]\n",
+                "    fundraise_df = fundraise[1]"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "5e625a2e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "trading_pair_info = openbb.crypto.dd.trading_pair_info(f\"{ticker}-USDT\")\n",
+                "if (isinstance(trading_pair_info, pd.DataFrame) and not trading_pair_info.empty) or (\n",
+                "    not isinstance(trading_pair_info, pd.DataFrame) and trading_pair_info\n",
+                "):\n",
+                "    trading_pair_info = trading_pair_info.set_index(\"Metric\")\n",
+                "    trading_pair_info\n",
+                "else:\n",
+                "    trading_pair_info = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "8f33b4d8",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import openbb_terminal.cryptocurrency.due_diligence.pycoingecko_model as gecko\n",
+                "from openbb_terminal.cryptocurrency.cryptocurrency_helpers import get_coingecko_id\n",
+                "\n",
+                "ath = pd.DataFrame()\n",
+                "try:\n",
+                "    cg_id = get_coingecko_id(symbol=ticker)\n",
+                "    coin = gecko.Coin(ticker)\n",
+                "    ath = coin.get_all_time_high(currency=cg_id)\n",
+                "\n",
+                "except Exception as e:\n",
+                "    print(\"Reached coingecko API limit\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "2a82e990",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import openbb_terminal.cryptocurrency.due_diligence.pycoingecko_model as gecko\n",
+                "from openbb_terminal.cryptocurrency.cryptocurrency_helpers import get_coingecko_id\n",
+                "\n",
+                "atl = pd.DataFrame()\n",
+                "try:\n",
+                "    cg_id = get_coingecko_id(symbol=ticker)\n",
+                "    coin = gecko.Coin(ticker)\n",
+                "    atl = coin.get_all_time_low(currency=cg_id)\n",
+                "\n",
+                "except Exception as e:\n",
+                "    print(\"Reached coingecko API limit\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e9e512e9",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# market stats about loaded coin\n",
+                "\n",
+                "market = openbb.crypto.dd.mkt(ticker)\n",
+                "\n",
+                "if (isinstance(market, pd.DataFrame) and not market.empty) or (\n",
+                "    not isinstance(market, pd.DataFrame) and market\n",
+                "):\n",
+                "    market = market.set_index(\"exchange\")\n",
+                "\n",
+                "    market[\"market_url\"] = market[\"market_url\"].apply(\n",
+                "        lambda x: f'<a href=\"{x}\">{x}</a>'\n",
+                "    )\n",
+                "    market\n",
+                "else:\n",
+                "    market = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "1d6e76cb",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# all exchanges where loaded coin is listed\n",
+                "ex = openbb.crypto.dd.ex(ticker)\n",
+                "\n",
+                "if (isinstance(ex, pd.DataFrame) and not ex.empty) or (\n",
+                "    not isinstance(ex, pd.DataFrame) and ex\n",
+                "):\n",
+                "    ex = ex.set_index(\"id\")\n",
+                "    ex\n",
+                "else:\n",
+                "    ex = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "1fcdbc67",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# last trades\n",
+                "trades = openbb.crypto.dd.trades(symbol=ticker, exchange_id=\"gemini\", to_symbol=\"USD\")\n",
+                "if (isinstance(trades, pd.DataFrame) and not trades.empty) or (\n",
+                "    not isinstance(trades, pd.DataFrame) and trades\n",
+                "):\n",
+                "    trades = trades.set_index(\"Date\")\n",
+                "    trades\n",
+                "else:\n",
+                "    trades = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "262d190a",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# order book\n",
+                "order_book_raw = openbb.crypto.dd.ob(\n",
+                "    symbol=ticker, exchange=\"gemini\", to_symbol=\"USD\"\n",
+                ")  # this returns a dict\n",
+                "\n",
+                "if order_book_raw:\n",
+                "    order_book = openbb.crypto.dd.ob_chart(\n",
+                "        symbol=ticker, exchange=\"gemini\", to_symbol=\"USD\", external_axes=True\n",
+                "    )\n",
+                "    if order_book:\n",
+                "        order_book = order_book.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "679d0d79",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# price and supply related metrics for loaded coin\n",
+                "\n",
+                "ps = openbb.crypto.dd.ps(ticker)\n",
+                "if (isinstance(ps, pd.DataFrame) and not ps.empty) or (\n",
+                "    not isinstance(ps, pd.DataFrame) and ps\n",
+                "):\n",
+                "    ps = ps.set_index(\"Metric\")\n",
+                "    ps\n",
+                "else:\n",
+                "    ps = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "92e76d79",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# events\n",
+                "\n",
+                "events = openbb.crypto.dd.events(ticker)\n",
+                "\n",
+                "if (isinstance(events, pd.DataFrame) and not events.empty) or (\n",
+                "    not isinstance(events, pd.DataFrame) and events\n",
+                "):\n",
+                "    events = events.set_index(\"date\")\n",
+                "    events[\"link\"] = events[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
+                "else:\n",
+                "    events = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "a14130db",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# social media\n",
+                "\n",
+                "from openbb_terminal.cryptocurrency.due_diligence.pycoingecko_view import display_social\n",
+                "\n",
+                "display_social(ticker)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "8f89627f",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# tweets for loaded coin\n",
+                "\n",
+                "tweets = openbb.crypto.dd.twitter(ticker)\n",
+                "tweets"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "9bb75443",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# github activity over time\n",
+                "\n",
+                "gh_data = openbb.crypto.dd.gh(symbol=ticker)\n",
+                "\n",
+                "if (isinstance(gh_data, pd.DataFrame) and not gh_data.empty) or (\n",
+                "    not isinstance(gh_data, pd.DataFrame) and gh_data\n",
+                "):\n",
+                "    gh = openbb.crypto.dd.gh_chart(symbol=ticker, external_axes=True)\n",
+                "    if gh:\n",
+                "        gh = gh.to_html()\n",
+                "else:\n",
+                "    gh_data = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "fcaa973d",
+            "metadata": {},
+            "source": [
+                "## TA\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "477317b4",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ticker_data = historical_data_one_year.copy()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "7af3695c",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# simple moving average\n",
+                "ticker_data.index.names = [\"date\"]\n",
+                "\n",
+                "sma = openbb.ta.ma_chart(\n",
+                "    data=ticker_data,\n",
+                "    ma_type=\"SMA\",\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if sma:\n",
+                "    sma = sma.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "5d5089fa",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# exponential moving average\n",
+                "ema = openbb.ta.ma_chart(\n",
+                "    data=ticker_data,\n",
+                "    ma_type=\"EMA\",\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if ema:\n",
+                "    ema = ema.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "5facfbf4",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# zero lag exponential moving average\n",
+                "\n",
+                "zlma = openbb.ta.ma_chart(\n",
+                "    data=ticker_data,\n",
+                "    ma_type=\"ZLMA\",\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if zlma:\n",
+                "    zlma = zlma.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "df54f7ad",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# commodity channel index\n",
+                "\n",
+                "cci = openbb.ta.cci_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if cci:\n",
+                "    cci = cci.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "f53469eb",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# moving average convergence/divergence\n",
+                "\n",
+                "macd = openbb.ta.macd_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if macd:\n",
+                "    macd = macd.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "dd79e6b6",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# fisher transform\n",
+                "\n",
+                "fisher = openbb.ta.fisher_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if fisher:\n",
+                "    fisher = fisher.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "b699e61f",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# aroon indicator\n",
+                "\n",
+                "aroon = openbb.ta.aroon_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if aroon:\n",
+                "    aroon = aroon.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "79401027",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# bollinger bands\n",
+                "\n",
+                "bbands = openbb.ta.bbands_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if bbands:\n",
+                "    bbands = bbands.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "0b5e2949",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# fibonacci retracement\n",
+                "\n",
+                "fib = openbb.ta.fib_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if fib:\n",
+                "    fib = fib.to_html()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "48847a7f",
+            "metadata": {},
+            "source": [
+                "## QA"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e77b373b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# summary\n",
+                "\n",
+                "summary = openbb.qa.summary(data=ticker_data)\n",
+                "summary"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "3ecfc93e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# normality statistics and tests\n",
+                "\n",
+                "# openbb.qa.normality_chart(\n",
+                "#     data=ticker_data,\n",
+                "#     target=\"Close\",\n",
+                "# )\n",
+                "\n",
+                "normality = openbb.qa.normality(\n",
+                "    data=ticker_data[\"Close\"],\n",
+                ")\n",
+                "normality"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "8abe96b0",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# box and whisker plot\n",
+                "\n",
+                "bw = openbb.qa.bw(\n",
+                "    symbol=ticker,\n",
+                "    data=ticker_data,\n",
+                "    target=\"Close\",\n",
+                "    yearly=False,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if bw:\n",
+                "    bw = bw.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "66a7dccc",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# rolling mean and std deviation of prices\n",
+                "\n",
+                "rolling = openbb.qa.rolling_chart(\n",
+                "    symbol=ticker,\n",
+                "    data=ticker_data,\n",
+                "    target=\"Close\",\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if rolling:\n",
+                "    rolling = rolling.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "d6b43dd7",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# rolling kurtosis of distribution of prices\n",
+                "\n",
+                "kurtosis = openbb.qa.kurtosis_chart(\n",
+                "    symbol=ticker,\n",
+                "    data=ticker_data,\n",
+                "    target=\"Close\",\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if kurtosis:\n",
+                "    kurtosis = kurtosis.to_html()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
+            "metadata": {},
+            "source": [
+                "## Render the report template to a file"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "body = f\"\"\"\n",
+                "<style>\n",
+                "@font-face {{\n",
+                "    font-family: \"Fira Code\";\n",
+                "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
+                "    font-weight: 400 700;\n",
+                "    font-stretch: 50%;\n",
+                "}}\n",
+                "</style>\n",
+                "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
+                "\"\"\"\n",
+                "\n",
+                "\n",
+                "img = (\n",
+                "    str(REPOSITORY_DIRECTORY)\n",
+                "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
+                ")\n",
+                "floppy_disk_img = (\n",
+                "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
+                ")\n",
+                "body += widgets.header(\n",
+                "    img,\n",
+                "    floppy_disk_img,\n",
+                "    author,\n",
+                "    report_date,\n",
+                "    report_time,\n",
+                "    report_timezone,\n",
+                "    f\"<b>INVESTMENT RESEARCH REPORT:</b> {ticker}\",\n",
+                ")\n",
+                "\n",
+                "body += widgets.tablinks(\n",
+                "    [\n",
+                "        \"SUMMARY\",\n",
+                "        \"Due Diligence\",\n",
+                "        \"Technical Analysis\",\n",
+                "        \"Quantitative Analysis\",\n",
+                "    ]\n",
+                ")\n",
+                "\n",
+                "comment = \"\"\n",
+                "\n",
+                "# Summary tab\n",
+                "htmlcode = \"\"\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Basic information about loaded coin\") + basic_info.to_html()]\n",
+                ")\n",
+                "if not links.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Links\") + links.to_html(escape=False)])\n",
+                "\n",
+                "if not news.empty:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, \"Published news\") + news.to_html(escape=False)]\n",
+                "    )\n",
+                "\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Historical data\")])\n",
+                "for data in historical_data:\n",
+                "    htmlcode += widgets.row([data])\n",
+                "\n",
+                "htmlcode += widgets.row([widgets.h(3, \"1-year historical data candlestick chart\")])\n",
+                "htmlcode += widgets.row([candle_one_year])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Sentiment analysis\")])\n",
+                "htmlcode += widgets.row([headlines])\n",
+                "# TODO: print rich table\n",
+                "# htmlcode += widgets.row([widgets.h(3, \"Quick performance\")])\n",
+                "# htmlcode += widgets.row([quick_performance])\n",
+                "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
+                "\n",
+                "# # Due diligence tab\n",
+                "htmlcode = \"\"\n",
+                "if not trading_pair_info.empty:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, f\"Trading pair info {ticker}/USDT\") + trading_pair_info.to_html()]\n",
+                "    )\n",
+                "if not mcapdom_df.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Market cap dominance\")])\n",
+                "    htmlcode += widgets.row([mcapdom])\n",
+                "\n",
+                "if not roadmap_model.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Roadmap\") + roadmap_model.to_html()])\n",
+                "    htmlcode += widgets.row([roadmap_view])\n",
+                "\n",
+                "if not tokenomics_model.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Tokenomics\") + tokenomics_model.to_html()])\n",
+                "    htmlcode += widgets.row([tokenomics_view])\n",
+                "\n",
+                "if fundraise:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Fundraising Details\")])\n",
+                "    htmlcode += widgets.row([widgets.p(fundraise_info)])\n",
+                "    htmlcode += widgets.row([fundraise_df.to_html()])\n",
+                "\n",
+                "if not ath.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"All time high\")])\n",
+                "    htmlcode += widgets.row([ath.to_html()])\n",
+                "\n",
+                "if not atl.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"All time low\")])\n",
+                "    htmlcode += widgets.row([atl.to_html()])\n",
+                "\n",
+                "if not market.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"All markets\")])\n",
+                "    htmlcode += widgets.row([market.sample(n=20).sort_index().to_html(escape=False)])\n",
+                "\n",
+                "if not ex.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Exchanges where loaded coin is listed\")])\n",
+                "    htmlcode += widgets.row([ex.sample(n=20).sort_index().to_html()])\n",
+                "\n",
+                "if not trades.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Last trades\")])\n",
+                "    htmlcode += widgets.row([trades.tail(20).to_html()])\n",
+                "\n",
+                "if order_book_raw:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Order book\")])\n",
+                "    htmlcode += widgets.row([order_book])\n",
+                "\n",
+                "if not ps.empty:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, \"Price and supply related metrics for loaded coin\")]\n",
+                "    )\n",
+                "    htmlcode += widgets.row([ps.to_html()])\n",
+                "\n",
+                "if not events.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Events\")])\n",
+                "    htmlcode += widgets.row([events.to_html(escape=False)])\n",
+                "\n",
+                "# TODO: print rich table\n",
+                "# htmlcode += widgets.row([widgets.h(3, \"Tweets for loaded coin\")])\n",
+                "# htmlcode += widgets.row([tweets])\n",
+                "# htmlcode += widgets.row([widgets.h(3, \"Social media\")])\n",
+                "# htmlcode += widgets.row([social.to_html()])\n",
+                "\n",
+                "if not gh_data.empty:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Github activity over time\")])\n",
+                "    htmlcode += widgets.row([gh])\n",
+                "else:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Github activity over time\")])\n",
+                "    htmlcode += widgets.row([widgets.p(\"No data available.\")])\n",
+                "\n",
+                "body += widgets.add_tab(\"Due Diligence\", htmlcode)\n",
+                "\n",
+                "# Technical Analysis tab\n",
+                "htmlcode = \"\"\n",
+                "htmlcode = widgets.row([widgets.h(3, \"Simple moving average\")])\n",
+                "htmlcode += widgets.row([sma])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Exponential moving average\")])\n",
+                "htmlcode += widgets.row([ema])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Zero lag exponential moving average\")])\n",
+                "htmlcode += widgets.row([zlma])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Commodity channel index\")])\n",
+                "htmlcode += widgets.row([cci])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Moving average convergence/divergence\")])\n",
+                "htmlcode += widgets.row([macd])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Fisher transform\")])\n",
+                "htmlcode += widgets.row([fisher])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Aroon indicator\")])\n",
+                "htmlcode += widgets.row([aroon])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Bollinger bands\")])\n",
+                "htmlcode += widgets.row([bbands])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Fibonacci retracement\")])\n",
+                "htmlcode += widgets.row([fib])\n",
+                "body += widgets.add_tab(\"Technical Analysis\", htmlcode)\n",
+                "\n",
+                "# Quantitative Analysis tab\n",
+                "htmlcode = \"\"\n",
+                "htmlcode = widgets.row([widgets.h(3, \"Summary\") + summary.to_html()])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Normality statistics and tests\") + normality.to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Box and whisker plot\")])\n",
+                "htmlcode += widgets.row([bw])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Rolling mean and std deviation of prices\")])\n",
+                "htmlcode += widgets.row([rolling])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Rolling kurtosis of distribution of prices\")])\n",
+                "htmlcode += widgets.row([kurtosis])\n",
+                "body += widgets.add_tab(\"Quantitative Analysis\", htmlcode)\n",
+                "\n",
+                "body += widgets.tab_clickable_and_save_evt()\n",
+                "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
+                "\n",
+                "# # to save the results\n",
+                "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
+                "    fh.write(report)"
+            ]
+        }
+    ],
+    "metadata": {
+        "celltoolbar": "Tags",
+        "kernelspec": {
+            "display_name": "venv",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.9.6"
+        },
+        "vscode": {
+            "interpreter": {
+                "hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
+            }
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 5
+}
\ No newline at end of file
diff --git a/openbb_terminal/reports/templates/economy.ipynb b/openbb_terminal/reports/templates/economy.ipynb
index 90b1b53cfd5..f0068f8dfda 100644
--- a/openbb_terminal/reports/templates/economy.ipynb
+++ b/openbb_terminal/reports/templates/economy.ipynb
@@ -1,739 +1,750 @@
 {
- "cells": [
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "70ba2c8a",
-   "metadata": {},
-   "source": [
-    "## Notebook setup\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "driven-billion",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "import io\n",
-    "import warnings\n",
-    "import datetime\n",
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "import base64\n",
-    "import pytz\n",
-    "\n",
-    "from IPython.display import HTML\n",
-    "\n",
-    "import openbb_terminal.config_terminal as cfg\n",
-    "from openbb_terminal.reports import widget_helpers as widgets\n",
-    "from openbb_terminal.sdk import openbb\n",
-    "from openbb_terminal.helper_funcs import get_user_timezone\n",
-    "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
-    "from openbb_terminal import OpenBBFigure, theme\n",
-    "from openbb_terminal.helper_classes import TerminalStyle\n",
-    "\n",
-    "\n",
-    "warnings.filterwarnings(\"ignore\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f9feebc8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from openbb_terminal.core.session.current_user import get_current_user\n",
-    "\n",
-    "user = get_current_user()\n",
-    "\n",
-    "cfg.theme = TerminalStyle(\n",
-    "    user.preferences.MPL_STYLE,\n",
-    "    user.preferences.PMF_STYLE,\n",
-    "    user.preferences.RICH_STYLE,\n",
-    ")\n",
-    "theme.apply_style(\"light\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e6e39973",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "stylesheet = widgets.html_report_stylesheet()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "daef64ec",
-   "metadata": {
-    "tags": [
-     "parameters"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "# Parameters that will be replaced when calling this notebook\n",
-    "# Do not leave parameters blank as notebook will not run otherwise\n",
-    "report_name = \"economy_report\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "author = \"OpenBB\"\n",
-    "report_title = f\"Economy report\"\n",
-    "user_time_zone = pytz.timezone(get_user_timezone())\n",
-    "report_date = pd.Timestamp.now(tz=user_time_zone).strftime(\"%d %B, %Y\")\n",
-    "report_time = pd.Timestamp.now(tz=user_time_zone).strftime(\"%H:%M\")\n",
-    "report_timezone = pd.Timestamp.now(tz=user_time_zone).tzinfo\n",
-    "report_title, report_date, report_time, report_timezone"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "9363f19a",
-   "metadata": {},
-   "source": [
-    "## Data\n"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "0b9ec3f9",
-   "metadata": {},
-   "source": [
-    "Summary\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e3b15d6f-dc9e-4f97-aa07-37d949a4e4bb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "overview = openbb.economy.overview()\n",
-    "overview.set_index(list(overview.columns[0]), inplace=True)\n",
-    "overview = OpenBBFigure.to_table(overview, print_index=True, width=600)\n",
-    "\n",
-    "futures = openbb.economy.futures()\n",
-    "futures.set_index(list(futures.columns[0]), inplace=True)\n",
-    "futures[\"%Chg\"] = futures[\"%Chg\"].apply(lambda x: float(f\"{x:.2f}\"))\n",
-    "futures_fig = OpenBBFigure.to_table(futures, print_index=True)\n",
-    "\n",
-    "news = openbb.news(\"economy\")\n",
-    "news.columns = news.columns.str.title()\n",
-    "news[\"Title\"] = news.apply(lambda x: f'<a href=\"{x[\"Link\"]}\">{x[\"Title\"]}</a>', axis=1)\n",
-    "news = news[[\"Title\", \"Published\"]]\n",
-    "news[\"Published\"] = pd.to_datetime(news[\"Published\"]).dt.strftime(\"%Y-%m-%d %H:%M\")\n",
-    "news.set_index(\"Published\", inplace=True)\n",
-    "\n",
-    "news = OpenBBFigure.to_table(news, print_index=True, columnwidth=[1.3, 7], width=1100)\n",
-    "news.update_layout(clickmode=\"event+select\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "64729474",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "rtps_data = openbb.economy.rtps()\n",
-    "subplots = OpenBBFigure.create_subplots(1, 2, horizontal_spacing=0.15)\n",
-    "openbb.economy.rtps_chart(external_axes=True).to_subplot(subplots, 1, 1)\n",
-    "\n",
-    "chg = futures[\"%Chg\"]\n",
-    "colors = [theme.up_color if x > 0 else theme.down_color for x in list(chg.values)]\n",
-    "subplots.add_bar(\n",
-    "    y=chg.index,\n",
-    "    x=chg.values,\n",
-    "    orientation=\"h\",\n",
-    "    marker_color=colors,\n",
-    "    showlegend=False,\n",
-    "    row=1,\n",
-    "    col=2,\n",
-    ")\n",
-    "subplots.update_xaxes(title_text=\"Performance (%)\", row=1, col=1)\n",
-    "subplots.update_xaxes(title_text=\"Change %\", row=1, col=2)\n",
-    "subplots.update_layout(margin=dict(l=0, r=0, t=0, b=0), yaxis=dict(side=\"left\"))\n",
-    "chart_0 = subplots.to_html()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "7315ac99",
-   "metadata": {},
-   "source": [
-    "Events\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a02c6166",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "events_1 = openbb.economy.events(\n",
-    "    countries=\"United States\",\n",
-    "    start_date=datetime.datetime.now().strftime(\"%Y-%m-%d\"),\n",
-    ")\n",
-    "if not events_1.empty:\n",
-    "    events_1 = OpenBBFigure.to_table(\n",
-    "        events_1.set_index(\"Date\"), print_index=True, height=200\n",
-    "    )\n",
-    "\n",
-    "events_2 = openbb.economy.events(\n",
-    "    countries=[\n",
-    "        \"Germany\",\n",
-    "        \"Spain\",\n",
-    "        \"Italy\",\n",
-    "        \"United Kingdom\",\n",
-    "        \"France\",\n",
-    "        \"Portugal\",\n",
-    "        \"Greece\",\n",
-    "    ],\n",
-    "    start_date=datetime.datetime.now().strftime(\"%Y-%m-%d\"),\n",
-    ")\n",
-    "if not events_2.empty:\n",
-    "    events_2 = OpenBBFigure.to_table(events_2.set_index(\"Date\"), print_index=True)\n",
-    "\n",
-    "events_3 = openbb.economy.events(\n",
-    "    countries=\"China\",\n",
-    "    start_date=datetime.datetime.now().strftime(\"%Y-%m-%d\"),\n",
-    ")\n",
-    "if not events_3.empty:\n",
-    "    events_3 = OpenBBFigure.to_table(events_3.set_index(\"Date\"), print_index=True)"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "f1863bd0",
-   "metadata": {},
-   "source": [
-    "Yields\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8e332ca6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ycrv = openbb.fixedincome.ycrv(return_date=True)\n",
-    "\n",
-    "if (isinstance(ycrv, pd.DataFrame) and not ycrv.empty) or (\n",
-    "    not isinstance(ycrv, pd.DataFrame) and ycrv\n",
-    "):\n",
-    "    ycrv_data_1, _ = ycrv\n",
-    "    ycrv_country_1 = \"United states\"\n",
-    "\n",
-    "    ycrv_chart_1 = openbb.fixedincome.ycrv_chart(external_axes=True)\n",
-    "\n",
-    "    if ycrv_chart_1:\n",
-    "        ycrv_chart_1 = ycrv_chart_1.to_html()\n",
-    "\n",
-    "    if not ycrv_data_1.empty:\n",
-    "        ycrv_data_1.drop([\"Maturity\"], axis=1, inplace=True)\n",
-    "        ycrv_data_1.index = [\n",
-    "            \"1M\",\n",
-    "            \"3M\",\n",
-    "            \"6M\",\n",
-    "            \"1Y\",\n",
-    "            \"2Y\",\n",
-    "            \"3Y\",\n",
-    "            \"5Y\",\n",
-    "            \"7Y\",\n",
-    "            \"10Y\",\n",
-    "            \"20Y\",\n",
-    "            \"30Y\",\n",
-    "        ]\n",
-    "else:\n",
-    "    ycrv = None"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "31fb0f86",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "openbb.economy.treasury_maturities()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c4f987af",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "subplots = OpenBBFigure.create_subplots(\n",
-    "    2,\n",
-    "    2,\n",
-    "    vertical_spacing=0.15,\n",
-    "    subplot_titles=(\"UST 2y-10y\", \"UST 10y-30y\", \"Nominal vs TIPS\"),\n",
-    "    specs=[[{}, {}], [{\"colspan\": 2}, None]],\n",
-    ")\n",
-    "openbb.economy.treasury_chart(\n",
-    "    instruments=[\"nominal\"],\n",
-    "    maturities=[\"2y\", \"10y\"],\n",
-    "    frequency=\"daily\",\n",
-    "    start_date=\"2020-01-01\",\n",
-    "    external_axes=True,\n",
-    ").to_subplot(subplots, 1, 1)\n",
-    "\n",
-    "openbb.economy.treasury_chart(\n",
-    "    instruments=[\"nominal\"],\n",
-    "    maturities=[\"10y\", \"30y\"],\n",
-    "    frequency=\"daily\",\n",
-    "    start_date=\"2020-01-01\",\n",
-    "    external_axes=True,\n",
-    ").to_subplot(subplots, 1, 2)\n",
-    "\n",
-    "openbb.economy.treasury_chart(\n",
-    "    instruments=[\"nominal\", \"inflation\"],\n",
-    "    maturities=[\"10y\"],\n",
-    "    frequency=\"daily\",\n",
-    "    start_date=\"2020-01-01\",\n",
-    "    external_axes=True,\n",
-    ").to_subplot(subplots, 2, 1)\n",
-    "\n",
-    "ust = subplots.to_html()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "7a3c421f",
-   "metadata": {},
-   "source": [
-    "Equity Market\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "12c98e06",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "valuation = OpenBBFigure.to_table(openbb.economy.valuation(), print_index=False)\n",
-    "performance = OpenBBFigure.to_table(openbb.economy.performance(), print_index=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "42f5570d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fig = OpenBBFigure(yaxis_title=\"Cumulative returns (%)\")\n",
-    "data = openbb.economy.index(\n",
-    "    indices=[\"sp500\", \"dow_djus\", \"nasdaq100\", \"russell3000\", \"cboe_vix\"],\n",
-    "    start_date=\"2000-03-09\",\n",
-    ")\n",
-    "\n",
-    "data = data.pct_change().dropna()\n",
-    "data = (1 + data.shift(periods=1, fill_value=0)).cumprod() - 1\n",
-    "for col in data.columns:\n",
-    "    fig.add_scatter(\n",
-    "        x=data.index,\n",
-    "        y=data[col] * 100,\n",
-    "        name=col,\n",
-    "    )\n",
-    "\n",
-    "eqty_0 = fig.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "286a82d7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fig = OpenBBFigure(yaxis_title=\"Cumulative returns (%)\")\n",
-    "data = openbb.economy.index(\n",
-    "    indices=[\"ftse100\", \"de_dax40\", \"fr_cac40\", \"it_mib40\", \"es_ibex35\"],\n",
-    "    start_date=\"2000-01-01\",\n",
-    ")\n",
-    "\n",
-    "data = data.pct_change().dropna()\n",
-    "data = (1 + data.shift(periods=1, fill_value=0)).cumprod() - 1\n",
-    "for col in data.columns:\n",
-    "    fig.add_scatter(\n",
-    "        x=data.index,\n",
-    "        y=data[col] * 100,\n",
-    "        name=col,\n",
-    "    )\n",
-    "\n",
-    "eqty_1 = fig.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e825e8ed",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fig = OpenBBFigure(yaxis_title=\"Cumulative returns (%)\")\n",
-    "data = openbb.economy.index(\n",
-    "    indices=[\"jp_n225\", \"cn_csi300\", \"hk_china\", \"au_asx50\"], start_date=\"2014-01-01\"\n",
-    ")\n",
-    "\n",
-    "data = data.pct_change().dropna()\n",
-    "data = (1 + data.shift(periods=1, fill_value=0)).cumprod() - 1\n",
-    "for col in data.columns:\n",
-    "    fig.add_scatter(\n",
-    "        x=data.index,\n",
-    "        y=data[col] * 100,\n",
-    "        name=col,\n",
-    "    )\n",
-    "\n",
-    "eqty_2 = fig.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8eb1327b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fig = OpenBBFigure(yaxis_title=\"Cumulative returns (%)\")\n",
-    "data = openbb.economy.index(\n",
-    "    indices=[\"in_nse50\", \"br_bvsp\", \"za_jo\", \"mx_ipc\", \"ru_moex\"],\n",
-    "    start_date=\"2013-01-01\",\n",
-    ")\n",
-    "\n",
-    "data = data.pct_change().dropna()\n",
-    "data = (1 + data.shift(periods=1, fill_value=0)).cumprod() - 1\n",
-    "for col in data.columns:\n",
-    "    fig.add_scatter(\n",
-    "        x=data.index,\n",
-    "        y=data[col] * 100,\n",
-    "        name=col,\n",
-    "    )\n",
-    "\n",
-    "eqty_3 = fig.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "02630bd6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fig = OpenBBFigure(yaxis_title=\"Cumulative returns (%)\")\n",
-    "data = openbb.economy.index(indices=[\"arca_xoi\", \"arca_pse\"], start_date=\"2000-01-01\")\n",
-    "\n",
-    "data = data.pct_change().dropna()\n",
-    "data = (1 + data.shift(periods=1, fill_value=0)).cumprod() - 1\n",
-    "for col in data.columns:\n",
-    "    fig.add_scatter(\n",
-    "        x=data.index,\n",
-    "        y=data[col] * 100,\n",
-    "        name=col,\n",
-    "    )\n",
-    "\n",
-    "eqty_4 = fig.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5a4c8963",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bigmac_res = openbb.economy.bigmac()\n",
-    "\n",
-    "if (isinstance(bigmac_res, pd.DataFrame) and not bigmac_res.empty) or (\n",
-    "    not isinstance(bigmac_res, pd.DataFrame) and bigmac_res\n",
-    "):\n",
-    "    bigmac = openbb.economy.bigmac_chart(\n",
-    "        country_codes=[\n",
-    "            \"USA\",\n",
-    "            \"CAN\",\n",
-    "            \"ARG\",\n",
-    "            \"PRT\",\n",
-    "            \"NLD\",\n",
-    "            \"FRA\",\n",
-    "            \"UAE\",\n",
-    "            \"LKA\",\n",
-    "            \"VNM\",\n",
-    "            \"RUS\",\n",
-    "            \"SWE\",\n",
-    "            \"GBR\",\n",
-    "        ],\n",
-    "        external_axes=True,\n",
-    "    )\n",
-    "    if bigmac:\n",
-    "        bigmac.set_title(\"\")\n",
-    "        bigmac = bigmac.to_html()\n",
-    "\n",
-    "else:\n",
-    "    bigmac_res = pd.DataFrame()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1947a06c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "subplots = OpenBBFigure.create_subplots(1, 1, specs=[[{\"secondary_y\": True}]])\n",
-    "\n",
-    "openbb.economy.macro_chart(\n",
-    "    parameters=[\"CONF\", \"IP\"], start_date=\"2010-01-01\", external_axes=True\n",
-    ").to_subplot(subplots, 1, 1, secondary_y=False)\n",
-    "subplots.update_yaxes(title_text=\"Confidence and IP\", secondary_y=False)\n",
-    "\n",
-    "\n",
-    "df, df_dict, _ = openbb.economy.macro(parameters=[\"CPI\"], start_date=\"2010-01-01\")\n",
-    "cpi_chg = df.pct_change(1) * 100\n",
-    "subplots.add_scatter(\n",
-    "    x=cpi_chg.index,\n",
-    "    y=cpi_chg.T.values[0],\n",
-    "    name=\"CPI (% change)\",\n",
-    "    mode=\"lines\",\n",
-    "    line=dict(color=\"red\", dash=\"dash\"),\n",
-    "    secondary_y=True,\n",
-    "    yaxis=\"y2\",\n",
-    ")\n",
-    "subplots.update_yaxes(\n",
-    "    title_text=\"CPI (% change)\",\n",
-    "    secondary_y=True,\n",
-    "    range=[-2, 2],\n",
-    "    side=\"left\",\n",
-    "    overlaying=\"y\",\n",
-    ")\n",
-    "subplots.horizontal_legend()\n",
-    "\n",
-    "macro_0 = subplots.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "971e4c51",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fred = openbb.economy.fred(series_ids=[\"T10Y3M\"], start_date=\"1980-01-01\")\n",
-    "\n",
-    "if (isinstance(fred, pd.DataFrame) and not fred.empty) or (\n",
-    "    not isinstance(fred, pd.DataFrame) and fred\n",
-    "):\n",
-    "    df, df_dict = fred\n",
-    "\n",
-    "    fig = OpenBBFigure.create_subplots(1, 1, specs=[[{\"secondary_y\": True}]])\n",
-    "    fig.add_scatter(\n",
-    "        x=df.index,\n",
-    "        y=df[\"T10Y3M\"],\n",
-    "        name=df_dict[\"T10Y3M\"][\"title\"],\n",
-    "        line=dict(color=\"red\", dash=\"dash\"),\n",
-    "        secondary_y=False,\n",
-    "    )\n",
-    "    openbb.economy.fred_chart(\n",
-    "        series_ids=[\"A191RP1A027NBEA\"],\n",
-    "        start_date=\"1980-01-01\",\n",
-    "        external_axes=True,\n",
-    "    ).to_subplot(fig, 1, 1, secondary_y=True)\n",
-    "    fig.update_yaxes(secondary_y=True, side=\"left\", overlaying=\"y\")\n",
-    "    fig.set_title(\"\")\n",
-    "    fig.horizontal_legend()\n",
-    "\n",
-    "    fred_0 = fig.to_html()\n",
-    "else:\n",
-    "    fred = None"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
-   "metadata": {},
-   "source": [
-    "## Render the report template to a file\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "body = f\"\"\"\n",
-    "<style>\n",
-    "@font-face {{\n",
-    "    font-family: \"Fira Code\";\n",
-    "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
-    "    font-weight: 400 700;\n",
-    "    font-stretch: 50%;\n",
-    "}}\n",
-    "</style>\n",
-    "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
-    "\"\"\"\n",
-    "\n",
-    "\n",
-    "img = (\n",
-    "    str(REPOSITORY_DIRECTORY)\n",
-    "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
-    ")\n",
-    "floppy_disk_img = (\n",
-    "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
-    ")\n",
-    "body += widgets.header(\n",
-    "    img,\n",
-    "    floppy_disk_img,\n",
-    "    author,\n",
-    "    report_date,\n",
-    "    report_time,\n",
-    "    report_timezone,\n",
-    "    f\"<b>ECONOMY REPORT: Leverage multiple sources to create custom reports.</b>\",\n",
-    ")\n",
-    "\n",
-    "body += widgets.tablinks(\n",
-    "    [\n",
-    "        \"SUMMARY\",\n",
-    "        \"Events\",\n",
-    "        \"Yields\",\n",
-    "        \"Equity Market\",\n",
-    "        \"Macro Data\",\n",
-    "    ]\n",
-    ")\n",
-    "\n",
-    "# Summary\n",
-    "htmlcode = widgets.row(\n",
-    "    [widgets.h(3, \"Global markets (source: WSJ)\") + overview.to_html()]\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Commodities (source: WSJ)\") + futures_fig.to_html()]\n",
-    "    + [\n",
-    "        widgets.h(3, \"Real-time sector performance (source: Alphavantage)\")\n",
-    "        + rtps_data.to_html().replace(\"table\", 'table style=\"display:inline\"')\n",
-    "    ]\n",
-    ")\n",
-    "htmlcode += widgets.row([chart_0])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Top news on 'economy' keyword (source: Newsapi)\") + news.to_html()]\n",
-    ")\n",
-    "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
-    "\n",
-    "# Events\n",
-    "htmlcode = widgets.row([widgets.h(3, \"Economic calendars (source: investing.com)\")])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"United States\") + events_1.to_html()])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Select European Countries\") + events_2.to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"China\") + events_3.to_html()])\n",
-    "body += widgets.add_tab(\"Events\", htmlcode)\n",
-    "\n",
-    "# Yields\n",
-    "htmlcode = widgets.row([widgets.h(3, \"US treasuries (source: EconDB)\") + ust])\n",
-    "\n",
-    "if ycrv:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [\n",
-    "            widgets.h(3, f\"{ycrv_country_1} yield curve (source: FRED)\")\n",
-    "            + (ycrv_chart_1 or \"\")\n",
-    "        ]\n",
-    "    )\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"\") + ycrv_data_1.to_html()])\n",
-    "\n",
-    "body += widgets.add_tab(\"Yields\", htmlcode)\n",
-    "\n",
-    "# Equity market\n",
-    "htmlcode = widgets.row(\n",
-    "    [widgets.h(3, \"Valuation (source: Finviz)\") + valuation.to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Performance (source: Finviz)\") + valuation.to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"US markets (source: YahooFinance)\") + eqty_0])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"European markets (source: YahooFinance)\") + eqty_1]\n",
-    ")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"APAC markets (source: YahooFinance)\") + eqty_2])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Emerging markets (source: YahooFinance)\") + eqty_3]\n",
-    ")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"ARCA (source: YahooFinance)\") + eqty_4])\n",
-    "body += widgets.add_tab(\"Equity Market\", htmlcode)\n",
-    "\n",
-    "# Macro\n",
-    "htmlcode = \"\"\n",
-    "if not bigmac_res.empty:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, \"Bigmac index (source: Nasdaq)\") + (bigmac or \"\")]\n",
-    "    )\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Leading indicators (source: EconDB)\") + macro_0])\n",
-    "if fred:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, \"Recession indicator (source: FRED)\") + fred_0]\n",
-    "    )\n",
-    "body += widgets.add_tab(\"Macro Data\", htmlcode)\n",
-    "\n",
-    "body += widgets.tab_clickable_and_save_evt()\n",
-    "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
-    "\n",
-    "# to save the results\n",
-    "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
-    "    fh.write(report)"
-   ]
-  }
- ],
- "metadata": {
-  "celltoolbar": "Tags",
-  "kernelspec": {
-   "display_name": "venv",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.8"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+    "cells": [
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "id": "70ba2c8a",
+            "metadata": {},
+            "source": [
+                "## Notebook setup\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "driven-billion",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import os\n",
+                "import io\n",
+                "import warnings\n",
+                "import datetime\n",
+                "import numpy as np\n",
+                "import pandas as pd\n",
+                "import base64\n",
+                "import pytz\n",
+                "\n",
+                "from IPython.display import HTML\n",
+                "\n",
+                "import openbb_terminal.config_terminal as cfg\n",
+                "from openbb_terminal.helper_funcs import get_user_timezone\n",
+                "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
+                "from openbb_terminal import OpenBBFigure, theme\n",
+                "from openbb_terminal.helper_classes import TerminalStyle\n",
+                "\n",
+                "\n",
+                "warnings.filterwarnings(\"ignore\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "4494cd3e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Suppressing sdk logs\n",
+                "cfg.change_logging_suppress(new_value=True)\n",
+                "\n",
+                "# Import the OpenBB SDK\n",
+                "from openbb_terminal.sdk import openbb, widgets"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "f9feebc8",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from openbb_terminal.core.session.current_user import get_current_user\n",
+                "\n",
+                "user = get_current_user()\n",
+                "\n",
+                "cfg.theme = TerminalStyle(\n",
+                "    user.preferences.MPL_STYLE,\n",
+                "    user.preferences.PMF_STYLE,\n",
+                "    user.preferences.RICH_STYLE,\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e6e39973",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "stylesheet = widgets.html_report_stylesheet()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "daef64ec",
+            "metadata": {
+                "tags": [
+                    "parameters"
+                ]
+            },
+            "outputs": [],
+            "source": [
+                "# Parameters that will be replaced when calling this notebook\n",
+                "# Do not leave parameters blank as notebook will not run otherwise\n",
+                "report_name = \"economy_report\""
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "author = \"OpenBB\"\n",
+                "report_title = f\"Economy report\"\n",
+                "user_time_zone = pytz.timezone(get_user_timezone())\n",
+                "report_date = pd.Timestamp.now(tz=user_time_zone).strftime(\"%d %B, %Y\")\n",
+                "report_time = pd.Timestamp.now(tz=user_time_zone).strftime(\"%H:%M\")\n",
+                "report_timezone = pd.Timestamp.now(tz=user_time_zone).tzinfo\n",
+                "report_title, report_date, report_time, report_timezone"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "id": "9363f19a",
+            "metadata": {},
+            "source": [
+                "## Data\n"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "id": "0b9ec3f9",
+            "metadata": {},
+            "source": [
+                "Summary\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e3b15d6f-dc9e-4f97-aa07-37d949a4e4bb",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "overview = openbb.economy.overview()\n",
+                "overview.set_index(list(overview.columns[0]), inplace=True)\n",
+                "overview = OpenBBFigure.to_table(overview, print_index=True, width=600)\n",
+                "\n",
+                "futures = openbb.economy.futures()\n",
+                "futures.set_index(list(futures.columns[0]), inplace=True)\n",
+                "futures[\"%Chg\"] = futures[\"%Chg\"].apply(lambda x: float(f\"{x:.2f}\"))\n",
+                "futures_fig = OpenBBFigure.to_table(futures, print_index=True)\n",
+                "\n",
+                "news = openbb.news(\"economy\")\n",
+                "news.columns = news.columns.str.title()\n",
+                "news[\"Title\"] = news.apply(lambda x: f'<a href=\"{x[\"Link\"]}\">{x[\"Title\"]}</a>', axis=1)\n",
+                "news = news[[\"Title\", \"Published\"]]\n",
+                "news[\"Published\"] = pd.to_datetime(news[\"Published\"]).dt.strftime(\"%Y-%m-%d %H:%M\")\n",
+                "news.set_index(\"Published\", inplace=True)\n",
+                "\n",
+                "news = OpenBBFigure.to_table(news, print_index=True, columnwidth=[1.3, 7], width=1100)\n",
+                "news.update_layout(clickmode=\"event+select\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "64729474",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "rtps_data = openbb.economy.rtps()\n",
+                "subplots = OpenBBFigure.create_subplots(1, 2, horizontal_spacing=0.15)\n",
+                "openbb.economy.rtps_chart(external_axes=True).to_subplot(subplots, 1, 1)\n",
+                "\n",
+                "chg = futures[\"%Chg\"]\n",
+                "colors = [theme.up_color if x > 0 else theme.down_color for x in list(chg.values)]\n",
+                "subplots.add_bar(\n",
+                "    y=chg.index,\n",
+                "    x=chg.values,\n",
+                "    orientation=\"h\",\n",
+                "    marker_color=colors,\n",
+                "    showlegend=False,\n",
+                "    row=1,\n",
+                "    col=2,\n",
+                ")\n",
+                "subplots.update_xaxes(title_text=\"Performance (%)\", row=1, col=1)\n",
+                "subplots.update_xaxes(title_text=\"Change %\", row=1, col=2)\n",
+                "subplots.update_layout(margin=dict(l=0, r=0, t=0, b=0), yaxis=dict(side=\"left\"))\n",
+                "chart_0 = subplots.to_html()"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "id": "7315ac99",
+            "metadata": {},
+            "source": [
+                "Events\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "a02c6166",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "events_1 = openbb.economy.events(\n",
+                "    countries=\"United States\",\n",
+                "    start_date=datetime.datetime.now().strftime(\"%Y-%m-%d\"),\n",
+                ")\n",
+                "if not events_1.empty:\n",
+                "    events_1 = OpenBBFigure.to_table(\n",
+                "        events_1.set_index(\"Date\"), print_index=True, height=200\n",
+                "    )\n",
+                "\n",
+                "events_2 = openbb.economy.events(\n",
+                "    countries=[\n",
+                "        \"Germany\",\n",
+                "        \"Spain\",\n",
+                "        \"Italy\",\n",
+                "        \"United Kingdom\",\n",
+                "        \"France\",\n",
+                "        \"Portugal\",\n",
+                "        \"Greece\",\n",
+                "    ],\n",
+                "    start_date=datetime.datetime.now().strftime(\"%Y-%m-%d\"),\n",
+                ")\n",
+                "if not events_2.empty:\n",
+                "    events_2 = OpenBBFigure.to_table(events_2.set_index(\"Date\"), print_index=True)\n",
+                "\n",
+                "events_3 = openbb.economy.events(\n",
+                "    countries=\"China\",\n",
+                "    start_date=datetime.datetime.now().strftime(\"%Y-%m-%d\"),\n",
+                ")\n",
+                "if not events_3.empty:\n",
+                "    events_3 = OpenBBFigure.to_table(events_3.set_index(\"Date\"), print_index=True)"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "id": "f1863bd0",
+            "metadata": {},
+            "source": [
+                "Yields\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "8e332ca6",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ycrv = openbb.fixedincome.ycrv(return_date=True)\n",
+                "\n",
+                "if (isinstance(ycrv, pd.DataFrame) and not ycrv.empty) or (\n",
+                "    not isinstance(ycrv, pd.DataFrame) and ycrv\n",
+                "):\n",
+                "    ycrv_data_1, _ = ycrv\n",
+                "    ycrv_country_1 = \"United states\"\n",
+                "\n",
+                "    ycrv_chart_1 = openbb.fixedincome.ycrv_chart(external_axes=True)\n",
+                "\n",
+                "    if ycrv_chart_1:\n",
+                "        ycrv_chart_1 = ycrv_chart_1.to_html()\n",
+                "\n",
+                "    if not ycrv_data_1.empty:\n",
+                "        ycrv_data_1.drop([\"Maturity\"], axis=1, inplace=True)\n",
+                "        ycrv_data_1.index = [\n",
+                "            \"1M\",\n",
+                "            \"3M\",\n",
+                "            \"6M\",\n",
+                "            \"1Y\",\n",
+                "            \"2Y\",\n",
+                "            \"3Y\",\n",
+                "            \"5Y\",\n",
+                "            \"7Y\",\n",
+                "            \"10Y\",\n",
+                "            \"20Y\",\n",
+                "            \"30Y\",\n",
+                "        ]\n",
+                "else:\n",
+                "    ycrv = None"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "31fb0f86",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "openbb.economy.treasury_maturities()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "c4f987af",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "subplots = OpenBBFigure.create_subplots(\n",
+                "    2,\n",
+                "    2,\n",
+                "    vertical_spacing=0.15,\n",
+                "    subplot_titles=(\"UST 2y-10y\", \"UST 10y-30y\", \"Nominal vs TIPS\"),\n",
+                "    specs=[[{}, {}], [{\"colspan\": 2}, None]],\n",
+                ")\n",
+                "openbb.economy.treasury_chart(\n",
+                "    instruments=[\"nominal\"],\n",
+                "    maturities=[\"2y\", \"10y\"],\n",
+                "    frequency=\"daily\",\n",
+                "    start_date=\"2020-01-01\",\n",
+                "    external_axes=True,\n",
+                ").to_subplot(subplots, 1, 1)\n",
+                "\n",
+                "openbb.economy.treasury_chart(\n",
+                "    instruments=[\"nominal\"],\n",
+                "    maturities=[\"10y\", \"30y\"],\n",
+                "    frequency=\"daily\",\n",
+                "    start_date=\"2020-01-01\",\n",
+                "    external_axes=True,\n",
+                ").to_subplot(subplots, 1, 2)\n",
+                "\n",
+                "openbb.economy.treasury_chart(\n",
+                "    instruments=[\"nominal\", \"inflation\"],\n",
+                "    maturities=[\"10y\"],\n",
+                "    frequency=\"daily\",\n",
+                "    start_date=\"2020-01-01\",\n",
+                "    external_axes=True,\n",
+                ").to_subplot(subplots, 2, 1)\n",
+                "\n",
+                "ust = subplots.to_html()"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "id": "7a3c421f",
+            "metadata": {},
+            "source": [
+                "Equity Market\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "12c98e06",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "valuation = OpenBBFigure.to_table(openbb.economy.valuation(), print_index=False)\n",
+                "performance = OpenBBFigure.to_table(openbb.economy.performance(), print_index=False)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "42f5570d",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "fig = OpenBBFigure(yaxis_title=\"Cumulative returns (%)\")\n",
+                "data = openbb.economy.index(\n",
+                "    indices=[\"sp500\", \"dow_djus\", \"nasdaq100\", \"russell3000\", \"cboe_vix\"],\n",
+                "    start_date=\"2000-03-09\",\n",
+                ")\n",
+                "\n",
+                "data = data.pct_change().dropna()\n",
+                "data = (1 + data.shift(periods=1, fill_value=0)).cumprod() - 1\n",
+                "for col in data.columns:\n",
+                "    fig.add_scatter(\n",
+                "        x=data.index,\n",
+                "        y=data[col] * 100,\n",
+                "        name=col,\n",
+                "    )\n",
+                "\n",
+                "eqty_0 = fig.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "286a82d7",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "fig = OpenBBFigure(yaxis_title=\"Cumulative returns (%)\")\n",
+                "data = openbb.economy.index(\n",
+                "    indices=[\"ftse100\", \"de_dax40\", \"fr_cac40\", \"it_mib40\", \"es_ibex35\"],\n",
+                "    start_date=\"2000-01-01\",\n",
+                ")\n",
+                "\n",
+                "data = data.pct_change().dropna()\n",
+                "data = (1 + data.shift(periods=1, fill_value=0)).cumprod() - 1\n",
+                "for col in data.columns:\n",
+                "    fig.add_scatter(\n",
+                "        x=data.index,\n",
+                "        y=data[col] * 100,\n",
+                "        name=col,\n",
+                "    )\n",
+                "\n",
+                "eqty_1 = fig.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e825e8ed",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "fig = OpenBBFigure(yaxis_title=\"Cumulative returns (%)\")\n",
+                "data = openbb.economy.index(\n",
+                "    indices=[\"jp_n225\", \"cn_csi300\", \"hk_china\", \"au_asx50\"], start_date=\"2014-01-01\"\n",
+                ")\n",
+                "\n",
+                "data = data.pct_change().dropna()\n",
+                "data = (1 + data.shift(periods=1, fill_value=0)).cumprod() - 1\n",
+                "for col in data.columns:\n",
+                "    fig.add_scatter(\n",
+                "        x=data.index,\n",
+                "        y=data[col] * 100,\n",
+                "        name=col,\n",
+                "    )\n",
+                "\n",
+                "eqty_2 = fig.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "8eb1327b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "fig = OpenBBFigure(yaxis_title=\"Cumulative returns (%)\")\n",
+                "data = openbb.economy.index(\n",
+                "    indices=[\"in_nse50\", \"br_bvsp\", \"za_jo\", \"mx_ipc\", \"ru_moex\"],\n",
+                "    start_date=\"2013-01-01\",\n",
+                ")\n",
+                "\n",
+                "data = data.pct_change().dropna()\n",
+                "data = (1 + data.shift(periods=1, fill_value=0)).cumprod() - 1\n",
+                "for col in data.columns:\n",
+                "    fig.add_scatter(\n",
+                "        x=data.index,\n",
+                "        y=data[col] * 100,\n",
+                "        name=col,\n",
+                "    )\n",
+                "\n",
+                "eqty_3 = fig.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "02630bd6",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "fig = OpenBBFigure(yaxis_title=\"Cumulative returns (%)\")\n",
+                "data = openbb.economy.index(indices=[\"arca_xoi\", \"arca_pse\"], start_date=\"2000-01-01\")\n",
+                "\n",
+                "data = data.pct_change().dropna()\n",
+                "data = (1 + data.shift(periods=1, fill_value=0)).cumprod() - 1\n",
+                "for col in data.columns:\n",
+                "    fig.add_scatter(\n",
+                "        x=data.index,\n",
+                "        y=data[col] * 100,\n",
+                "        name=col,\n",
+                "    )\n",
+                "\n",
+                "eqty_4 = fig.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "5a4c8963",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "bigmac_res = openbb.economy.bigmac()\n",
+                "\n",
+                "if (isinstance(bigmac_res, pd.DataFrame) and not bigmac_res.empty) or (\n",
+                "    not isinstance(bigmac_res, pd.DataFrame) and bigmac_res\n",
+                "):\n",
+                "    bigmac = openbb.economy.bigmac_chart(\n",
+                "        country_codes=[\n",
+                "            \"USA\",\n",
+                "            \"CAN\",\n",
+                "            \"ARG\",\n",
+                "            \"PRT\",\n",
+                "            \"NLD\",\n",
+                "            \"FRA\",\n",
+                "            \"UAE\",\n",
+                "            \"LKA\",\n",
+                "            \"VNM\",\n",
+                "            \"RUS\",\n",
+                "            \"SWE\",\n",
+                "            \"GBR\",\n",
+                "        ],\n",
+                "        external_axes=True,\n",
+                "    )\n",
+                "    if bigmac:\n",
+                "        bigmac.set_title(\"\")\n",
+                "        bigmac = bigmac.to_html()\n",
+                "\n",
+                "else:\n",
+                "    bigmac_res = pd.DataFrame()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "1947a06c",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "subplots = OpenBBFigure.create_subplots(1, 1, specs=[[{\"secondary_y\": True}]])\n",
+                "\n",
+                "openbb.economy.macro_chart(\n",
+                "    parameters=[\"CONF\", \"IP\"], start_date=\"2010-01-01\", external_axes=True\n",
+                ").to_subplot(subplots, 1, 1, secondary_y=False)\n",
+                "subplots.update_yaxes(title_text=\"Confidence and IP\", secondary_y=False)\n",
+                "\n",
+                "\n",
+                "df, df_dict, _ = openbb.economy.macro(parameters=[\"CPI\"], start_date=\"2010-01-01\")\n",
+                "cpi_chg = df.pct_change(1) * 100\n",
+                "subplots.add_scatter(\n",
+                "    x=cpi_chg.index,\n",
+                "    y=cpi_chg.T.values[0],\n",
+                "    name=\"CPI (% change)\",\n",
+                "    mode=\"lines\",\n",
+                "    line=dict(color=\"red\", dash=\"dash\"),\n",
+                "    secondary_y=True,\n",
+                "    yaxis=\"y2\",\n",
+                ")\n",
+                "subplots.update_yaxes(\n",
+                "    title_text=\"CPI (% change)\",\n",
+                "    secondary_y=True,\n",
+                "    range=[-2, 2],\n",
+                "    side=\"left\",\n",
+                "    overlaying=\"y\",\n",
+                ")\n",
+                "subplots.horizontal_legend()\n",
+                "\n",
+                "macro_0 = subplots.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "971e4c51",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "fred = openbb.economy.fred(series_ids=[\"T10Y3M\"], start_date=\"1980-01-01\")\n",
+                "\n",
+                "if (isinstance(fred, pd.DataFrame) and not fred.empty) or (\n",
+                "    not isinstance(fred, pd.DataFrame) and fred\n",
+                "):\n",
+                "    df, df_dict = fred\n",
+                "\n",
+                "    fig = OpenBBFigure.create_subplots(1, 1, specs=[[{\"secondary_y\": True}]])\n",
+                "    fig.add_scatter(\n",
+                "        x=df.index,\n",
+                "        y=df[\"T10Y3M\"],\n",
+                "        name=df_dict[\"T10Y3M\"][\"title\"],\n",
+                "        line=dict(color=\"red\", dash=\"dash\"),\n",
+                "        secondary_y=False,\n",
+                "    )\n",
+                "    openbb.economy.fred_chart(\n",
+                "        series_ids=[\"A191RP1A027NBEA\"],\n",
+                "        start_date=\"1980-01-01\",\n",
+                "        external_axes=True,\n",
+                "    ).to_subplot(fig, 1, 1, secondary_y=True)\n",
+                "    fig.update_yaxes(secondary_y=True, side=\"left\", overlaying=\"y\")\n",
+                "    fig.set_title(\"\")\n",
+                "    fig.horizontal_legend()\n",
+                "\n",
+                "    fred_0 = fig.to_html()\n",
+                "else:\n",
+                "    fred = None"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
+            "metadata": {},
+            "source": [
+                "## Render the report template to a file\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "body = f\"\"\"\n",
+                "<style>\n",
+                "@font-face {{\n",
+                "    font-family: \"Fira Code\";\n",
+                "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
+                "    font-weight: 400 700;\n",
+                "    font-stretch: 50%;\n",
+                "}}\n",
+                "</style>\n",
+                "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
+                "\"\"\"\n",
+                "\n",
+                "\n",
+                "img = (\n",
+                "    str(REPOSITORY_DIRECTORY)\n",
+                "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
+                ")\n",
+                "floppy_disk_img = (\n",
+                "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
+                ")\n",
+                "body += widgets.header(\n",
+                "    img,\n",
+                "    floppy_disk_img,\n",
+                "    author,\n",
+                "    report_date,\n",
+                "    report_time,\n",
+                "    report_timezone,\n",
+                "    f\"<b>ECONOMY REPORT: Leverage multiple sources to create custom reports.</b>\",\n",
+                ")\n",
+                "\n",
+                "body += widgets.tablinks(\n",
+                "    [\n",
+                "        \"SUMMARY\",\n",
+                "        \"Events\",\n",
+                "        \"Yields\",\n",
+                "        \"Equity Market\",\n",
+                "        \"Macro Data\",\n",
+                "    ]\n",
+                ")\n",
+                "\n",
+                "# Summary\n",
+                "htmlcode = widgets.row(\n",
+                "    [widgets.h(3, \"Global markets (source: WSJ)\") + overview.to_html()]\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Commodities (source: WSJ)\") + futures_fig.to_html()]\n",
+                "    + [\n",
+                "        widgets.h(3, \"Real-time sector performance (source: Alphavantage)\")\n",
+                "        + rtps_data.to_html().replace(\"table\", 'table style=\"display:inline\"')\n",
+                "    ]\n",
+                ")\n",
+                "htmlcode += widgets.row([chart_0])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Top news on 'economy' keyword (source: Newsapi)\") + news.to_html()]\n",
+                ")\n",
+                "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
+                "\n",
+                "# Events\n",
+                "htmlcode = widgets.row([widgets.h(3, \"Economic calendars (source: investing.com)\")])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"United States\") + events_1.to_html()])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Select European Countries\") + events_2.to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row([widgets.h(3, \"China\") + events_3.to_html()])\n",
+                "body += widgets.add_tab(\"Events\", htmlcode)\n",
+                "\n",
+                "# Yields\n",
+                "htmlcode = widgets.row([widgets.h(3, \"US treasuries (source: EconDB)\") + ust])\n",
+                "\n",
+                "if ycrv:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [\n",
+                "            widgets.h(3, f\"{ycrv_country_1} yield curve (source: FRED)\")\n",
+                "            + (ycrv_chart_1 or \"\")\n",
+                "        ]\n",
+                "    )\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"\") + ycrv_data_1.to_html()])\n",
+                "\n",
+                "body += widgets.add_tab(\"Yields\", htmlcode)\n",
+                "\n",
+                "# Equity market\n",
+                "htmlcode = widgets.row(\n",
+                "    [widgets.h(3, \"Valuation (source: Finviz)\") + valuation.to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Performance (source: Finviz)\") + valuation.to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row([widgets.h(3, \"US markets (source: YahooFinance)\") + eqty_0])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"European markets (source: YahooFinance)\") + eqty_1]\n",
+                ")\n",
+                "htmlcode += widgets.row([widgets.h(3, \"APAC markets (source: YahooFinance)\") + eqty_2])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Emerging markets (source: YahooFinance)\") + eqty_3]\n",
+                ")\n",
+                "htmlcode += widgets.row([widgets.h(3, \"ARCA (source: YahooFinance)\") + eqty_4])\n",
+                "body += widgets.add_tab(\"Equity Market\", htmlcode)\n",
+                "\n",
+                "# Macro\n",
+                "htmlcode = \"\"\n",
+                "if not bigmac_res.empty:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, \"Bigmac index (source: Nasdaq)\") + (bigmac or \"\")]\n",
+                "    )\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Leading indicators (source: EconDB)\") + macro_0])\n",
+                "if fred:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, \"Recession indicator (source: FRED)\") + fred_0]\n",
+                "    )\n",
+                "body += widgets.add_tab(\"Macro Data\", htmlcode)\n",
+                "\n",
+                "body += widgets.tab_clickable_and_save_evt()\n",
+                "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
+                "\n",
+                "# to save the results\n",
+                "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
+                "    fh.write(report)"
+            ]
+        }
+    ],
+    "metadata": {
+        "celltoolbar": "Tags",
+        "kernelspec": {
+            "display_name": "venv",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.9.13"
+        },
+        "vscode": {
+            "interpreter": {
+                "hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
+            }
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 5
+}
\ No newline at end of file
diff --git a/openbb_terminal/reports/templates/equity.ipynb b/openbb_terminal/reports/templates/equity.ipynb
index 2090444ccdd..8fe2d932bcf 100644
--- a/openbb_terminal/reports/templates/equity.ipynb
+++ b/openbb_terminal/reports/templates/equity.ipynb
@@ -1,1376 +1,1397 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "70ba2c8a",
-   "metadata": {},
-   "source": [
-    "## Notebook setup\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "driven-billion",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import warnings\n",
-    "import datetime\n",
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "from IPython.display import HTML\n",
-    "\n",
-    "# import sys\n",
-    "# sys.path.append('../../')\n",
-    "\n",
-    "from openbb_terminal.reports import widget_helpers as widgets\n",
-    "from openbb_terminal.sdk import openbb\n",
-    "from openbb_terminal import config_terminal as cfg\n",
-    "from openbb_terminal.helper_classes import TerminalStyle\n",
-    "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
-    "from openbb_terminal import OpenBBFigure\n",
-    "from openbb_terminal.core.plots.plotly_ta.ta_class import PlotlyTA\n",
-    "\n",
-    "warnings.filterwarnings(\"ignore\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cf31bcc7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from openbb_terminal.core.session.current_user import get_current_user\n",
-    "\n",
-    "user = get_current_user()\n",
-    "\n",
-    "cfg.theme = TerminalStyle(\n",
-    "    user.preferences.MPL_STYLE,\n",
-    "    user.preferences.PMF_STYLE,\n",
-    "    user.preferences.RICH_STYLE,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "stylesheet = widgets.html_report_stylesheet()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "807fda4e",
-   "metadata": {},
-   "source": [
-    "## Select symbol\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "intended-sherman",
-   "metadata": {
-    "tags": [
-     "parameters"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "# Parameters that will be replaced when calling this notebook\n",
-    "# Do not leave parameters blank as notebook will not run otherwise\n",
-    "symbol = \"msft\"\n",
-    "report_name = f\"Equity report for {symbol}\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a441ddbc-d75b-4a18-84d4-e01b677674d3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "if \".\" in symbol:\n",
-    "    import sys\n",
-    "\n",
-    "    sys.exit(0)\n",
-    "symbol = symbol.upper()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ticker_data = openbb.stocks.load(\n",
-    "    symbol=symbol, start_date=datetime.datetime.now() - datetime.timedelta(days=18 * 30)\n",
-    ")\n",
-    "ticker_data = openbb.stocks.process_candle(data=ticker_data)\n",
-    "\n",
-    "author = \"\"\n",
-    "report_title = f\"Investment Research Report on {symbol.upper()}\"\n",
-    "report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
-    "report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
-    "report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
-    "report_title, report_date, report_time, report_timezone"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e3b15d6f-dc9e-4f97-aa07-37d949a4e4bb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "info = openbb.stocks.fa.info(symbol=symbol).transpose()\n",
-    "\n",
-    "long_summary = \"Long business summary\"\n",
-    "long_name = \"Long name\"\n",
-    "\n",
-    "if long_summary in info and info[long_summary][0] != \"NA\":\n",
-    "    overview = info[long_summary][0]\n",
-    "elif long_name in info:\n",
-    "    overview = info[long_name][0]\n",
-    "else:\n",
-    "    overview = \"\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f8a0d747",
-   "metadata": {},
-   "source": [
-    "## Data\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "aca4b6ef",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "(\n",
-    "    df_year_estimates,\n",
-    "    df_quarter_earnings,\n",
-    "    df_quarter_revenues,\n",
-    ") = openbb.stocks.fa.est(symbol=symbol)\n",
-    "df_quarter_revenues"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c0f0a1ca",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "display_year = sorted(df_year_estimates.columns.tolist())[:3]\n",
-    "df_year_estimates = df_year_estimates[display_year].head(5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6976c1d5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "tables = openbb.etf.news(info[\"Short name\"][0], 5) if \"Short name\" in info else symbol\n",
-    "\n",
-    "for table in tables:\n",
-    "    if not isinstance(table, pd.DataFrame):\n",
-    "        continue\n",
-    "\n",
-    "    table[0].loc[\"link\"] = (\n",
-    "        table[0].loc[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
-    "    )"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "38e38d7c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "quote_data = openbb.stocks.quote(symbol)\n",
-    "quote_data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fde46353",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_institutional_shareholders = openbb.stocks.fa.shrs(symbol, holder=\"institutional\")\n",
-    "df_institutional_shareholders.index += 1\n",
-    "df_institutional_shareholders"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e101e24e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "openbb.stocks.fa.shrs(symbol)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "51dfd9d2",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_institutional_shareholders = openbb.stocks.fa.shrs(symbol)\n",
-    "df_institutional_shareholders.index += 1\n",
-    "df_institutional_shareholders"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3022130e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_sec_filings = openbb.stocks.fa.sec(symbol)[[\"Type\", \"Category\", \"Link\"]].head(5)\n",
-    "df_sec_filings[\"Link\"] = df_sec_filings[\"Link\"].apply(\n",
-    "    lambda x: f'<a href=\"{x}\">{x}</a>'\n",
-    ")\n",
-    "df_sec_filings"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4662b1ac",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_analyst = openbb.stocks.fa.analyst(symbol=symbol)\n",
-    "\n",
-    "if not df_analyst.empty:\n",
-    "    if \"target\" in df_analyst.columns:\n",
-    "        if \"target_to\" in df_analyst.columns:\n",
-    "            df_analyst[\"target\"] = df_analyst[\"target_to\"].combine_first(\n",
-    "                df_analyst[\"target\"]\n",
-    "            )\n",
-    "        else:\n",
-    "            df_analyst[\"target\"] = df_analyst[\"target_to\"]\n",
-    "        df_analyst = df_analyst[[\"category\", \"analyst\", \"rating\", \"target\"]].rename(\n",
-    "            columns={\n",
-    "                \"category\": \"Category\",\n",
-    "                \"analyst\": \"Analyst\",\n",
-    "                \"rating\": \"Rating\",\n",
-    "                \"target\": \"Price Target\",\n",
-    "            }\n",
-    "        )\n",
-    "df_analyst"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "df8bdb7d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_rating = openbb.stocks.fa.rating(symbol)\n",
-    "df_rating"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d0df953b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "pcr_chart = openbb.stocks.options.pcr_chart(symbol, window=30, external_axes=True)\n",
-    "\n",
-    "if pcr_chart:\n",
-    "    pcr_chart = pcr_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "bd79195c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "expiry_dates = openbb.stocks.options.expirations(symbol)\n",
-    "exp = expiry_dates[0]\n",
-    "option_chain = openbb.stocks.options.chains(symbol, expiration=exp)\n",
-    "current_price = float(ticker_data[\"Adj Close\"][-1])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ad6d0c24",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "vol_chart = openbb.stocks.options.vol(\n",
-    "    option_chain, current_price, symbol, exp, external_axes=True\n",
-    ")\n",
-    "\n",
-    "if vol_chart:\n",
-    "    vol_chart = vol_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "be2d1e3a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "voi_chart = openbb.stocks.options.voi(\n",
-    "    option_chain, current_price, symbol, exp, external_axes=True\n",
-    ")\n",
-    "\n",
-    "if voi_chart:\n",
-    "    voi_chart = voi_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "324e2d4b-b2f6-4da3-bac4-ef785ad4e436",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "net_short_position = openbb.stocks.dps.spos_chart(\n",
-    "    symbol=symbol,\n",
-    "    limit=84,\n",
-    "    raw=False,\n",
-    "    export=\"\",\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if net_short_position:\n",
-    "    net_short_position = net_short_position.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ac0bfbda-e4b8-4b3b-b8e7-c02639fdb971",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "dark_pools = openbb.stocks.dps.dpotc_chart(symbol=symbol, external_axes=True)\n",
-    "\n",
-    "if dark_pools:\n",
-    "    dark_pools = dark_pools.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "22a7266f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "gtrades_chart = openbb.stocks.gov.gtrades_chart(\n",
-    "    symbol,\n",
-    "    past_transactions_months=12,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if gtrades_chart:\n",
-    "    gtrades_chart = gtrades_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4c670ba3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "gov_contracts_chart = openbb.stocks.gov.contracts_chart(\n",
-    "    symbol,\n",
-    "    past_transaction_days=365,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if gov_contracts_chart:\n",
-    "    gov_contracts_chart = gov_contracts_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "caa3dae2",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "google_mentions_chart = openbb.stocks.ba.mentions_chart(\n",
-    "    symbol,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if google_mentions_chart:\n",
-    "    google_mentions_chart = google_mentions_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b77e60d8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "google_regions_chart = openbb.stocks.ba.regions_chart(\n",
-    "    symbol,\n",
-    "    limit=10,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if google_regions_chart:\n",
-    "    google_regions_chart = google_regions_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "78593369",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "similar_companies = openbb.stocks.ca.similar(symbol, source=\"Polygon\")\n",
-    "similar_companies.append(symbol)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4639665b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "historical_similar = openbb.stocks.ca.hist_chart(\n",
-    "    similar_companies,\n",
-    "    external_axes=True,\n",
-    "    normalize=False,\n",
-    ")\n",
-    "\n",
-    "if historical_similar:\n",
-    "    historical_similar = historical_similar.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "74565e53",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "hcorr_similar = openbb.stocks.ca.hcorr_chart(\n",
-    "    similar_companies,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if hcorr_similar:\n",
-    "    hcorr_similar = hcorr_similar.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "936babfd",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "vol_similar = openbb.stocks.ca.volume_chart(\n",
-    "    similar_companies,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if vol_similar:\n",
-    "    vol_similar = vol_similar.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "99388d4e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "scorr_similar = openbb.stocks.ca.scorr_chart(\n",
-    "    similar_companies,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if scorr_similar:\n",
-    "    scorr_similar = scorr_similar.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "eaa67343",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "income_comparison = openbb.stocks.ca.income(similar_companies)\n",
-    "income_comparison"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "13ad71cf",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "try:\n",
-    "    df_related_queries = openbb.stocks.ba.queries(symbol)\n",
-    "    df_related_queries.index += 1\n",
-    "    df_related_queries.index\n",
-    "except:\n",
-    "    pass"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "58c06129",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "try:\n",
-    "    df_rising_queries = openbb.stocks.ba.rise(symbol)\n",
-    "    df_rising_queries.index += 1\n",
-    "    df_rising_queries\n",
-    "except:\n",
-    "    pass"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0a467f1a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "gov_histcont_chart = openbb.stocks.gov.histcont_chart(\n",
-    "    symbol,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if gov_histcont_chart:\n",
-    "    gov_histcont_chart = gov_histcont_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "730cae26",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_lobbying = openbb.stocks.gov.lobbying(symbol, limit=5)\n",
-    "df_lobbying"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d8bb53c1-147e-4342-af61-0d0a9cc56e59",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "price_vs_short_interest = openbb.stocks.dps.psi_sg_chart(\n",
-    "    symbol=symbol, external_axes=True\n",
-    ")\n",
-    "\n",
-    "if price_vs_short_interest:\n",
-    "    price_vs_short_interest = price_vs_short_interest.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "394668e1-1158-4a2b-8a38-04c72a6abdd6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "price_chart = openbb.stocks.candle(\n",
-    "    symbol=symbol,\n",
-    "    data=ticker_data,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if price_chart:\n",
-    "    price_chart = price_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "900686a3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "price_target_chart = openbb.stocks.fa.pt_chart(\n",
-    "    symbol=symbol,\n",
-    "    start_date=\"2022-01-01\",\n",
-    "    data=ticker_data,\n",
-    "    limit=10,\n",
-    "    raw=False,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if price_target_chart:\n",
-    "    price_target_chart = price_target_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "61d62e1a-199e-481d-b57d-38ab486951be",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = openbb.stocks.fa.pt(symbol=symbol)\n",
-    "avg_ratings_last_30_days = 0\n",
-    "days = 0\n",
-    "if not df.empty:\n",
-    "    df_ratings = df[datetime.datetime.now() - datetime.timedelta(days=days) :]\n",
-    "    while df_ratings.empty:\n",
-    "        days += 30\n",
-    "        df_ratings = df[datetime.datetime.now() - datetime.timedelta(days=days) :]\n",
-    "\n",
-    "        if days > 100:\n",
-    "            break\n",
-    "\n",
-    "    if not df_ratings.empty:\n",
-    "        avg_ratings_last_30_days = round(np.mean(df_ratings[\"Price Target\"].values), 2)\n",
-    "    else:\n",
-    "        avg_ratings = 0\n",
-    "\n",
-    "last_price = round(ticker_data[\"Close\"][-1], 2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f3733ff2",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ratings_over_time_chart = openbb.stocks.fa.rot_chart(\n",
-    "    symbol=symbol,\n",
-    "    limit=10,\n",
-    "    raw=False,\n",
-    "    export=\"\",\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if ratings_over_time_chart:\n",
-    "    ratings_over_time_chart = ratings_over_time_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "924f8042-e58a-449c-91a3-7923158ff714",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ta_rsi = openbb.ta.rsi_chart(ticker_data[\"Close\"], external_axes=True)\n",
-    "\n",
-    "if ta_rsi:\n",
-    "    ta_rsi = ta_rsi.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "953a340e-7ea1-4aa3-ae1d-872683dced41",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = openbb.ta.rsi(ticker_data[\"Close\"])\n",
-    "rsi_value = round(df.values[-1][0], 2)\n",
-    "rsi_value"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dce71711-20b3-4c69-af52-e0f9a69991f8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.linear_model import LinearRegression\n",
-    "\n",
-    "model = LinearRegression().fit(\n",
-    "    np.array(range(len(ticker_data[\"Close\"][-30:].index))).reshape(-1, 1),\n",
-    "    ticker_data[\"Close\"][-30:].values,\n",
-    ")\n",
-    "regression_slope = round(model.coef_[0], 2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6272e34b-9511-4b48-9eea-ea882ce9846a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_insider = pd.DataFrame.from_dict(openbb.stocks.ins.lins(symbol=symbol)).head(10)\n",
-    "if not df_insider.empty:\n",
-    "    df_insider[\"Val ($)\"] = df_insider[\"Value ($)\"].replace({\",\": \"\"}, regex=True)\n",
-    "    df_insider[\"Trade\"] = df_insider.apply(\n",
-    "        lambda row: (-1 * float(row[\"Val ($)\"]))\n",
-    "        if row[\"Transaction\"] == \"Sale\"\n",
-    "        else (float(row[\"Val ($)\"]) if row[\"Transaction\"] == \"Buy\" else 0),\n",
-    "        axis=1,\n",
-    "    )\n",
-    "    last_10_insider_trading = round(sum(df_insider[\"Trade\"]) / 1_000_000, 2)\n",
-    "    df_insider = df_insider.drop(columns=[\"Val ($)\", \"Trade\"])\n",
-    "    df_insider"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "29254666-58c6-4686-87e6-2635ad8387e2",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "finbrain_sentiment = openbb.stocks.ba.headlines_chart(symbol=symbol, external_axes=True)\n",
-    "\n",
-    "if finbrain_sentiment:\n",
-    "    finbrain_sentiment = finbrain_sentiment.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b8251b47-8ecc-47be-83f3-d9f108596898",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_sentiment_finbrain = openbb.stocks.ca.sentiment(symbols=[symbol])\n",
-    "finbrain_sentiment_val = float(df_sentiment_finbrain.values[-1][0])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6fe6e513-d568-41b4-8aa0-37cc578c9dc3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "(\n",
-    "    watchlist_count,\n",
-    "    n_cases,\n",
-    "    n_bull,\n",
-    "    n_bear,\n",
-    ") = openbb.stocks.ba.bullbear(symbol=symbol)\n",
-    "stocktwits_sentiment = f\"Watchlist count: {watchlist_count}</br>\"\n",
-    "if n_cases > 0:\n",
-    "    stocktwits_sentiment += f\"\\nLast {n_cases} sentiment messages:</br>\"\n",
-    "    stocktwits_sentiment += f\"Bullish {round(100*n_bull/n_cases, 2)}%</br>\"\n",
-    "    stocktwits_sentiment += f\"Bearish {round(100*n_bear/n_cases, 2)}%\"\n",
-    "else:\n",
-    "    stocktwits_sentiment += \"No messages found\"\n",
-    "stocktwits_sentiment"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "bfb75909-b877-4b3a-82a7-21ce174a7bb4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "snews = openbb.stocks.ba.snews_chart(symbol, external_axes=True)\n",
-    "\n",
-    "if snews:\n",
-    "    snews = snews.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "329c9e1b-e1de-4836-91fd-656cc87f7111",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ticker_data_all = openbb.stocks.load(\n",
-    "    symbol=symbol,\n",
-    "    start_date=datetime.datetime.now() - datetime.timedelta(days=5 * 12 * 21),\n",
-    ")\n",
-    "ticker_data_all[\"Returns\"] = ticker_data_all[\"Adj Close\"].pct_change()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "37743ef3-2f16-4166-bfcc-a0fe3eb959bc",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bw_month = openbb.qa.bw(\n",
-    "    ticker_data_all,\n",
-    "    \"Returns\",\n",
-    "    symbol,\n",
-    "    yearly=False,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if bw_month:\n",
-    "    bw_month = bw_month.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "16b33868-23dc-4c77-ac00-acb452da386c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bw_year = openbb.qa.bw(\n",
-    "    ticker_data_all,\n",
-    "    \"Returns\",\n",
-    "    symbol,\n",
-    "    yearly=True,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if bw_year:\n",
-    "    bw_year = bw_year.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "28ce0827",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "income_df = openbb.stocks.fa.income(symbol, source=\"FinancialModelingPrep\")\n",
-    "data_df = openbb.stocks.fa.data(symbol)\n",
-    "mgmt_df = openbb.stocks.fa.mgmt(symbol)\n",
-    "if not mgmt_df.empty:\n",
-    "    mgmt_df[\"Info\"] = mgmt_df[\"Info\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
-    "    mgmt_df[\"Insider Activity\"] = mgmt_df[\"Insider Activity\"].apply(\n",
-    "        lambda x: f'<a href=\"{x}\">{x}</a>' if x != \"-\" else x\n",
-    "    )\n",
-    "try:\n",
-    "    hist_dcf = openbb.stocks.fa.dcfc(symbol)\n",
-    "except:\n",
-    "    pass\n",
-    "enterprise_df = openbb.stocks.fa.enterprise(symbol)\n",
-    "score = openbb.stocks.fa.score(symbol, years=10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "42e289ab",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "indicators = dict(\n",
-    "    ema=dict(length=[50]),\n",
-    "    sma=dict(length=[50]),\n",
-    "    wma=dict(length=[50]),\n",
-    ")\n",
-    "\n",
-    "ma_chart = PlotlyTA.plot(ticker_data, indicators, symbol, candles=False, volume=False)\n",
-    "\n",
-    "if ma_chart:\n",
-    "    ma_chart = ma_chart.show(external=True)\n",
-    "    ma_chart = ma_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e8846a6f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "macd_chart = openbb.ta.macd_chart(\n",
-    "    ticker_data[\"Close\"], symbol=symbol, external_axes=True\n",
-    ")\n",
-    "\n",
-    "if macd_chart:\n",
-    "    macd_chart = macd_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "48a7a427",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "cci_chart = openbb.ta.cci_chart(ticker_data, symbol=symbol, external_axes=True)\n",
-    "\n",
-    "if cci_chart:\n",
-    "    cci_chart = cci_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6a1bd2c6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "stoch_chart = openbb.ta.stoch_chart(ticker_data, symbol=symbol, external_axes=True)\n",
-    "\n",
-    "if stoch_chart:\n",
-    "    stoch_chart = stoch_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2611d3c6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "adx_chart = openbb.ta.adx_chart(ticker_data, symbol=symbol, external_axes=True)\n",
-    "\n",
-    "if adx_chart:\n",
-    "    adx_chart = adx_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6ecb6e17",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bbands_chart = openbb.ta.bbands_chart(ticker_data, symbol=symbol, external_axes=True)\n",
-    "\n",
-    "if bbands_chart:\n",
-    "    bbands_chart = bbands_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "07e42fdb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ad_chart = openbb.ta.ad_chart(ticker_data, symbol=symbol, external_axes=True)\n",
-    "\n",
-    "if ad_chart:\n",
-    "    ad_chart = ad_chart.to_html()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
-   "metadata": {},
-   "source": [
-    "## Render the report template to a file\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "body = f\"\"\"\n",
-    "<style>\n",
-    "@font-face {{\n",
-    "    font-family: \"Fira Code\";\n",
-    "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
-    "    font-weight: 400 700;\n",
-    "    font-stretch: 50%;\n",
-    "}}\n",
-    "</style>\n",
-    "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
-    "\"\"\"\n",
-    "\n",
-    "\n",
-    "img = (\n",
-    "    str(REPOSITORY_DIRECTORY)\n",
-    "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
-    ")\n",
-    "floppy_disk_img = (\n",
-    "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
-    ")\n",
-    "body += widgets.header(\n",
-    "    img,\n",
-    "    floppy_disk_img,\n",
-    "    author,\n",
-    "    report_date,\n",
-    "    report_time,\n",
-    "    report_timezone,\n",
-    "    report_title,\n",
-    ")\n",
-    "\n",
-    "body += widgets.tablinks(\n",
-    "    [\n",
-    "        \"SUMMARY\",\n",
-    "        \"Overview\",\n",
-    "        \"Fundamental Analysis\",\n",
-    "        \"Technical Analysis\",\n",
-    "        \"Behavioural Analysis\",\n",
-    "        \"Government Menu\",\n",
-    "        \"Comparison Menu\",\n",
-    "        \"Options\",\n",
-    "        \"Dark Pool and Shorts\",\n",
-    "        \"Quantitative Analysis\",\n",
-    "        \"Analyst Opinions\",\n",
-    "        \"Insider Trading\",\n",
-    "        #    \"Prediction Techniques\",\n",
-    "    ]\n",
-    ")\n",
-    "\n",
-    "htmlcode = widgets.h(3, \"KPIs\")\n",
-    "htmlcode += widgets.kpi(\n",
-    "    [last_price],\n",
-    "    [\n",
-    "        \"Last closing price is above the average price ratings of last 30 days\",\n",
-    "        \"Average price ratings of last 30 day is above last closing price\",\n",
-    "    ],\n",
-    "    avg_ratings_last_30_days,\n",
-    ")\n",
-    "htmlcode += widgets.kpi(\n",
-    "    [30, 70],\n",
-    "    [\"RSI level is oversold\", \"RSI level is normal\", \"RSI level is overbought\"],\n",
-    "    rsi_value,\n",
-    ")\n",
-    "try:\n",
-    "    htmlcode += widgets.kpi(\n",
-    "        [0],\n",
-    "        [\n",
-    "            \"The sum of last 10 insider trading (in millions) was negative\",\n",
-    "            \"The sum of last 10 insider trading (in millions) was positive\",\n",
-    "        ],\n",
-    "        last_10_insider_trading,\n",
-    "    )\n",
-    "except:\n",
-    "    pass\n",
-    "htmlcode += widgets.kpi(\n",
-    "    [-0.1, 0.1],\n",
-    "    [\n",
-    "        \"Last FinBrain sentiment is bearish\",\n",
-    "        \" Last FinBrain sentiment is neutral\",\n",
-    "        \"Last FinBrain sentiment is bullish\",\n",
-    "    ],\n",
-    "    finbrain_sentiment_val,\n",
-    ")\n",
-    "if score and score[\"Total Score\"]:\n",
-    "    htmlcode += widgets.kpi(\n",
-    "        [25, 75],\n",
-    "        [\n",
-    "            \"Buffet Score is not favourable\",\n",
-    "            \"Buffet Score is neutral\",\n",
-    "            \"Buffet Score is favourable\",\n",
-    "        ],\n",
-    "        float(score[\"Total Score\"]),\n",
-    "    )\n",
-    "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
-    "\n",
-    "htmlcode = \"\"\n",
-    "if overview:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Description\") + widgets.p(overview)])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Price Chart\") + (price_chart or \"\")])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Quote\") + quote_data.to_html()])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Latest News for \" + symbol)])\n",
-    "try:\n",
-    "    for table in tables:\n",
-    "        htmlcode += widgets.row(\n",
-    "            [widgets.h(4, table[1][\"title\"]) + table[0].to_html(escape=False)]\n",
-    "        )\n",
-    "except:\n",
-    "    pass\n",
-    "\n",
-    "if not mgmt_df.empty:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, f\"Management team of {symbol}\") + mgmt_df.to_html(escape=False)]\n",
-    "    )\n",
-    "body += widgets.add_tab(\"Overview\", htmlcode)\n",
-    "\n",
-    "htmlcode = widgets.row(\n",
-    "    [widgets.h(3, \"Price Target Chart\") + (price_target_chart or \"\")]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Analyst Ratings over time\") + (ratings_over_time_chart or \"\")]\n",
-    ")\n",
-    "try:\n",
-    "    htmlcode += widgets.row([widgets.h(3, \"Analyst Ratings\") + df_analyst.to_html()])\n",
-    "except:\n",
-    "    pass\n",
-    "try:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, \"Analyst Recommendations\") + df_rating.to_html()]\n",
-    "    )\n",
-    "except:\n",
-    "    pass\n",
-    "\n",
-    "body += widgets.add_tab(\"Analyst Opinions\", htmlcode)\n",
-    "\n",
-    "try:\n",
-    "    htmlcode = widgets.row(\n",
-    "        [widgets.h(3, \"Estimates\") + df_year_estimates.head().to_html()]\n",
-    "    )\n",
-    "except:\n",
-    "    pass\n",
-    "\n",
-    "if not df_quarter_earnings.empty:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, \"Earnings\") + df_quarter_earnings.head().to_html()]\n",
-    "    )\n",
-    "if not df_quarter_revenues.empty:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, \"Revenues\") + df_quarter_revenues.head().to_html()]\n",
-    "    )\n",
-    "try:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [\n",
-    "            widgets.h(3, \"Major Institutional Shareholders\")\n",
-    "            + df_institutional_shareholders.head().to_html()\n",
-    "        ]\n",
-    "    )\n",
-    "except:\n",
-    "    pass\n",
-    "try:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, f\"Historical DCF for {symbol}\") + hist_dcf.to_html()]\n",
-    "    )\n",
-    "except:\n",
-    "    pass\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, f\"Enterprise data for {symbol}\") + enterprise_df.to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, f\"Income Statement for {symbol}\") + income_df.to_html()]\n",
-    ")\n",
-    "try:\n",
-    "    htmlcode += widgets.row([widgets.h(3, f\"Data for {symbol}\") + data_df.to_html()])\n",
-    "except:\n",
-    "    pass\n",
-    "try:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [widgets.h(3, \"SEC filings\") + df_sec_filings.to_html(escape=False)]\n",
-    "    )\n",
-    "except:\n",
-    "    pass\n",
-    "\n",
-    "body += widgets.add_tab(\"Fundamental Analysis\", htmlcode)\n",
-    "\n",
-    "htmlcode = widgets.row([widgets.h(3, \"Put to call ratio\") + (pcr_chart or \"\")])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Option Volume for closest expiry date\") + (vol_chart or \"\")]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [\n",
-    "        widgets.h(3, \"Volume and Open Interest for closest expiry date\")\n",
-    "        + (voi_chart or \"\")\n",
-    "    ]\n",
-    ")\n",
-    "\n",
-    "body += widgets.add_tab(\"Options\", htmlcode)\n",
-    "\n",
-    "htmlcode = widgets.row([net_short_position or \"\"])\n",
-    "htmlcode += widgets.row([price_vs_short_interest or \"\"])\n",
-    "# htmlcode += widgets.row([dark_pools])\n",
-    "body += widgets.add_tab(\"Dark Pool and Shorts\", htmlcode)\n",
-    "\n",
-    "htmlcode = widgets.row(\n",
-    "    [\n",
-    "        widgets.h(3, \"Congress trading in the past 12 months for \" + symbol)\n",
-    "        + (gtrades_chart or \"\")\n",
-    "    ]\n",
-    ")\n",
-    "htmlcode += widgets.row([gov_histcont_chart or \"\"])\n",
-    "htmlcode += widgets.row([gov_contracts_chart or \"\"])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Recent Corporate Lobbying by \" + symbol)])\n",
-    "try:\n",
-    "    for _, row in df_lobbying.iterrows():\n",
-    "        amount = (\n",
-    "            \"$\" + str(int(float(row[\"Amount\"]))) if row[\"Amount\"] is not None else \"N/A\"\n",
-    "        )\n",
-    "        htmlcode += widgets.row([widgets.p(f\"{row['Date']}: {row['Client']} {amount}\")])\n",
-    "        if (row[\"Amount\"] is not None) and (row[\"Specific_Issue\"] is not None):\n",
-    "            htmlcode += widgets.row(\n",
-    "                [\n",
-    "                    widgets.p(\n",
-    "                        \"\\t\"\n",
-    "                        + row[\"Specific_Issue\"].replace(\"\\n\", \" \").replace(\"\\r\", \"\")\n",
-    "                    )\n",
-    "                ]\n",
-    "            )\n",
-    "except:\n",
-    "    pass\n",
-    "\n",
-    "body += widgets.add_tab(\"Government Menu\", htmlcode)\n",
-    "\n",
-    "htmlcode = widgets.row(\n",
-    "    [\n",
-    "        widgets.h(3, f\"Price over the past year for companies similar to {symbol}\")\n",
-    "        + (historical_similar or \"\")\n",
-    "    ]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [\n",
-    "        widgets.h(3, f\"Price correlation with similar companies for {symbol}\")\n",
-    "        + (hcorr_similar or \"\")\n",
-    "    ]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [\n",
-    "        widgets.h(3, f\"Volume over the past year for companies similar to {symbol}\")\n",
-    "        + (vol_similar or \"\")\n",
-    "    ]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [\n",
-    "        widgets.h(3, f\"Sentiment correlation with similar companies for {symbol}\")\n",
-    "        + (scorr_similar or \"\")\n",
-    "    ]\n",
-    ")\n",
-    "if isinstance(income_comparison, pd.DataFrame):\n",
-    "    htmlcode += widgets.row(\n",
-    "        [\n",
-    "            widgets.h(3, f\"Income data for similar companies to {symbol}\")\n",
-    "            + income_comparison.to_html()\n",
-    "        ]\n",
-    "    )\n",
-    "htmlcode += widgets.row(\n",
-    "    [\n",
-    "        widgets.p(\n",
-    "            \"Note that similar companies have been found using openbb.stocks.ca.similar\"\n",
-    "        )\n",
-    "    ]\n",
-    ")\n",
-    "body += widgets.add_tab(\"Comparison Menu\", htmlcode)\n",
-    "\n",
-    "htmlcode = widgets.row([widgets.h(3, f\"Moving Averages for {symbol}\") + ma_chart])\n",
-    "htmlcode += widgets.row([macd_chart or \"\"])\n",
-    "htmlcode += widgets.row([ta_rsi or \"\"])\n",
-    "htmlcode += widgets.row([stoch_chart or \"\"])\n",
-    "htmlcode += widgets.row([cci_chart or \"\"])\n",
-    "htmlcode += widgets.row([ad_chart or \"\"])\n",
-    "htmlcode += widgets.row([bbands_chart or \"\"])\n",
-    "htmlcode += widgets.row([adx_chart or \"\"])\n",
-    "body += widgets.add_tab(\"Technical Analysis\", htmlcode)\n",
-    "\n",
-    "if not df_insider.empty:\n",
-    "    htmlcode = widgets.row(\n",
-    "        [widgets.h(3, \"Last Activity\") + df_insider.head(10).to_html(col_space=\"75px\")]\n",
-    "    )\n",
-    "else:\n",
-    "    htmlcode = widgets.row(\n",
-    "        [widgets.h(3, \"Last Activity\") + widgets.p(\"No insider trading data found.\")]\n",
-    "    )\n",
-    "\n",
-    "body += widgets.add_tab(\"Insider Trading\", htmlcode)\n",
-    "\n",
-    "\n",
-    "htmlcode = widgets.row([bw_year or \"\"])\n",
-    "htmlcode += widgets.row([bw_month or \"\"])\n",
-    "body += widgets.add_tab(\"Quantitative Analysis\", htmlcode)\n",
-    "\n",
-    "\n",
-    "htmlcode = widgets.row([finbrain_sentiment or \"\"])\n",
-    "htmlcode += widgets.row([snews or \"\"])\n",
-    "htmlcode += widgets.row(\n",
-    "    [\n",
-    "        widgets.h(3, \"Interest in \" + symbol + \" based on google analytics\")\n",
-    "        + (google_mentions_chart or \"\")\n",
-    "    ]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [\n",
-    "        widgets.h(3, f\"Regions with highest interest in {symbol}\")\n",
-    "        + (google_regions_chart or \"\")\n",
-    "    ]\n",
-    ")\n",
-    "try:\n",
-    "    htmlcode += widgets.row(\n",
-    "        [\n",
-    "            widgets.h(3, f\"Top queries related to {symbol}\")\n",
-    "            + df_related_queries.to_html()\n",
-    "        ]\n",
-    "    )\n",
-    "    htmlcode += widgets.row(\n",
-    "        [\n",
-    "            widgets.h(3, f\"Top rising queries related to {symbol}\")\n",
-    "            + df_rising_queries.to_html()\n",
-    "        ]\n",
-    "    )\n",
-    "except:\n",
-    "    pass\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, f\"Stocktwits sentiment for {symbol}\") + stocktwits_sentiment]\n",
-    ")\n",
-    "body += widgets.add_tab(\"Behavioural Analysis\", htmlcode)\n",
-    "\n",
-    "body += widgets.tab_clickable_and_save_evt()\n",
-    "\n",
-    "report = widgets.html_report(\n",
-    "    title=report_name, stylesheet=widgets.html_report_stylesheet(), body=body\n",
-    ")\n",
-    "\n",
-    "# to save the results\n",
-    "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
-    "    fh.write(report)"
-   ]
-  }
- ],
- "metadata": {
-  "celltoolbar": "Tags",
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.9"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "af870c0f9615f5bb08692efcc9bf540319fe60e6793056508a4dab09c9fa8dda"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "id": "70ba2c8a",
+            "metadata": {},
+            "source": [
+                "## Notebook setup\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "driven-billion",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import warnings\n",
+                "import datetime\n",
+                "import numpy as np\n",
+                "import pandas as pd\n",
+                "\n",
+                "from IPython.display import HTML\n",
+                "\n",
+                "from openbb_terminal import config_terminal as cfg\n",
+                "from openbb_terminal.helper_classes import TerminalStyle\n",
+                "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
+                "from openbb_terminal import OpenBBFigure\n",
+                "from openbb_terminal.core.plots.plotly_ta.ta_class import PlotlyTA\n",
+                "\n",
+                "warnings.filterwarnings(\"ignore\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "150e5103",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Suppressing sdk logs\n",
+                "cfg.change_logging_suppress(new_value=True)\n",
+                "\n",
+                "# Import the OpenBB SDK\n",
+                "from openbb_terminal.sdk import openbb, widgets"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "cf31bcc7",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from openbb_terminal.core.session.current_user import get_current_user\n",
+                "\n",
+                "user = get_current_user()\n",
+                "\n",
+                "cfg.theme = TerminalStyle(\n",
+                "    user.preferences.MPL_STYLE,\n",
+                "    user.preferences.PMF_STYLE,\n",
+                "    user.preferences.RICH_STYLE,\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "stylesheet = widgets.html_report_stylesheet()"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "id": "807fda4e",
+            "metadata": {},
+            "source": [
+                "## Select symbol\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "intended-sherman",
+            "metadata": {
+                "tags": [
+                    "parameters"
+                ]
+            },
+            "outputs": [],
+            "source": [
+                "# Parameters that will be replaced when calling this notebook\n",
+                "# Do not leave parameters blank as notebook will not run otherwise\n",
+                "symbol = \"msft\"\n",
+                "report_name = f\"Equity report for {symbol}\""
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "a441ddbc-d75b-4a18-84d4-e01b677674d3",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "if \".\" in symbol:\n",
+                "    import sys\n",
+                "\n",
+                "    sys.exit(0)\n",
+                "symbol = symbol.upper()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ticker_data = openbb.stocks.load(\n",
+                "    symbol=symbol, start_date=datetime.datetime.now() - datetime.timedelta(days=18 * 30)\n",
+                ")\n",
+                "ticker_data = openbb.stocks.process_candle(data=ticker_data)\n",
+                "\n",
+                "author = \"\"\n",
+                "report_title = f\"Investment Research Report on {symbol.upper()}\"\n",
+                "report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
+                "report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
+                "report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
+                "report_title, report_date, report_time, report_timezone"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e3b15d6f-dc9e-4f97-aa07-37d949a4e4bb",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "info = openbb.stocks.fa.info(symbol=symbol).transpose()\n",
+                "\n",
+                "long_summary = \"Long business summary\"\n",
+                "long_name = \"Long name\"\n",
+                "\n",
+                "if long_summary in info and info[long_summary][0] != \"NA\":\n",
+                "    overview = info[long_summary][0]\n",
+                "elif long_name in info:\n",
+                "    overview = info[long_name][0]\n",
+                "else:\n",
+                "    overview = \"\""
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "f8a0d747",
+            "metadata": {},
+            "source": [
+                "## Data\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "aca4b6ef",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "(\n",
+                "    df_year_estimates,\n",
+                "    df_quarter_earnings,\n",
+                "    df_quarter_revenues,\n",
+                ") = openbb.stocks.fa.est(symbol=symbol)\n",
+                "df_quarter_revenues"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "c0f0a1ca",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "display_year = sorted(df_year_estimates.columns.tolist())[:3]\n",
+                "df_year_estimates = df_year_estimates[display_year].head(5)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "6976c1d5",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "tables = openbb.etf.news(info[\"Short name\"][0], 5) if \"Short name\" in info else symbol\n",
+                "\n",
+                "for table in tables:\n",
+                "    if not isinstance(table, pd.DataFrame):\n",
+                "        continue\n",
+                "\n",
+                "    table[0].loc[\"link\"] = (\n",
+                "        table[0].loc[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
+                "    )"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "38e38d7c",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "quote_data = openbb.stocks.quote(symbol)\n",
+                "quote_data"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "fde46353",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "df_institutional_shareholders = openbb.stocks.fa.shrs(symbol, holder=\"institutional\")\n",
+                "df_institutional_shareholders.index += 1\n",
+                "df_institutional_shareholders"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e101e24e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "openbb.stocks.fa.shrs(symbol)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "51dfd9d2",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "df_institutional_shareholders = openbb.stocks.fa.shrs(symbol)\n",
+                "df_institutional_shareholders.index += 1\n",
+                "df_institutional_shareholders"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "3022130e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "df_sec_filings = openbb.stocks.fa.sec(symbol)[[\"Type\", \"Category\", \"Link\"]].head(5)\n",
+                "df_sec_filings[\"Link\"] = df_sec_filings[\"Link\"].apply(\n",
+                "    lambda x: f'<a href=\"{x}\">{x}</a>'\n",
+                ")\n",
+                "df_sec_filings"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "4662b1ac",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "df_analyst = openbb.stocks.fa.analyst(symbol=symbol)\n",
+                "\n",
+                "if not df_analyst.empty:\n",
+                "    if \"target\" in df_analyst.columns:\n",
+                "        if \"target_to\" in df_analyst.columns:\n",
+                "            df_analyst[\"target\"] = df_analyst[\"target_to\"].combine_first(\n",
+                "                df_analyst[\"target\"]\n",
+                "            )\n",
+                "        else:\n",
+                "            df_analyst[\"target\"] = df_analyst[\"target_to\"]\n",
+                "        df_analyst = df_analyst[[\"category\", \"analyst\", \"rating\", \"target\"]].rename(\n",
+                "            columns={\n",
+                "                \"category\": \"Category\",\n",
+                "                \"analyst\": \"Analyst\",\n",
+                "                \"rating\": \"Rating\",\n",
+                "                \"target\": \"Price Target\",\n",
+                "            }\n",
+                "        )\n",
+                "df_analyst"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "df8bdb7d",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "df_rating = openbb.stocks.fa.rating(symbol)\n",
+                "df_rating"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "d0df953b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "pcr_chart = openbb.stocks.options.pcr_chart(symbol, window=30, external_axes=True)\n",
+                "\n",
+                "if pcr_chart:\n",
+                "    pcr_chart = pcr_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "bd79195c",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "expiry_dates = openbb.stocks.options.expirations(symbol)\n",
+                "exp = expiry_dates[0]\n",
+                "option_chain = openbb.stocks.options.chains(symbol, expiration=exp)\n",
+                "current_price = float(ticker_data[\"Adj Close\"][-1])"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "ad6d0c24",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "vol_chart = openbb.stocks.options.vol(\n",
+                "    option_chain, current_price, symbol, exp, external_axes=True\n",
+                ")\n",
+                "\n",
+                "if vol_chart:\n",
+                "    vol_chart = vol_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "be2d1e3a",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "voi_chart = openbb.stocks.options.voi(\n",
+                "    option_chain, current_price, symbol, exp, external_axes=True\n",
+                ")\n",
+                "\n",
+                "if voi_chart:\n",
+                "    voi_chart = voi_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "324e2d4b-b2f6-4da3-bac4-ef785ad4e436",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "net_short_position = openbb.stocks.dps.spos_chart(\n",
+                "    symbol=symbol,\n",
+                "    limit=84,\n",
+                "    raw=False,\n",
+                "    export=\"\",\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if net_short_position:\n",
+                "    net_short_position = net_short_position.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "ac0bfbda-e4b8-4b3b-b8e7-c02639fdb971",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "dark_pools = openbb.stocks.dps.dpotc_chart(symbol=symbol, external_axes=True)\n",
+                "\n",
+                "if dark_pools:\n",
+                "    dark_pools = dark_pools.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "22a7266f",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "gtrades_chart = openbb.stocks.gov.gtrades_chart(\n",
+                "    symbol,\n",
+                "    past_transactions_months=12,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if gtrades_chart:\n",
+                "    gtrades_chart = gtrades_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "4c670ba3",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "gov_contracts_chart = openbb.stocks.gov.contracts_chart(\n",
+                "    symbol,\n",
+                "    past_transaction_days=365,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if gov_contracts_chart:\n",
+                "    gov_contracts_chart = gov_contracts_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "caa3dae2",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "google_mentions_chart = openbb.stocks.ba.mentions_chart(\n",
+                "    symbol,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if google_mentions_chart:\n",
+                "    google_mentions_chart = google_mentions_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "b77e60d8",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "google_regions_chart = openbb.stocks.ba.regions_chart(\n",
+                "    symbol,\n",
+                "    limit=10,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if google_regions_chart:\n",
+                "    google_regions_chart = google_regions_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "78593369",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "similar_companies = openbb.stocks.ca.similar(symbol, source=\"Polygon\")\n",
+                "if similar_companies:\n",
+                "    similar_companies.append(symbol)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "4639665b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "historical_similar = openbb.stocks.ca.hist_chart(\n",
+                "    similar_companies,\n",
+                "    external_axes=True,\n",
+                "    normalize=False,\n",
+                ")\n",
+                "\n",
+                "if historical_similar:\n",
+                "    historical_similar = historical_similar.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "74565e53",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "hcorr_similar = openbb.stocks.ca.hcorr_chart(\n",
+                "    similar_companies,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if hcorr_similar:\n",
+                "    hcorr_similar = hcorr_similar.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "936babfd",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "vol_similar = openbb.stocks.ca.volume_chart(\n",
+                "    similar_companies,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if vol_similar:\n",
+                "    vol_similar = vol_similar.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "99388d4e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "scorr_similar = openbb.stocks.ca.scorr_chart(\n",
+                "    similar_companies,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if scorr_similar:\n",
+                "    scorr_similar = scorr_similar.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "eaa67343",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "income_comparison = openbb.stocks.ca.income(similar_companies)\n",
+                "income_comparison"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "13ad71cf",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "try:\n",
+                "    df_related_queries = openbb.stocks.ba.queries(symbol)\n",
+                "    df_related_queries.index += 1\n",
+                "    df_related_queries.index\n",
+                "except:\n",
+                "    pass"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "58c06129",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "try:\n",
+                "    df_rising_queries = openbb.stocks.ba.rise(symbol)\n",
+                "    df_rising_queries.index += 1\n",
+                "    df_rising_queries\n",
+                "except:\n",
+                "    pass"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "0a467f1a",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "gov_histcont_chart = openbb.stocks.gov.histcont_chart(\n",
+                "    symbol,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if gov_histcont_chart:\n",
+                "    gov_histcont_chart = gov_histcont_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "730cae26",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "df_lobbying = openbb.stocks.gov.lobbying(symbol, limit=5)\n",
+                "df_lobbying"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "d8bb53c1-147e-4342-af61-0d0a9cc56e59",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "price_vs_short_interest = openbb.stocks.dps.psi_sg_chart(\n",
+                "    symbol=symbol, external_axes=True\n",
+                ")\n",
+                "\n",
+                "if price_vs_short_interest:\n",
+                "    price_vs_short_interest = price_vs_short_interest.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "394668e1-1158-4a2b-8a38-04c72a6abdd6",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "price_chart = openbb.stocks.candle(\n",
+                "    symbol=symbol,\n",
+                "    data=ticker_data,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if price_chart:\n",
+                "    price_chart = price_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "900686a3",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "price_target_chart = openbb.stocks.fa.pt_chart(\n",
+                "    symbol=symbol,\n",
+                "    start_date=\"2022-01-01\",\n",
+                "    data=ticker_data,\n",
+                "    limit=10,\n",
+                "    raw=False,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if price_target_chart:\n",
+                "    price_target_chart = price_target_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "61d62e1a-199e-481d-b57d-38ab486951be",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "df = openbb.stocks.fa.pt(symbol=symbol)\n",
+                "avg_ratings_last_30_days = 0\n",
+                "days = 0\n",
+                "if not df.empty:\n",
+                "    df_ratings = df[datetime.datetime.now() - datetime.timedelta(days=days) :]\n",
+                "    while df_ratings.empty:\n",
+                "        days += 30\n",
+                "        df_ratings = df[datetime.datetime.now() - datetime.timedelta(days=days) :]\n",
+                "\n",
+                "        if days > 100:\n",
+                "            break\n",
+                "\n",
+                "    if not df_ratings.empty:\n",
+                "        avg_ratings_last_30_days = round(np.mean(df_ratings[\"Price Target\"].values), 2)\n",
+                "    else:\n",
+                "        avg_ratings = 0\n",
+                "\n",
+                "last_price = round(ticker_data[\"Close\"][-1], 2)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "f3733ff2",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ratings_over_time_chart = openbb.stocks.fa.rot_chart(\n",
+                "    symbol=symbol,\n",
+                "    limit=10,\n",
+                "    raw=False,\n",
+                "    export=\"\",\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if ratings_over_time_chart:\n",
+                "    ratings_over_time_chart = ratings_over_time_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "924f8042-e58a-449c-91a3-7923158ff714",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ta_rsi = openbb.ta.rsi_chart(ticker_data[\"Close\"], external_axes=True)\n",
+                "\n",
+                "if ta_rsi:\n",
+                "    ta_rsi = ta_rsi.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "953a340e-7ea1-4aa3-ae1d-872683dced41",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "df = openbb.ta.rsi(ticker_data[\"Close\"])\n",
+                "rsi_value = round(df.values[-1][0], 2)\n",
+                "rsi_value"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "dce71711-20b3-4c69-af52-e0f9a69991f8",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from sklearn.linear_model import LinearRegression\n",
+                "\n",
+                "model = LinearRegression().fit(\n",
+                "    np.array(range(len(ticker_data[\"Close\"][-30:].index))).reshape(-1, 1),\n",
+                "    ticker_data[\"Close\"][-30:].values,\n",
+                ")\n",
+                "regression_slope = round(model.coef_[0], 2)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "6272e34b-9511-4b48-9eea-ea882ce9846a",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "df_insider = pd.DataFrame.from_dict(openbb.stocks.ins.lins(symbol=symbol)).head(10)\n",
+                "if not df_insider.empty:\n",
+                "    df_insider[\"Val ($)\"] = df_insider[\"Value ($)\"].replace({\",\": \"\"}, regex=True)\n",
+                "    df_insider[\"Trade\"] = df_insider.apply(\n",
+                "        lambda row: (-1 * float(row[\"Val ($)\"]))\n",
+                "        if row[\"Transaction\"] == \"Sale\"\n",
+                "        else (float(row[\"Val ($)\"]) if row[\"Transaction\"] == \"Buy\" else 0),\n",
+                "        axis=1,\n",
+                "    )\n",
+                "    last_10_insider_trading = round(sum(df_insider[\"Trade\"]) / 1_000_000, 2)\n",
+                "    df_insider = df_insider.drop(columns=[\"Val ($)\", \"Trade\"])\n",
+                "    df_insider"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "29254666-58c6-4686-87e6-2635ad8387e2",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "finbrain_sentiment = openbb.stocks.ba.headlines_chart(symbol=symbol, external_axes=True)\n",
+                "\n",
+                "if finbrain_sentiment:\n",
+                "    finbrain_sentiment = finbrain_sentiment.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "b8251b47-8ecc-47be-83f3-d9f108596898",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "df_sentiment_finbrain = openbb.stocks.ca.sentiment(symbols=[symbol])\n",
+                "finbrain_sentiment_val = float(df_sentiment_finbrain.values[-1][0])"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "6fe6e513-d568-41b4-8aa0-37cc578c9dc3",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "(\n",
+                "    watchlist_count,\n",
+                "    n_cases,\n",
+                "    n_bull,\n",
+                "    n_bear,\n",
+                ") = openbb.stocks.ba.bullbear(symbol=symbol)\n",
+                "stocktwits_sentiment = f\"Watchlist count: {watchlist_count}</br>\"\n",
+                "if n_cases > 0:\n",
+                "    stocktwits_sentiment += f\"\\nLast {n_cases} sentiment messages:</br>\"\n",
+                "    stocktwits_sentiment += f\"Bullish {round(100*n_bull/n_cases, 2)}%</br>\"\n",
+                "    stocktwits_sentiment += f\"Bearish {round(100*n_bear/n_cases, 2)}%\"\n",
+                "else:\n",
+                "    stocktwits_sentiment += \"No messages found\"\n",
+                "stocktwits_sentiment"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "bfb75909-b877-4b3a-82a7-21ce174a7bb4",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "snews = openbb.stocks.ba.snews_chart(symbol, external_axes=True)\n",
+                "\n",
+                "if snews:\n",
+                "    snews = snews.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "329c9e1b-e1de-4836-91fd-656cc87f7111",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ticker_data_all = openbb.stocks.load(\n",
+                "    symbol=symbol,\n",
+                "    start_date=datetime.datetime.now() - datetime.timedelta(days=5 * 12 * 21),\n",
+                ")\n",
+                "ticker_data_all[\"Returns\"] = ticker_data_all[\"Adj Close\"].pct_change()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "37743ef3-2f16-4166-bfcc-a0fe3eb959bc",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "bw_month = openbb.qa.bw(\n",
+                "    ticker_data_all,\n",
+                "    \"Returns\",\n",
+                "    symbol,\n",
+                "    yearly=False,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if bw_month:\n",
+                "    bw_month = bw_month.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "16b33868-23dc-4c77-ac00-acb452da386c",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "bw_year = openbb.qa.bw(\n",
+                "    ticker_data_all,\n",
+                "    \"Returns\",\n",
+                "    symbol,\n",
+                "    yearly=True,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if bw_year:\n",
+                "    bw_year = bw_year.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "28ce0827",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "income_df = openbb.stocks.fa.income(symbol, source=\"FinancialModelingPrep\")\n",
+                "data_df = openbb.stocks.fa.data(symbol)\n",
+                "mgmt_df = openbb.stocks.fa.mgmt(symbol)\n",
+                "if not mgmt_df.empty:\n",
+                "    mgmt_df[\"Info\"] = mgmt_df[\"Info\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
+                "    mgmt_df[\"Insider Activity\"] = mgmt_df[\"Insider Activity\"].apply(\n",
+                "        lambda x: f'<a href=\"{x}\">{x}</a>' if x != \"-\" else x\n",
+                "    )\n",
+                "try:\n",
+                "    hist_dcf = openbb.stocks.fa.dcfc(symbol)\n",
+                "except:\n",
+                "    pass\n",
+                "enterprise_df = openbb.stocks.fa.enterprise(symbol)\n",
+                "score = openbb.stocks.fa.score(symbol, years=10)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "42e289ab",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "indicators = dict(\n",
+                "    ema=dict(length=[50]),\n",
+                "    sma=dict(length=[50]),\n",
+                "    wma=dict(length=[50]),\n",
+                ")\n",
+                "\n",
+                "ma_chart = PlotlyTA.plot(ticker_data, indicators, symbol, candles=False, volume=False)\n",
+                "\n",
+                "if ma_chart:\n",
+                "    ma_chart = ma_chart.show(external=True)\n",
+                "    ma_chart = ma_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e8846a6f",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "macd_chart = openbb.ta.macd_chart(\n",
+                "    ticker_data[\"Close\"], symbol=symbol, external_axes=True\n",
+                ")\n",
+                "\n",
+                "if macd_chart:\n",
+                "    macd_chart = macd_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "48a7a427",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "cci_chart = openbb.ta.cci_chart(ticker_data, symbol=symbol, external_axes=True)\n",
+                "\n",
+                "if cci_chart:\n",
+                "    cci_chart = cci_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "6a1bd2c6",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "stoch_chart = openbb.ta.stoch_chart(ticker_data, symbol=symbol, external_axes=True)\n",
+                "\n",
+                "if stoch_chart:\n",
+                "    stoch_chart = stoch_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "2611d3c6",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "adx_chart = openbb.ta.adx_chart(ticker_data, symbol=symbol, external_axes=True)\n",
+                "\n",
+                "if adx_chart:\n",
+                "    adx_chart = adx_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "6ecb6e17",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "bbands_chart = openbb.ta.bbands_chart(ticker_data, symbol=symbol, external_axes=True)\n",
+                "\n",
+                "if bbands_chart:\n",
+                "    bbands_chart = bbands_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "07e42fdb",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ad_chart = openbb.ta.ad_chart(ticker_data, symbol=symbol, external_axes=True)\n",
+                "\n",
+                "if ad_chart:\n",
+                "    ad_chart = ad_chart.to_html()"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
+            "metadata": {},
+            "source": [
+                "## Render the report template to a file\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "body = f\"\"\"\n",
+                "<style>\n",
+                "@font-face {{\n",
+                "    font-family: \"Fira Code\";\n",
+                "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
+                "    font-weight: 400 700;\n",
+                "    font-stretch: 50%;\n",
+                "}}\n",
+                "</style>\n",
+                "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
+                "\"\"\"\n",
+                "\n",
+                "\n",
+                "img = (\n",
+                "    str(REPOSITORY_DIRECTORY)\n",
+                "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
+                ")\n",
+                "floppy_disk_img = (\n",
+                "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
+                ")\n",
+                "body += widgets.header(\n",
+                "    img,\n",
+                "    floppy_disk_img,\n",
+                "    author,\n",
+                "    report_date,\n",
+                "    report_time,\n",
+                "    report_timezone,\n",
+                "    report_title,\n",
+                ")\n",
+                "\n",
+                "body += widgets.tablinks(\n",
+                "    [\n",
+                "        \"SUMMARY\",\n",
+                "        \"Overview\",\n",
+                "        \"Fundamental Analysis\",\n",
+                "        \"Technical Analysis\",\n",
+                "        \"Behavioural Analysis\",\n",
+                "        \"Government Menu\",\n",
+                "        \"Comparison Menu\",\n",
+                "        \"Options\",\n",
+                "        \"Dark Pool and Shorts\",\n",
+                "        \"Quantitative Analysis\",\n",
+                "        \"Analyst Opinions\",\n",
+                "        \"Insider Trading\",\n",
+                "        #    \"Prediction Techniques\",\n",
+                "    ]\n",
+                ")\n",
+                "\n",
+                "htmlcode = widgets.h(3, \"KPIs\")\n",
+                "htmlcode += widgets.kpi(\n",
+                "    [last_price],\n",
+                "    [\n",
+                "        \"Last closing price is above the average price ratings of last 30 days\",\n",
+                "        \"Average price ratings of last 30 day is above last closing price\",\n",
+                "    ],\n",
+                "    avg_ratings_last_30_days,\n",
+                ")\n",
+                "htmlcode += widgets.kpi(\n",
+                "    [30, 70],\n",
+                "    [\"RSI level is oversold\", \"RSI level is normal\", \"RSI level is overbought\"],\n",
+                "    rsi_value,\n",
+                ")\n",
+                "try:\n",
+                "    htmlcode += widgets.kpi(\n",
+                "        [0],\n",
+                "        [\n",
+                "            \"The sum of last 10 insider trading (in millions) was negative\",\n",
+                "            \"The sum of last 10 insider trading (in millions) was positive\",\n",
+                "        ],\n",
+                "        last_10_insider_trading,\n",
+                "    )\n",
+                "except:\n",
+                "    pass\n",
+                "htmlcode += widgets.kpi(\n",
+                "    [-0.1, 0.1],\n",
+                "    [\n",
+                "        \"Last FinBrain sentiment is bearish\",\n",
+                "        \" Last FinBrain sentiment is neutral\",\n",
+                "        \"Last FinBrain sentiment is bullish\",\n",
+                "    ],\n",
+                "    finbrain_sentiment_val,\n",
+                ")\n",
+                "if score and score[\"Total Score\"]:\n",
+                "    htmlcode += widgets.kpi(\n",
+                "        [25, 75],\n",
+                "        [\n",
+                "            \"Buffet Score is not favourable\",\n",
+                "            \"Buffet Score is neutral\",\n",
+                "            \"Buffet Score is favourable\",\n",
+                "        ],\n",
+                "        float(score[\"Total Score\"]),\n",
+                "    )\n",
+                "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
+                "\n",
+                "htmlcode = \"\"\n",
+                "if overview:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Description\") + widgets.p(overview)])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Price Chart\") + (price_chart or \"\")])\n",
+                "\n",
+                "try:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Quote\") + quote_data.to_html()])\n",
+                "except:\n",
+                "    pass\n",
+                "\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Latest News for \" + symbol)])\n",
+                "try:\n",
+                "    for table in tables:\n",
+                "        htmlcode += widgets.row(\n",
+                "            [widgets.h(4, table[1][\"title\"]) + table[0].to_html(escape=False)]\n",
+                "        )\n",
+                "except:\n",
+                "    pass\n",
+                "\n",
+                "if not mgmt_df.empty:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, f\"Management team of {symbol}\") + mgmt_df.to_html(escape=False)]\n",
+                "    )\n",
+                "body += widgets.add_tab(\"Overview\", htmlcode)\n",
+                "\n",
+                "htmlcode = widgets.row(\n",
+                "    [widgets.h(3, \"Price Target Chart\") + (price_target_chart or \"\")]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Analyst Ratings over time\") + (ratings_over_time_chart or \"\")]\n",
+                ")\n",
+                "try:\n",
+                "    htmlcode += widgets.row([widgets.h(3, \"Analyst Ratings\") + df_analyst.to_html()])\n",
+                "except:\n",
+                "    pass\n",
+                "try:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, \"Analyst Recommendations\") + df_rating.to_html()]\n",
+                "    )\n",
+                "except:\n",
+                "    pass\n",
+                "\n",
+                "body += widgets.add_tab(\"Analyst Opinions\", htmlcode)\n",
+                "\n",
+                "try:\n",
+                "    htmlcode = widgets.row(\n",
+                "        [widgets.h(3, \"Estimates\") + df_year_estimates.head().to_html()]\n",
+                "    )\n",
+                "except:\n",
+                "    pass\n",
+                "\n",
+                "if not df_quarter_earnings.empty:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, \"Earnings\") + df_quarter_earnings.head().to_html()]\n",
+                "    )\n",
+                "if not df_quarter_revenues.empty:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, \"Revenues\") + df_quarter_revenues.head().to_html()]\n",
+                "    )\n",
+                "try:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [\n",
+                "            widgets.h(3, \"Major Institutional Shareholders\")\n",
+                "            + df_institutional_shareholders.head().to_html()\n",
+                "        ]\n",
+                "    )\n",
+                "except:\n",
+                "    pass\n",
+                "try:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, f\"Historical DCF for {symbol}\") + hist_dcf.to_html()]\n",
+                "    )\n",
+                "except:\n",
+                "    pass\n",
+                "try:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, f\"Enterprise data for {symbol}\") + enterprise_df.to_html()]\n",
+                "    )\n",
+                "except:\n",
+                "    pass\n",
+                "try:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, f\"Income Statement for {symbol}\") + income_df.to_html()]\n",
+                "    )\n",
+                "except:\n",
+                "    pass\n",
+                "try:\n",
+                "    htmlcode += widgets.row([widgets.h(3, f\"Data for {symbol}\") + data_df.to_html()])\n",
+                "except:\n",
+                "    pass\n",
+                "try:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [widgets.h(3, \"SEC filings\") + df_sec_filings.to_html(escape=False)]\n",
+                "    )\n",
+                "except:\n",
+                "    pass\n",
+                "\n",
+                "body += widgets.add_tab(\"Fundamental Analysis\", htmlcode)\n",
+                "\n",
+                "htmlcode = widgets.row([widgets.h(3, \"Put to call ratio\") + (pcr_chart or \"\")])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Option Volume for closest expiry date\") + (vol_chart or \"\")]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [\n",
+                "        widgets.h(3, \"Volume and Open Interest for closest expiry date\")\n",
+                "        + (voi_chart or \"\")\n",
+                "    ]\n",
+                ")\n",
+                "\n",
+                "body += widgets.add_tab(\"Options\", htmlcode)\n",
+                "\n",
+                "htmlcode = widgets.row([net_short_position or \"\"])\n",
+                "htmlcode += widgets.row([price_vs_short_interest or \"\"])\n",
+                "# htmlcode += widgets.row([dark_pools])\n",
+                "body += widgets.add_tab(\"Dark Pool and Shorts\", htmlcode)\n",
+                "\n",
+                "htmlcode = widgets.row(\n",
+                "    [\n",
+                "        widgets.h(3, \"Congress trading in the past 12 months for \" + symbol)\n",
+                "        + (gtrades_chart or \"\")\n",
+                "    ]\n",
+                ")\n",
+                "htmlcode += widgets.row([gov_histcont_chart or \"\"])\n",
+                "htmlcode += widgets.row([gov_contracts_chart or \"\"])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Recent Corporate Lobbying by \" + symbol)])\n",
+                "try:\n",
+                "    for _, row in df_lobbying.iterrows():\n",
+                "        amount = (\n",
+                "            \"$\" + str(int(float(row[\"Amount\"]))) if row[\"Amount\"] is not None else \"N/A\"\n",
+                "        )\n",
+                "        htmlcode += widgets.row([widgets.p(f\"{row['Date']}: {row['Client']} {amount}\")])\n",
+                "        if (row[\"Amount\"] is not None) and (row[\"Specific_Issue\"] is not None):\n",
+                "            htmlcode += widgets.row(\n",
+                "                [\n",
+                "                    widgets.p(\n",
+                "                        \"\\t\"\n",
+                "                        + row[\"Specific_Issue\"].replace(\"\\n\", \" \").replace(\"\\r\", \"\")\n",
+                "                    )\n",
+                "                ]\n",
+                "            )\n",
+                "except:\n",
+                "    pass\n",
+                "\n",
+                "body += widgets.add_tab(\"Government Menu\", htmlcode)\n",
+                "\n",
+                "htmlcode = widgets.row(\n",
+                "    [\n",
+                "        widgets.h(3, f\"Price over the past year for companies similar to {symbol}\")\n",
+                "        + (historical_similar or \"\")\n",
+                "    ]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [\n",
+                "        widgets.h(3, f\"Price correlation with similar companies for {symbol}\")\n",
+                "        + (hcorr_similar or \"\")\n",
+                "    ]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [\n",
+                "        widgets.h(3, f\"Volume over the past year for companies similar to {symbol}\")\n",
+                "        + (vol_similar or \"\")\n",
+                "    ]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [\n",
+                "        widgets.h(3, f\"Sentiment correlation with similar companies for {symbol}\")\n",
+                "        + (scorr_similar or \"\")\n",
+                "    ]\n",
+                ")\n",
+                "if isinstance(income_comparison, pd.DataFrame):\n",
+                "    htmlcode += widgets.row(\n",
+                "        [\n",
+                "            widgets.h(3, f\"Income data for similar companies to {symbol}\")\n",
+                "            + income_comparison.to_html()\n",
+                "        ]\n",
+                "    )\n",
+                "htmlcode += widgets.row(\n",
+                "    [\n",
+                "        widgets.p(\n",
+                "            \"Note that similar companies have been found using openbb.stocks.ca.similar\"\n",
+                "        )\n",
+                "    ]\n",
+                ")\n",
+                "body += widgets.add_tab(\"Comparison Menu\", htmlcode)\n",
+                "\n",
+                "htmlcode = widgets.row([widgets.h(3, f\"Moving Averages for {symbol}\") + ma_chart])\n",
+                "htmlcode += widgets.row([macd_chart or \"\"])\n",
+                "htmlcode += widgets.row([ta_rsi or \"\"])\n",
+                "htmlcode += widgets.row([stoch_chart or \"\"])\n",
+                "htmlcode += widgets.row([cci_chart or \"\"])\n",
+                "htmlcode += widgets.row([ad_chart or \"\"])\n",
+                "htmlcode += widgets.row([bbands_chart or \"\"])\n",
+                "htmlcode += widgets.row([adx_chart or \"\"])\n",
+                "body += widgets.add_tab(\"Technical Analysis\", htmlcode)\n",
+                "\n",
+                "if not df_insider.empty:\n",
+                "    htmlcode = widgets.row(\n",
+                "        [widgets.h(3, \"Last Activity\") + df_insider.head(10).to_html(col_space=\"75px\")]\n",
+                "    )\n",
+                "else:\n",
+                "    htmlcode = widgets.row(\n",
+                "        [widgets.h(3, \"Last Activity\") + widgets.p(\"No insider trading data found.\")]\n",
+                "    )\n",
+                "\n",
+                "body += widgets.add_tab(\"Insider Trading\", htmlcode)\n",
+                "\n",
+                "\n",
+                "htmlcode = widgets.row([bw_year or \"\"])\n",
+                "htmlcode += widgets.row([bw_month or \"\"])\n",
+                "body += widgets.add_tab(\"Quantitative Analysis\", htmlcode)\n",
+                "\n",
+                "\n",
+                "htmlcode = widgets.row([finbrain_sentiment or \"\"])\n",
+                "htmlcode += widgets.row([snews or \"\"])\n",
+                "htmlcode += widgets.row(\n",
+                "    [\n",
+                "        widgets.h(3, \"Interest in \" + symbol + \" based on google analytics\")\n",
+                "        + (google_mentions_chart or \"\")\n",
+                "    ]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [\n",
+                "        widgets.h(3, f\"Regions with highest interest in {symbol}\")\n",
+                "        + (google_regions_chart or \"\")\n",
+                "    ]\n",
+                ")\n",
+                "try:\n",
+                "    htmlcode += widgets.row(\n",
+                "        [\n",
+                "            widgets.h(3, f\"Top queries related to {symbol}\")\n",
+                "            + df_related_queries.to_html()\n",
+                "        ]\n",
+                "    )\n",
+                "    htmlcode += widgets.row(\n",
+                "        [\n",
+                "            widgets.h(3, f\"Top rising queries related to {symbol}\")\n",
+                "            + df_rising_queries.to_html()\n",
+                "        ]\n",
+                "    )\n",
+                "except:\n",
+                "    pass\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, f\"Stocktwits sentiment for {symbol}\") + stocktwits_sentiment]\n",
+                ")\n",
+                "body += widgets.add_tab(\"Behavioural Analysis\", htmlcode)\n",
+                "\n",
+                "body += widgets.tab_clickable_and_save_evt()\n",
+                "\n",
+                "report = widgets.html_report(\n",
+                "    title=report_name, stylesheet=widgets.html_report_stylesheet(), body=body\n",
+                ")\n",
+                "\n",
+                "# to save the results\n",
+                "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
+                "    fh.write(report)"
+            ]
+        }
+    ],
+    "metadata": {
+        "celltoolbar": "Tags",
+        "kernelspec": {
+            "display_name": "Python 3",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.10.9"
+        },
+        "vscode": {
+            "interpreter": {
+                "hash": "af870c0f9615f5bb08692efcc9bf540319fe60e6793056508a4dab09c9fa8dda"
+            }
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 5
+}
\ No newline at end of file
diff --git a/openbb_terminal/reports/templates/etf.ipynb b/openbb_terminal/reports/templates/etf.ipynb
index 470ce9b2a17..715e48c8039 100644
--- a/openbb_terminal/reports/templates/etf.ipynb
+++ b/openbb_terminal/reports/templates/etf.ipynb
@@ -1,350 +1,364 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "70ba2c8a",
-   "metadata": {},
-   "source": [
-    "## Notebook setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "driven-billion",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import warnings\n",
-    "import numpy as np\n",
-    "import datetime\n",
-    "\n",
-    "from IPython.display import HTML\n",
-    "\n",
-    "import openbb_terminal.config_terminal as cfg\n",
-    "from openbb_terminal.reports import widget_helpers as widgets\n",
-    "from openbb_terminal.sdk import openbb\n",
-    "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
-    "from openbb_terminal import OpenBBFigure, theme\n",
-    "from openbb_terminal.helper_classes import TerminalStyle\n",
-    "\n",
-    "warnings.filterwarnings(\"ignore\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from openbb_terminal.core.session.current_user import get_current_user\n",
-    "\n",
-    "user = get_current_user()\n",
-    "\n",
-    "cfg.theme = TerminalStyle(\n",
-    "    user.preferences.MPL_STYLE,\n",
-    "    user.preferences.PMF_STYLE,\n",
-    "    user.preferences.RICH_STYLE,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "36091f30",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "stylesheet = widgets.html_report_stylesheet()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "807fda4e",
-   "metadata": {},
-   "source": [
-    "## Select Ticker"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "intended-sherman",
-   "metadata": {
-    "tags": [
-     "parameters"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "# Parameters that will be replaced when calling this notebook\n",
-    "# Do not leave parameters blank as notebook will not run otherwise\n",
-    "symbol = \"VTI\"\n",
-    "report_name = \"Equity Report for VTI\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e1f87190",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ticker = symbol"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a441ddbc-d75b-4a18-84d4-e01b677674d3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "if \".\" in ticker:\n",
-    "    import sys\n",
-    "\n",
-    "    sys.exit(0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ticker_data = openbb.stocks.load(\n",
-    "    symbol=ticker, start_date=datetime.datetime.now() - datetime.timedelta(days=4 * 30)\n",
-    ")\n",
-    "ticker_data = openbb.stocks.process_candle(data=ticker_data)\n",
-    "\n",
-    "author = \"OpenBB\"\n",
-    "report_title = f\"ETF RESEARCH REPORT ON {ticker.upper()}\"\n",
-    "report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
-    "report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
-    "report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
-    "report_title, report_date, report_time, report_timezone"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2ecfcf81",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# info = openbb.etf.summary(name=ticker)\n",
-    "# info"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f8a0d747",
-   "metadata": {},
-   "source": [
-    "## Data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "39b8e77d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data = openbb.stocks.load(ticker)\n",
-    "\n",
-    "candle_chart = openbb.etf.candle(\n",
-    "    symbol=ticker,\n",
-    "    data=data,\n",
-    "    external_axes=True,\n",
-    ")\n",
-    "\n",
-    "if candle_chart:\n",
-    "    candle_chart = candle_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f751f57c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "\n",
-    "sectors = openbb.etf.weights(ticker)\n",
-    "sector_weights_formatted = {}\n",
-    "for sector_weight in sectors:\n",
-    "    sector_weights_formatted[sector_weight[\"sector\"]] = (\n",
-    "        float(sector_weight[\"weightPercentage\"].strip(\"%\")) / 100\n",
-    "    )\n",
-    "sector_weights_formatted = dict(sorted(sector_weights_formatted.items()))\n",
-    "weights_df = pd.DataFrame.from_dict(sector_weights_formatted, orient=\"index\")\n",
-    "weights_df.columns = [\"Percentage\"]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "324e2d4b-b2f6-4da3-bac4-ef785ad4e436",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "weights_chart = \"\"\n",
-    "\n",
-    "if len(weights_df[weights_df[\"Percentage\"] > 10].index) > 1:\n",
-    "    colors = theme.get_colors()\n",
-    "    fig = OpenBBFigure.create_subplots(\n",
-    "        1,\n",
-    "        3,\n",
-    "        specs=[[{\"type\": \"domain\"}, {\"type\": \"pie\", \"colspan\": 2}, None]],\n",
-    "        row_heights=[1],\n",
-    "        column_widths=[0.1, 0.8, 0.1],\n",
-    "    )\n",
-    "\n",
-    "    fig.add_pie(\n",
-    "        labels=weights_df[weights_df[\"Percentage\"] > 10].index,\n",
-    "        values=weights_df[weights_df[\"Percentage\"] > 10][\"Percentage\"],\n",
-    "        textinfo=\"label+percent\",\n",
-    "        hoverinfo=\"label+percent\",\n",
-    "        automargin=True,\n",
-    "        rotation=45,\n",
-    "        row=1,\n",
-    "        col=2,\n",
-    "    )\n",
-    "    fig.update_traces(\n",
-    "        textposition=\"outside\",\n",
-    "        textfont_size=15,\n",
-    "        marker=dict(\n",
-    "            colors=colors,\n",
-    "            line=dict(color=\"#F5EFF3\", width=0.8),\n",
-    "        ),\n",
-    "    )\n",
-    "\n",
-    "    fig.update_layout(\n",
-    "        margin=dict(t=40, b=20),\n",
-    "        title=dict(\n",
-    "            text=f\"Sector holdings of {ticker}\",\n",
-    "            y=0.98,\n",
-    "            x=0.5,\n",
-    "            xanchor=\"center\",\n",
-    "            yanchor=\"top\",\n",
-    "        ),\n",
-    "        colorway=colors,\n",
-    "        showlegend=False,\n",
-    "    )\n",
-    "\n",
-    "    weights_chart = fig.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d8bb53c1-147e-4342-af61-0d0a9cc56e59",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "holdings = openbb.etf.holdings(ticker)\n",
-    "holdings"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
-   "metadata": {},
-   "source": [
-    "## Render the report template to a file"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "body = f\"\"\"\n",
-    "<style>\n",
-    "@font-face {{\n",
-    "    font-family: \"Fira Code\";\n",
-    "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
-    "    font-weight: 400 700;\n",
-    "    font-stretch: 50%;\n",
-    "}}\n",
-    "</style>\n",
-    "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
-    "\"\"\"\n",
-    "\n",
-    "img = (\n",
-    "    str(REPOSITORY_DIRECTORY)\n",
-    "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
-    ")\n",
-    "floppy_disk_img = (\n",
-    "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
-    ")\n",
-    "body += widgets.header(\n",
-    "    img,\n",
-    "    floppy_disk_img,\n",
-    "    author,\n",
-    "    report_date,\n",
-    "    report_time,\n",
-    "    report_timezone,\n",
-    "    f\"<b>ETF RESEARCH REPORT:</b> {ticker.upper()}\",\n",
-    ")\n",
-    "\n",
-    "body += widgets.tablinks([\"SUMMARY\"])\n",
-    "\n",
-    "htmlcode = widgets.h(3, \"Summary\")\n",
-    "# htmlcode += widgets.p(info)\n",
-    "htmlcode += widgets.row([candle_chart])\n",
-    "\n",
-    "htmlcode += widgets.p(\"The ETF has the following weights distribution:\")\n",
-    "\n",
-    "htmlcode += widgets.row([weights_df.to_html()])\n",
-    "htmlcode += widgets.row([weights_chart])\n",
-    "\n",
-    "htmlcode += widgets.p(\"And has funds in the following assets:\")\n",
-    "htmlcode += widgets.row([holdings.to_html()])\n",
-    "\n",
-    "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
-    "\n",
-    "body += widgets.tab_clickable_and_save_evt()\n",
-    "\n",
-    "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
-    "\n",
-    "# to save the results\n",
-    "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
-    "    fh.write(report)"
-   ]
-  }
- ],
- "metadata": {
-  "celltoolbar": "Tags",
-  "kernelspec": {
-   "display_name": "venv",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.9"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "id": "70ba2c8a",
+            "metadata": {},
+            "source": [
+                "## Notebook setup"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "driven-billion",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import warnings\n",
+                "import numpy as np\n",
+                "import datetime\n",
+                "\n",
+                "from IPython.display import HTML\n",
+                "\n",
+                "import openbb_terminal.config_terminal as cfg\n",
+                "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
+                "from openbb_terminal import OpenBBFigure, theme\n",
+                "from openbb_terminal.helper_classes import TerminalStyle\n",
+                "\n",
+                "warnings.filterwarnings(\"ignore\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "473e83c7",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Suppressing sdk logs\n",
+                "cfg.change_logging_suppress(new_value=True)\n",
+                "\n",
+                "# Import the OpenBB SDK\n",
+                "from openbb_terminal.sdk import openbb, widgets"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from openbb_terminal.core.session.current_user import get_current_user\n",
+                "\n",
+                "user = get_current_user()\n",
+                "\n",
+                "cfg.theme = TerminalStyle(\n",
+                "    user.preferences.MPL_STYLE,\n",
+                "    user.preferences.PMF_STYLE,\n",
+                "    user.preferences.RICH_STYLE,\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "36091f30",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "stylesheet = widgets.html_report_stylesheet()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "807fda4e",
+            "metadata": {},
+            "source": [
+                "## Select Ticker"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "intended-sherman",
+            "metadata": {
+                "tags": [
+                    "parameters"
+                ]
+            },
+            "outputs": [],
+            "source": [
+                "# Parameters that will be replaced when calling this notebook\n",
+                "# Do not leave parameters blank as notebook will not run otherwise\n",
+                "symbol = \"VTI\"\n",
+                "report_name = \"Equity Report for VTI\""
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e1f87190",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ticker = symbol"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "a441ddbc-d75b-4a18-84d4-e01b677674d3",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "if \".\" in ticker:\n",
+                "    import sys\n",
+                "\n",
+                "    sys.exit(0)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ticker_data = openbb.stocks.load(\n",
+                "    symbol=ticker, start_date=datetime.datetime.now() - datetime.timedelta(days=4 * 30)\n",
+                ")\n",
+                "ticker_data = openbb.stocks.process_candle(data=ticker_data)\n",
+                "\n",
+                "author = \"OpenBB\"\n",
+                "report_title = f\"ETF RESEARCH REPORT ON {ticker.upper()}\"\n",
+                "report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
+                "report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
+                "report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
+                "report_title, report_date, report_time, report_timezone"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "2ecfcf81",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# info = openbb.etf.summary(name=ticker)\n",
+                "# info"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "f8a0d747",
+            "metadata": {},
+            "source": [
+                "## Data"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "39b8e77d",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "data = openbb.stocks.load(ticker)\n",
+                "\n",
+                "candle_chart = openbb.etf.candle(\n",
+                "    symbol=ticker,\n",
+                "    data=data,\n",
+                "    external_axes=True,\n",
+                ")\n",
+                "\n",
+                "if candle_chart:\n",
+                "    candle_chart = candle_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "f751f57c",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import pandas as pd\n",
+                "\n",
+                "sectors = openbb.etf.weights(ticker)\n",
+                "sector_weights_formatted = {}\n",
+                "for sector_weight in sectors:\n",
+                "    sector_weights_formatted[sector_weight[\"sector\"]] = (\n",
+                "        float(sector_weight[\"weightPercentage\"].strip(\"%\")) / 100\n",
+                "    )\n",
+                "sector_weights_formatted = dict(sorted(sector_weights_formatted.items()))\n",
+                "weights_df = pd.DataFrame.from_dict(sector_weights_formatted, orient=\"index\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "324e2d4b-b2f6-4da3-bac4-ef785ad4e436",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "weights_chart = \"\"\n",
+                "\n",
+                "if \"Percentage\" in weights_df.columns:\n",
+                "    weights_df.columns = [\"Percentage\"]\n",
+                "\n",
+                "if \"Percentage\" in weights_df.columns and len(weights_df[weights_df[\"Percentage\"] > 10].index) > 1:\n",
+                "    colors = theme.get_colors()\n",
+                "    fig = OpenBBFigure.create_subplots(\n",
+                "        1,\n",
+                "        3,\n",
+                "        specs=[[{\"type\": \"domain\"}, {\"type\": \"pie\", \"colspan\": 2}, None]],\n",
+                "        row_heights=[1],\n",
+                "        column_widths=[0.1, 0.8, 0.1],\n",
+                "    )\n",
+                "\n",
+                "    fig.add_pie(\n",
+                "        labels=weights_df[weights_df[\"Percentage\"] > 10].index,\n",
+                "        values=weights_df[weights_df[\"Percentage\"] > 10][\"Percentage\"],\n",
+                "        textinfo=\"label+percent\",\n",
+                "        hoverinfo=\"label+percent\",\n",
+                "        automargin=True,\n",
+                "        rotation=45,\n",
+                "        row=1,\n",
+                "        col=2,\n",
+                "    )\n",
+                "    fig.update_traces(\n",
+                "        textposition=\"outside\",\n",
+                "        textfont_size=15,\n",
+                "        marker=dict(\n",
+                "            colors=colors,\n",
+                "            line=dict(color=\"#F5EFF3\", width=0.8),\n",
+                "        ),\n",
+                "    )\n",
+                "\n",
+                "    fig.update_layout(\n",
+                "        margin=dict(t=40, b=20),\n",
+                "        title=dict(\n",
+                "            text=f\"Sector holdings of {ticker}\",\n",
+                "            y=0.98,\n",
+                "            x=0.5,\n",
+                "            xanchor=\"center\",\n",
+                "            yanchor=\"top\",\n",
+                "        ),\n",
+                "        colorway=colors,\n",
+                "        showlegend=False,\n",
+                "    )\n",
+                "\n",
+                "    weights_chart = fig.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "d8bb53c1-147e-4342-af61-0d0a9cc56e59",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "holdings = openbb.etf.holdings(ticker)\n",
+                "holdings"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
+            "metadata": {},
+            "source": [
+                "## Render the report template to a file"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "body = f\"\"\"\n",
+                "<style>\n",
+                "@font-face {{\n",
+                "    font-family: \"Fira Code\";\n",
+                "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
+                "    font-weight: 400 700;\n",
+                "    font-stretch: 50%;\n",
+                "}}\n",
+                "</style>\n",
+                "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
+                "\"\"\"\n",
+                "\n",
+                "img = (\n",
+                "    str(REPOSITORY_DIRECTORY)\n",
+                "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
+                ")\n",
+                "floppy_disk_img = (\n",
+                "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
+                ")\n",
+                "body += widgets.header(\n",
+                "    img,\n",
+                "    floppy_disk_img,\n",
+                "    author,\n",
+                "    report_date,\n",
+                "    report_time,\n",
+                "    report_timezone,\n",
+                "    f\"<b>ETF RESEARCH REPORT:</b> {ticker.upper()}\",\n",
+                ")\n",
+                "\n",
+                "body += widgets.tablinks([\"SUMMARY\"])\n",
+                "\n",
+                "htmlcode = widgets.h(3, \"Summary\")\n",
+                "# htmlcode += widgets.p(info)\n",
+                "htmlcode += widgets.row([candle_chart])\n",
+                "\n",
+                "htmlcode += widgets.p(\"The ETF has the following weights distribution:\")\n",
+                "\n",
+                "htmlcode += widgets.row([weights_df.to_html()])\n",
+                "htmlcode += widgets.row([weights_chart])\n",
+                "\n",
+                "htmlcode += widgets.p(\"And has funds in the following assets:\")\n",
+                "htmlcode += widgets.row([holdings.to_html()])\n",
+                "\n",
+                "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
+                "\n",
+                "body += widgets.tab_clickable_and_save_evt()\n",
+                "\n",
+                "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
+                "\n",
+                "# to save the results\n",
+                "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
+                "    fh.write(report)"
+            ]
+        }
+    ],
+    "metadata": {
+        "celltoolbar": "Tags",
+        "kernelspec": {
+            "display_name": "venv",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.9.13"
+        },
+        "vscode": {
+            "interpreter": {
+                "hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
+            }
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 5
+}
\ No newline at end of file
diff --git a/openbb_terminal/reports/templates/forecast.ipynb b/openbb_terminal/reports/templates/forecast.ipynb
index e9846c1b68a..23aa6f20278 100644
--- a/openbb_terminal/reports/templates/forecast.ipynb
+++ b/openbb_terminal/reports/templates/forecast.ipynb
@@ -1,311 +1,321 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "70ba2c8a",
-   "metadata": {},
-   "source": [
-    "## Notebook setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "driven-billion",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "import io\n",
-    "import warnings\n",
-    "import datetime\n",
-    "import numpy as np\n",
-    "import base64\n",
-    "\n",
-    "from IPython.display import HTML\n",
-    "\n",
-    "import openbb_terminal.config_terminal as cfg\n",
-    "from openbb_terminal.reports import widget_helpers as widgets\n",
-    "from openbb_terminal.sdk import openbb\n",
-    "from openbb_terminal.helper_classes import TerminalStyle\n",
-    "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
-    "\n",
-    "from openbb_terminal import OpenBBFigure\n",
-    "\n",
-    "\n",
-    "warnings.filterwarnings(\"ignore\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from openbb_terminal.core.session.current_user import get_current_user\n",
-    "\n",
-    "user = get_current_user()\n",
-    "\n",
-    "cfg.theme = TerminalStyle(\n",
-    "    user.preferences.MPL_STYLE,\n",
-    "    user.preferences.PMF_STYLE,\n",
-    "    user.preferences.RICH_STYLE,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f6d22d4f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "stylesheet = widgets.html_report_stylesheet()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9c3ae3e3-2b91-43a6-aa44-7b10986fd369",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def get_html(func, title, *args, **kwargs):\n",
-    "    kwargs[\"external_axes\"] = True\n",
-    "    local_fig = func(*args, **kwargs)\n",
-    "    # kwargs[\"chart\"] = True\n",
-    "    if title:\n",
-    "        local_fig.set_title(title)\n",
-    "        local_fig.set_xaxis_title(\"Lag\")\n",
-    "        local_fig.set_yaxis_title(\"Autocorrelation\")\n",
-    "\n",
-    "    return local_fig.to_html()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "807fda4e",
-   "metadata": {},
-   "source": [
-    "## Select Ticker"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "intended-sherman",
-   "metadata": {
-    "tags": [
-     "parameters"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "# Parameters that will be replaced when calling this notebook\n",
-    "# Do not leave parameters blank as notebook will not run otherwise\n",
-    "symbol = \"VTI\"\n",
-    "report_name = \"Forecast Report for VTI\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e1f87190",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ticker = symbol"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a441ddbc-d75b-4a18-84d4-e01b677674d3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "if \".\" in ticker:\n",
-    "    import sys\n",
-    "\n",
-    "    sys.exit(0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ticker_data = openbb.stocks.load(\n",
-    "    symbol=ticker, start_date=datetime.datetime.now() - datetime.timedelta(days=400)\n",
-    ")\n",
-    "\n",
-    "author = \"OpenBB\"\n",
-    "report_title = f\"FORECAST RESEARCH REPORT ON {ticker.upper()}\"\n",
-    "report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
-    "report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
-    "report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
-    "report_title, report_date, report_time, report_timezone"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f8a0d747",
-   "metadata": {},
-   "source": [
-    "## Data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cb31e9ee-e7ae-4e1b-89b4-bb6f571cfdfa",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "local_fig = openbb.stocks.candle(ticker, ticker_data, external_axes=True)\n",
-    "plot_chart = local_fig.to_html()\n",
-    "\n",
-    "# Prepare date for forecast\n",
-    "ticker_data = ticker_data.reset_index()\n",
-    "ticker_data.columns = [x.lower() for x in ticker_data.columns]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d8bb53c1-147e-4342-af61-0d0a9cc56e59",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "corr_chart = get_html(openbb.forecast.corr_chart, None, ticker_data)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "74b914a1-ed32-4a17-a943-7879bc8f00df",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "season_chart = get_html(openbb.forecast.season_chart, \"Seasonality Data\", ticker_data)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "53568c9b-aa06-4ba0-ad86-ede6732e3187",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "expo_chart = get_html(openbb.forecast.expo_chart, None, ticker_data)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0a919f67-ac9f-4b75-a3b3-102e0fbe5862",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "rnn_chart = get_html(openbb.forecast.rnn_chart, None, ticker_data)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
-   "metadata": {},
-   "source": [
-    "## Render the report template to a file"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "body = f\"\"\"\n",
-    "<style>\n",
-    "@font-face {{\n",
-    "    font-family: \"Fira Code\";\n",
-    "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
-    "    font-weight: 400 700;\n",
-    "    font-stretch: 50%;\n",
-    "}}\n",
-    "</style>\n",
-    "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
-    "\"\"\"\n",
-    "\n",
-    "\n",
-    "img = (\n",
-    "    str(REPOSITORY_DIRECTORY)\n",
-    "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
-    ")\n",
-    "floppy_disk_img = (\n",
-    "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
-    ")\n",
-    "body += widgets.header(\n",
-    "    img,\n",
-    "    floppy_disk_img,\n",
-    "    author,\n",
-    "    report_date,\n",
-    "    report_time,\n",
-    "    report_timezone,\n",
-    "    f\"<b>FORECAST REPORT ON:</b> {ticker.upper()}\",\n",
-    ")\n",
-    "\n",
-    "body += widgets.tablinks([\"SUMMARY\"])\n",
-    "\n",
-    "htmlcode = widgets.h(3, \"Summary\")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Understand the data\")])\n",
-    "htmlcode += widgets.row([ticker_data.head(10).to_html()])\n",
-    "htmlcode += widgets.row([plot_chart])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Analyzing the data\")])\n",
-    "htmlcode += widgets.row([corr_chart])\n",
-    "htmlcode += widgets.row([season_chart])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Creating predictions\")])\n",
-    "htmlcode += widgets.row([expo_chart])\n",
-    "htmlcode += widgets.row([rnn_chart])\n",
-    "\n",
-    "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
-    "body += widgets.tab_clickable_and_save_evt()\n",
-    "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
-    "\n",
-    "# to save the results\n",
-    "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
-    "    fh.write(report)"
-   ]
-  }
- ],
- "metadata": {
-  "celltoolbar": "Tags",
-  "kernelspec": {
-   "display_name": "venv",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.8"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "id": "70ba2c8a",
+            "metadata": {},
+            "source": [
+                "## Notebook setup"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "driven-billion",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import os\n",
+                "import io\n",
+                "import warnings\n",
+                "import datetime\n",
+                "import numpy as np\n",
+                "import base64\n",
+                "\n",
+                "from IPython.display import HTML\n",
+                "\n",
+                "import openbb_terminal.config_terminal as cfg\n",
+                "from openbb_terminal.helper_classes import TerminalStyle\n",
+                "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
+                "from openbb_terminal import OpenBBFigure\n",
+                "\n",
+                "warnings.filterwarnings(\"ignore\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "632bdfbc",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Suppressing sdk logs\n",
+                "cfg.change_logging_suppress(new_value=True)\n",
+                "\n",
+                "# Import the OpenBB SDK\n",
+                "from openbb_terminal.sdk import openbb, widgets"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from openbb_terminal.core.session.current_user import get_current_user\n",
+                "\n",
+                "user = get_current_user()\n",
+                "\n",
+                "cfg.theme = TerminalStyle(\n",
+                "    user.preferences.MPL_STYLE,\n",
+                "    user.preferences.PMF_STYLE,\n",
+                "    user.preferences.RICH_STYLE,\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "f6d22d4f",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "stylesheet = widgets.html_report_stylesheet()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "9c3ae3e3-2b91-43a6-aa44-7b10986fd369",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "def get_html(func, title, *args, **kwargs):\n",
+                "    kwargs[\"external_axes\"] = True\n",
+                "    local_fig = func(*args, **kwargs)\n",
+                "    # kwargs[\"chart\"] = True\n",
+                "    if title:\n",
+                "        local_fig.set_title(title)\n",
+                "        local_fig.set_xaxis_title(\"Lag\")\n",
+                "        local_fig.set_yaxis_title(\"Autocorrelation\")\n",
+                "\n",
+                "    return local_fig.to_html()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "807fda4e",
+            "metadata": {},
+            "source": [
+                "## Select Ticker"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "intended-sherman",
+            "metadata": {
+                "tags": [
+                    "parameters"
+                ]
+            },
+            "outputs": [],
+            "source": [
+                "# Parameters that will be replaced when calling this notebook\n",
+                "# Do not leave parameters blank as notebook will not run otherwise\n",
+                "symbol = \"VTI\"\n",
+                "report_name = \"Forecast Report for VTI\""
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e1f87190",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ticker = symbol"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "a441ddbc-d75b-4a18-84d4-e01b677674d3",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "if \".\" in ticker:\n",
+                "    import sys\n",
+                "\n",
+                "    sys.exit(0)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ticker_data = openbb.stocks.load(\n",
+                "    symbol=ticker, start_date=datetime.datetime.now() - datetime.timedelta(days=400)\n",
+                ")\n",
+                "\n",
+                "author = \"OpenBB\"\n",
+                "report_title = f\"FORECAST RESEARCH REPORT ON {ticker.upper()}\"\n",
+                "report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
+                "report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
+                "report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
+                "report_title, report_date, report_time, report_timezone"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "f8a0d747",
+            "metadata": {},
+            "source": [
+                "## Data"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "cb31e9ee-e7ae-4e1b-89b4-bb6f571cfdfa",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "local_fig = openbb.stocks.candle(ticker, ticker_data, external_axes=True)\n",
+                "plot_chart = local_fig.to_html()\n",
+                "\n",
+                "# Prepare date for forecast\n",
+                "ticker_data = ticker_data.reset_index()\n",
+                "ticker_data.columns = [x.lower() for x in ticker_data.columns]"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "d8bb53c1-147e-4342-af61-0d0a9cc56e59",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "corr_chart = get_html(openbb.forecast.corr_chart, None, ticker_data)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "74b914a1-ed32-4a17-a943-7879bc8f00df",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "season_chart = get_html(openbb.forecast.season_chart, \"Seasonality Data\", ticker_data)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "53568c9b-aa06-4ba0-ad86-ede6732e3187",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "expo_chart = get_html(openbb.forecast.expo_chart, None, ticker_data)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "0a919f67-ac9f-4b75-a3b3-102e0fbe5862",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "rnn_chart = get_html(openbb.forecast.rnn_chart, None, ticker_data)"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
+            "metadata": {},
+            "source": [
+                "## Render the report template to a file"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "body = f\"\"\"\n",
+                "<style>\n",
+                "@font-face {{\n",
+                "    font-family: \"Fira Code\";\n",
+                "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
+                "    font-weight: 400 700;\n",
+                "    font-stretch: 50%;\n",
+                "}}\n",
+                "</style>\n",
+                "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
+                "\"\"\"\n",
+                "\n",
+                "\n",
+                "img = (\n",
+                "    str(REPOSITORY_DIRECTORY)\n",
+                "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
+                ")\n",
+                "floppy_disk_img = (\n",
+                "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
+                ")\n",
+                "body += widgets.header(\n",
+                "    img,\n",
+                "    floppy_disk_img,\n",
+                "    author,\n",
+                "    report_date,\n",
+                "    report_time,\n",
+                "    report_timezone,\n",
+                "    f\"<b>FORECAST REPORT ON:</b> {ticker.upper()}\",\n",
+                ")\n",
+                "\n",
+                "body += widgets.tablinks([\"SUMMARY\"])\n",
+                "\n",
+                "htmlcode = widgets.h(3, \"Summary\")\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Understand the data\")])\n",
+                "htmlcode += widgets.row([ticker_data.head(10).to_html()])\n",
+                "htmlcode += widgets.row([plot_chart])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Analyzing the data\")])\n",
+                "htmlcode += widgets.row([corr_chart])\n",
+                "htmlcode += widgets.row([season_chart])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Creating predictions\")])\n",
+                "htmlcode += widgets.row([expo_chart])\n",
+                "htmlcode += widgets.row([rnn_chart])\n",
+                "\n",
+                "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
+                "body += widgets.tab_clickable_and_save_evt()\n",
+                "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
+                "\n",
+                "# to save the results\n",
+                "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
+                "    fh.write(report)"
+            ]
+        }
+    ],
+    "metadata": {
+        "celltoolbar": "Tags",
+        "kernelspec": {
+            "display_name": "venv",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.10.8"
+        },
+        "vscode": {
+            "interpreter": {
+                "hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
+            }
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 5
+}
\ No newline at end of file
diff --git a/openbb_terminal/reports/templates/forex.ipynb b/openbb_terminal/reports/templates/forex.ipynb
index e8eb28a56ae..53a59328b52 100644
--- a/openbb_terminal/reports/templates/forex.ipynb
+++ b/openbb_terminal/reports/templates/forex.ipynb
@@ -1,652 +1,664 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "70ba2c8a",
-   "metadata": {},
-   "source": [
-    "## Notebook setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "driven-billion",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "import io\n",
-    "import warnings\n",
-    "import datetime\n",
-    "import numpy as np\n",
-    "import base64\n",
-    "import pandas as pd\n",
-    "\n",
-    "from IPython.display import HTML\n",
-    "\n",
-    "import openbb_terminal.config_terminal as cfg\n",
-    "from openbb_terminal.sdk import widgets\n",
-    "from openbb_terminal.sdk import openbb\n",
-    "from openbb_terminal.helper_classes import TerminalStyle\n",
-    "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
-    "from openbb_terminal import OpenBBFigure\n",
-    "\n",
-    "warnings.filterwarnings(\"ignore\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from openbb_terminal.core.session.current_user import get_current_user\n",
-    "\n",
-    "user = get_current_user()\n",
-    "\n",
-    "cfg.theme = TerminalStyle(\n",
-    "    user.preferences.MPL_STYLE,\n",
-    "    user.preferences.PMF_STYLE,\n",
-    "    user.preferences.RICH_STYLE,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4b002bfd",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "stylesheet = widgets.html_report_stylesheet()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "807fda4e",
-   "metadata": {},
-   "source": [
-    "## Select Ticker"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "intended-sherman",
-   "metadata": {
-    "tags": [
-     "parameters"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "# Parameters that will be replaced when calling this notebook\n",
-    "# Do not leave parameters blank as notebook will not run otherwise\n",
-    "symbol = \"EURUSD\"\n",
-    "report_name = \"Forex Report for EURUSD\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "613cea1d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ticker = symbol"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d4897334",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "author = \"\"\n",
-    "report_title = f\"INVESTMENT RESEARCH REPORT ON {ticker.upper()}\"\n",
-    "report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
-    "report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
-    "report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
-    "report_title, report_date, report_time, report_timezone"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "07d09ce8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from_symbol = ticker[:3]\n",
-    "to_symbol = ticker[3:]\n",
-    "last_year = datetime.datetime.now() - datetime.timedelta(days=365)\n",
-    "\n",
-    "ticker_data = openbb.forex.load(\n",
-    "    from_symbol=from_symbol,\n",
-    "    to_symbol=to_symbol,\n",
-    "    start_date=last_year.strftime(\"%Y-%m-%d\"),\n",
-    "    interval=\"1day\",\n",
-    "    resolution=\"d\",\n",
-    ")\n",
-    "\n",
-    "# 1 year historical data\n",
-    "ticker_data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "88af0fbe",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "last_year = datetime.datetime.now() - datetime.timedelta(days=365)\n",
-    "\n",
-    "ticker_data_interval_1month = openbb.forex.load(\n",
-    "    from_symbol=from_symbol,\n",
-    "    to_symbol=to_symbol,\n",
-    "    start_date=last_year.strftime(\"%Y-%m-%d\"),\n",
-    "    interval=\"1month\",\n",
-    "    resolution=\"d\",\n",
-    ")\n",
-    "ticker_data_interval_1month = ticker_data_interval_1month.drop(columns=\"Volume\")\n",
-    "ticker_data_interval_1month"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f8a0d747",
-   "metadata": {},
-   "source": [
-    "## Data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "709a2a7e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# candle\n",
-    "\n",
-    "candle = openbb.forex.candle(\n",
-    "    data=ticker_data,\n",
-    "    to_symbol=to_symbol,\n",
-    "    from_symbol=from_symbol,\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "05f54519",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# candle graph with moving averages 7/14 and 30/60\n",
-    "candle_ma_7_14 = openbb.forex.candle(\n",
-    "    data=ticker_data,\n",
-    "    to_symbol=to_symbol,\n",
-    "    from_symbol=from_symbol,\n",
-    "    ma=[7, 14],\n",
-    "    external_axes=True,\n",
-    ").to_html()\n",
-    "\n",
-    "candle_ma_30_60 = openbb.forex.candle(\n",
-    "    data=ticker_data,\n",
-    "    to_symbol=to_symbol,\n",
-    "    from_symbol=from_symbol,\n",
-    "    ma=[30, 60],\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fc17a601",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fwd = openbb.forex.fwd(\n",
-    "    to_symbol=to_symbol,\n",
-    "    from_symbol=from_symbol,\n",
-    ")\n",
-    "\n",
-    "# forward rates\n",
-    "fwd"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "6c852082",
-   "metadata": {},
-   "source": [
-    "# Technical analysis"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4ff6345d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# simple moving average\n",
-    "ticker_data.index.names = [\"date\"]\n",
-    "\n",
-    "sma = openbb.ta.ma_chart(\n",
-    "    data=ticker_data[\"Close\"],\n",
-    "    ma_type=\"SMA\",\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5d5089fa",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# exponential moving average\n",
-    "ema = openbb.ta.ma_chart(\n",
-    "    data=ticker_data[\"Close\"],\n",
-    "    ma_type=\"EMA\",\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5facfbf4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# zero lag exponential moving average\n",
-    "\n",
-    "zlma = openbb.ta.ma_chart(\n",
-    "    data=ticker_data[\"Close\"],\n",
-    "    ma_type=\"ZLMA\",\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "df54f7ad",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# commodity channel index\n",
-    "\n",
-    "cci = openbb.ta.cci_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f53469eb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# moving average convergence/divergence\n",
-    "\n",
-    "macd = openbb.ta.macd_chart(\n",
-    "    data=ticker_data[\"Adj Close\"],\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dd79e6b6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# fisher transform\n",
-    "\n",
-    "fisher = openbb.ta.fisher_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b699e61f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# aroon indicator\n",
-    "\n",
-    "aroon = openbb.ta.aroon_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "79401027",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# bollinger bands\n",
-    "\n",
-    "bbands = openbb.ta.bbands_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0b5e2949",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# fibonacci retracement\n",
-    "\n",
-    "fib = openbb.ta.fib_chart(\n",
-    "    data=ticker_data,\n",
-    "    symbol=ticker,\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e6f6ce8a",
-   "metadata": {},
-   "source": [
-    "# Quantitative Analysis"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e77b373b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# summary\n",
-    "\n",
-    "summary = openbb.qa.summary(data=ticker_data)\n",
-    "summary"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3ecfc93e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# normality statistics and tests\n",
-    "\n",
-    "normality = openbb.qa.normality(\n",
-    "    data=ticker_data[\"Close\"],\n",
-    ")\n",
-    "normality"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "66a7dccc",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# rolling mean and std deviation of prices\n",
-    "\n",
-    "rolling = openbb.qa.rolling_chart(\n",
-    "    symbol=ticker,\n",
-    "    data=ticker_data,\n",
-    "    target=\"Close\",\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d6b43dd7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# rolling kurtosis of distribution of prices\n",
-    "\n",
-    "kurtosis = openbb.qa.kurtosis_chart(\n",
-    "    symbol=ticker,\n",
-    "    data=ticker_data,\n",
-    "    target=\"Close\",\n",
-    "    external_axes=True,\n",
-    ").to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fc31624a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# latest news\n",
-    "\n",
-    "news = openbb.news(term=ticker).head(10)\n",
-    "\n",
-    "news[\"published\"] = pd.to_datetime(news[\"published\"])\n",
-    "news[\"published\"] = pd.to_datetime(\n",
-    "    news[\"published\"], format=\"%d/%m/%y %H:%M:%S\"\n",
-    ").dt.strftime(\"%Y-%m-%d\")\n",
-    "news = news[[\"published\", \"title\", \"link\"]]\n",
-    "\n",
-    "news[\"link\"] = news[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
-    "news = news.set_index(\"published\")\n",
-    "news.sort_index()\n",
-    "news"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
-   "metadata": {},
-   "source": [
-    "## Render the report template to a file"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "body = f\"\"\"\n",
-    "<style>\n",
-    "@font-face {{\n",
-    "    font-family: \"Fira Code\";\n",
-    "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
-    "    font-weight: 400 700;\n",
-    "    font-stretch: 50%;\n",
-    "}}\n",
-    "</style>\n",
-    "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
-    "\"\"\"\n",
-    "\n",
-    "\n",
-    "img = (\n",
-    "    str(REPOSITORY_DIRECTORY)\n",
-    "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
-    ")\n",
-    "floppy_disk_img = (\n",
-    "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
-    ")\n",
-    "body += widgets.header(\n",
-    "    img,\n",
-    "    floppy_disk_img,\n",
-    "    author,\n",
-    "    report_date,\n",
-    "    report_time,\n",
-    "    report_timezone,\n",
-    "    f\"<b>INVESTMENT RESEARCH REPORT:</b> {ticker}\",\n",
-    ")\n",
-    "\n",
-    "body += widgets.tablinks(\n",
-    "    [\n",
-    "        \"SUMMARY\",\n",
-    "        \"Overview\",\n",
-    "        \"Technical Analysis\",\n",
-    "        \"Quantitative Analysis\",\n",
-    "    ]\n",
-    ")\n",
-    "\n",
-    "comment = \"Every analysis displayed considered every day data YTD\"\n",
-    "\n",
-    "\n",
-    "# TODO: add KPIs\n",
-    "\n",
-    "htmlcode = \"\"\n",
-    "\n",
-    "# htmlcode += widgets.h(3, \"KPIs\")\n",
-    "# htmlcode += widgets.kpi(\n",
-    "#     [30, 70],\n",
-    "#     [\"RSI level is oversold\", \"RSI level is normal\", \"RSI level is overbought\"],\n",
-    "#     999,\n",
-    "# )\n",
-    "# htmlcode += widgets.kpi(\n",
-    "#     [0],\n",
-    "#     [\n",
-    "#         \"The sum of last 10 insider trading (in millions) was negative\",\n",
-    "#         \"The sum of last 10 insider trading (in millions) was positive\",\n",
-    "#     ],\n",
-    "#     999,\n",
-    "# )\n",
-    "# htmlcode += widgets.kpi(\n",
-    "#     [-0.1, 0.1],\n",
-    "#     [\n",
-    "#         \"Last FinBrain sentiment is bearish\",\n",
-    "#         \"Last FinBrain sentiment is neutral\",\n",
-    "#         \"Last FinBrain sentiment is bullish\",\n",
-    "#     ],\n",
-    "#     999,\n",
-    "# )\n",
-    "\n",
-    "# Summary tab\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Latest news\") + news.to_html(escape=False)])\n",
-    "htmlcode += widgets.row(\n",
-    "    [\n",
-    "        widgets.h(3, \"One year historical data for 1st day each month\")\n",
-    "        + ticker_data_interval_1month.to_html()\n",
-    "    ]\n",
-    ")\n",
-    "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
-    "\n",
-    "# Overview tab\n",
-    "htmlcode = \"\"\n",
-    "htmlcode = widgets.row([widgets.h(3, \"Candlestick chart\")])\n",
-    "htmlcode += widgets.row([candle])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Candlestick chart with moving averages 7 and 14\")]\n",
-    ")\n",
-    "htmlcode += widgets.row([candle_ma_7_14])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Candlestick chart with moving averages 30 and 60\")]\n",
-    ")\n",
-    "htmlcode += widgets.row([candle_ma_30_60])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Forward rates\")])\n",
-    "htmlcode += widgets.row([fwd.to_html()])\n",
-    "body += widgets.add_tab(\"Overview\", htmlcode, True, comment)\n",
-    "\n",
-    "# Technical Analysis tab\n",
-    "htmlcode = widgets.row([widgets.h(3, \"Simple moving average\")])\n",
-    "htmlcode += widgets.row([sma])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Exponential moving average\")])\n",
-    "htmlcode += widgets.row([ema])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Zero lag exponential moving average\")])\n",
-    "htmlcode += widgets.row([zlma])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Commodity channel index\")])\n",
-    "htmlcode += widgets.row([cci])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Moving average convergence/divergence\")])\n",
-    "htmlcode += widgets.row([macd])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Fisher transform\")])\n",
-    "htmlcode += widgets.row([fisher])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Aroon indicator\")])\n",
-    "htmlcode += widgets.row([aroon])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Bollinger bands\")])\n",
-    "htmlcode += widgets.row([bbands])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Fibonacci retracement\")])\n",
-    "htmlcode += widgets.row([fib])\n",
-    "body += widgets.add_tab(\"Technical Analysis\", htmlcode, True, comment)\n",
-    "\n",
-    "# Quantitative Analysis tab\n",
-    "htmlcode = widgets.row([widgets.h(3, \"Summary\") + summary.to_html()])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Normality statistics and tests\") + normality.to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Rolling mean and std deviation of prices\")])\n",
-    "htmlcode += widgets.row([rolling])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Rolling kurtosis of distribution of prices\")])\n",
-    "htmlcode += widgets.row([kurtosis])\n",
-    "body += widgets.add_tab(\"Quantitative Analysis\", htmlcode, True, comment)\n",
-    "\n",
-    "body += widgets.tab_clickable_and_save_evt()\n",
-    "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
-    "\n",
-    "# # to save the results\n",
-    "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
-    "    fh.write(report)"
-   ]
-  }
- ],
- "metadata": {
-  "celltoolbar": "Tags",
-  "kernelspec": {
-   "display_name": "venv",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.8"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "id": "70ba2c8a",
+            "metadata": {},
+            "source": [
+                "## Notebook setup"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "driven-billion",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import os\n",
+                "import io\n",
+                "import warnings\n",
+                "import datetime\n",
+                "import numpy as np\n",
+                "import base64\n",
+                "import pandas as pd\n",
+                "\n",
+                "from IPython.display import HTML\n",
+                "\n",
+                "import openbb_terminal.config_terminal as cfg\n",
+                "from openbb_terminal.helper_classes import TerminalStyle\n",
+                "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
+                "from openbb_terminal import OpenBBFigure\n",
+                "\n",
+                "warnings.filterwarnings(\"ignore\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "03a286e7",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Suppressing sdk logs\n",
+                "cfg.change_logging_suppress(new_value=True)\n",
+                "\n",
+                "# Import the OpenBB SDK\n",
+                "from openbb_terminal.sdk import openbb, widgets"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from openbb_terminal.core.session.current_user import get_current_user\n",
+                "\n",
+                "user = get_current_user()\n",
+                "\n",
+                "cfg.theme = TerminalStyle(\n",
+                "    user.preferences.MPL_STYLE,\n",
+                "    user.preferences.PMF_STYLE,\n",
+                "    user.preferences.RICH_STYLE,\n",
+                ")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "4b002bfd",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "stylesheet = widgets.html_report_stylesheet()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "807fda4e",
+            "metadata": {},
+            "source": [
+                "## Select Ticker"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "intended-sherman",
+            "metadata": {
+                "tags": [
+                    "parameters"
+                ]
+            },
+            "outputs": [],
+            "source": [
+                "# Parameters that will be replaced when calling this notebook\n",
+                "# Do not leave parameters blank as notebook will not run otherwise\n",
+                "symbol = \"EURUSD\"\n",
+                "report_name = \"Forex Report for EURUSD\""
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "613cea1d",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "ticker = symbol"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "d4897334",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "author = \"\"\n",
+                "report_title = f\"INVESTMENT RESEARCH REPORT ON {ticker.upper()}\"\n",
+                "report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
+                "report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
+                "report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
+                "report_title, report_date, report_time, report_timezone"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "07d09ce8",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from_symbol = ticker[:3]\n",
+                "to_symbol = ticker[3:]\n",
+                "last_year = datetime.datetime.now() - datetime.timedelta(days=365)\n",
+                "\n",
+                "ticker_data = openbb.forex.load(\n",
+                "    from_symbol=from_symbol,\n",
+                "    to_symbol=to_symbol,\n",
+                "    start_date=last_year.strftime(\"%Y-%m-%d\"),\n",
+                "    interval=\"1day\",\n",
+                "    resolution=\"d\",\n",
+                ")\n",
+                "\n",
+                "# 1 year historical data\n",
+                "ticker_data"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "88af0fbe",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "last_year = datetime.datetime.now() - datetime.timedelta(days=365)\n",
+                "\n",
+                "ticker_data_interval_1month = openbb.forex.load(\n",
+                "    from_symbol=from_symbol,\n",
+                "    to_symbol=to_symbol,\n",
+                "    start_date=last_year.strftime(\"%Y-%m-%d\"),\n",
+                "    interval=\"1month\",\n",
+                "    resolution=\"d\",\n",
+                ")\n",
+                "ticker_data_interval_1month = ticker_data_interval_1month.drop(columns=\"Volume\")\n",
+                "ticker_data_interval_1month"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "f8a0d747",
+            "metadata": {},
+            "source": [
+                "## Data"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "709a2a7e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# candle\n",
+                "\n",
+                "candle = openbb.forex.candle(\n",
+                "    data=ticker_data,\n",
+                "    to_symbol=to_symbol,\n",
+                "    from_symbol=from_symbol,\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "05f54519",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# candle graph with moving averages 7/14 and 30/60\n",
+                "candle_ma_7_14 = openbb.forex.candle(\n",
+                "    data=ticker_data,\n",
+                "    to_symbol=to_symbol,\n",
+                "    from_symbol=from_symbol,\n",
+                "    ma=[7, 14],\n",
+                "    external_axes=True,\n",
+                ").to_html()\n",
+                "\n",
+                "candle_ma_30_60 = openbb.forex.candle(\n",
+                "    data=ticker_data,\n",
+                "    to_symbol=to_symbol,\n",
+                "    from_symbol=from_symbol,\n",
+                "    ma=[30, 60],\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "fc17a601",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "fwd = openbb.forex.fwd(\n",
+                "    to_symbol=to_symbol,\n",
+                "    from_symbol=from_symbol,\n",
+                ")\n",
+                "\n",
+                "# forward rates\n",
+                "fwd"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "6c852082",
+            "metadata": {},
+            "source": [
+                "# Technical analysis"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "4ff6345d",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# simple moving average\n",
+                "ticker_data.index.names = [\"date\"]\n",
+                "\n",
+                "sma = openbb.ta.ma_chart(\n",
+                "    data=ticker_data[\"Close\"],\n",
+                "    ma_type=\"SMA\",\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "5d5089fa",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# exponential moving average\n",
+                "ema = openbb.ta.ma_chart(\n",
+                "    data=ticker_data[\"Close\"],\n",
+                "    ma_type=\"EMA\",\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "5facfbf4",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# zero lag exponential moving average\n",
+                "\n",
+                "zlma = openbb.ta.ma_chart(\n",
+                "    data=ticker_data[\"Close\"],\n",
+                "    ma_type=\"ZLMA\",\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "df54f7ad",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# commodity channel index\n",
+                "\n",
+                "cci = openbb.ta.cci_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "f53469eb",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# moving average convergence/divergence\n",
+                "\n",
+                "macd = openbb.ta.macd_chart(\n",
+                "    data=ticker_data[\"Adj Close\"],\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "dd79e6b6",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# fisher transform\n",
+                "\n",
+                "fisher = openbb.ta.fisher_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "b699e61f",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# aroon indicator\n",
+                "\n",
+                "aroon = openbb.ta.aroon_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "79401027",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# bollinger bands\n",
+                "\n",
+                "bbands = openbb.ta.bbands_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "0b5e2949",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# fibonacci retracement\n",
+                "\n",
+                "fib = openbb.ta.fib_chart(\n",
+                "    data=ticker_data,\n",
+                "    symbol=ticker,\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "e6f6ce8a",
+            "metadata": {},
+            "source": [
+                "# Quantitative Analysis"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "e77b373b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# summary\n",
+                "\n",
+                "summary = openbb.qa.summary(data=ticker_data)\n",
+                "summary"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "3ecfc93e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# normality statistics and tests\n",
+                "\n",
+                "normality = openbb.qa.normality(\n",
+                "    data=ticker_data[\"Close\"],\n",
+                ")\n",
+                "normality"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "66a7dccc",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# rolling mean and std deviation of prices\n",
+                "\n",
+                "rolling = openbb.qa.rolling_chart(\n",
+                "    symbol=ticker,\n",
+                "    data=ticker_data,\n",
+                "    target=\"Close\",\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "d6b43dd7",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# rolling kurtosis of distribution of prices\n",
+                "\n",
+                "kurtosis = openbb.qa.kurtosis_chart(\n",
+                "    symbol=ticker,\n",
+                "    data=ticker_data,\n",
+                "    target=\"Close\",\n",
+                "    external_axes=True,\n",
+                ").to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "fc31624a",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# latest news\n",
+                "\n",
+                "news = openbb.news(term=ticker).head(10)\n",
+                "\n",
+                "news[\"published\"] = pd.to_datetime(news[\"published\"])\n",
+                "news[\"published\"] = pd.to_datetime(\n",
+                "    news[\"published\"], format=\"%d/%m/%y %H:%M:%S\"\n",
+                ").dt.strftime(\"%Y-%m-%d\")\n",
+                "news = news[[\"published\", \"title\", \"link\"]]\n",
+                "\n",
+                "news[\"link\"] = news[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
+                "news = news.set_index(\"published\")\n",
+                "news.sort_index()\n",
+                "news"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
+            "metadata": {},
+            "source": [
+                "## Render the report template to a file"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "body = f\"\"\"\n",
+                "<style>\n",
+                "@font-face {{\n",
+                "    font-family: \"Fira Code\";\n",
+                "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
+                "    font-weight: 400 700;\n",
+                "    font-stretch: 50%;\n",
+                "}}\n",
+                "</style>\n",
+                "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
+                "\"\"\"\n",
+                "\n",
+                "\n",
+                "img = (\n",
+                "    str(REPOSITORY_DIRECTORY)\n",
+                "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
+                ")\n",
+                "floppy_disk_img = (\n",
+                "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
+                ")\n",
+                "body += widgets.header(\n",
+                "    img,\n",
+                "    floppy_disk_img,\n",
+                "    author,\n",
+                "    report_date,\n",
+                "    report_time,\n",
+                "    report_timezone,\n",
+                "    f\"<b>INVESTMENT RESEARCH REPORT:</b> {ticker}\",\n",
+                ")\n",
+                "\n",
+                "body += widgets.tablinks(\n",
+                "    [\n",
+                "        \"SUMMARY\",\n",
+                "        \"Overview\",\n",
+                "        \"Technical Analysis\",\n",
+                "        \"Quantitative Analysis\",\n",
+                "    ]\n",
+                ")\n",
+                "\n",
+                "comment = \"Every analysis displayed considered every day data YTD\"\n",
+                "\n",
+                "\n",
+                "# TODO: add KPIs\n",
+                "\n",
+                "htmlcode = \"\"\n",
+                "\n",
+                "# htmlcode += widgets.h(3, \"KPIs\")\n",
+                "# htmlcode += widgets.kpi(\n",
+                "#     [30, 70],\n",
+                "#     [\"RSI level is oversold\", \"RSI level is normal\", \"RSI level is overbought\"],\n",
+                "#     999,\n",
+                "# )\n",
+                "# htmlcode += widgets.kpi(\n",
+                "#     [0],\n",
+                "#     [\n",
+                "#         \"The sum of last 10 insider trading (in millions) was negative\",\n",
+                "#         \"The sum of last 10 insider trading (in millions) was positive\",\n",
+                "#     ],\n",
+                "#     999,\n",
+                "# )\n",
+                "# htmlcode += widgets.kpi(\n",
+                "#     [-0.1, 0.1],\n",
+                "#     [\n",
+                "#         \"Last FinBrain sentiment is bearish\",\n",
+                "#         \"Last FinBrain sentiment is neutral\",\n",
+                "#         \"Last FinBrain sentiment is bullish\",\n",
+                "#     ],\n",
+                "#     999,\n",
+                "# )\n",
+                "\n",
+                "# Summary tab\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Latest news\") + news.to_html(escape=False)])\n",
+                "htmlcode += widgets.row(\n",
+                "    [\n",
+                "        widgets.h(3, \"One year historical data for 1st day each month\")\n",
+                "        + ticker_data_interval_1month.to_html()\n",
+                "    ]\n",
+                ")\n",
+                "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
+                "\n",
+                "# Overview tab\n",
+                "htmlcode = \"\"\n",
+                "htmlcode = widgets.row([widgets.h(3, \"Candlestick chart\")])\n",
+                "htmlcode += widgets.row([candle])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Candlestick chart with moving averages 7 and 14\")]\n",
+                ")\n",
+                "htmlcode += widgets.row([candle_ma_7_14])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Candlestick chart with moving averages 30 and 60\")]\n",
+                ")\n",
+                "htmlcode += widgets.row([candle_ma_30_60])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Forward rates\")])\n",
+                "htmlcode += widgets.row([fwd.to_html()])\n",
+                "body += widgets.add_tab(\"Overview\", htmlcode, True, comment)\n",
+                "\n",
+                "# Technical Analysis tab\n",
+                "htmlcode = widgets.row([widgets.h(3, \"Simple moving average\")])\n",
+                "htmlcode += widgets.row([sma])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Exponential moving average\")])\n",
+                "htmlcode += widgets.row([ema])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Zero lag exponential moving average\")])\n",
+                "htmlcode += widgets.row([zlma])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Commodity channel index\")])\n",
+                "htmlcode += widgets.row([cci])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Moving average convergence/divergence\")])\n",
+                "htmlcode += widgets.row([macd])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Fisher transform\")])\n",
+                "htmlcode += widgets.row([fisher])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Aroon indicator\")])\n",
+                "htmlcode += widgets.row([aroon])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Bollinger bands\")])\n",
+                "htmlcode += widgets.row([bbands])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Fibonacci retracement\")])\n",
+                "htmlcode += widgets.row([fib])\n",
+                "body += widgets.add_tab(\"Technical Analysis\", htmlcode, True, comment)\n",
+                "\n",
+                "# Quantitative Analysis tab\n",
+                "htmlcode = widgets.row([widgets.h(3, \"Summary\") + summary.to_html()])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Normality statistics and tests\") + normality.to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Rolling mean and std deviation of prices\")])\n",
+                "htmlcode += widgets.row([rolling])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Rolling kurtosis of distribution of prices\")])\n",
+                "htmlcode += widgets.row([kurtosis])\n",
+                "body += widgets.add_tab(\"Quantitative Analysis\", htmlcode, True, comment)\n",
+                "\n",
+                "body += widgets.tab_clickable_and_save_evt()\n",
+                "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
+                "\n",
+                "# # to save the results\n",
+                "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
+                "    fh.write(report)"
+            ]
+        }
+    ],
+    "metadata": {
+        "celltoolbar": "Tags",
+        "kernelspec": {
+            "display_name": "venv",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.10.8"
+        },
+        "vscode": {
+            "interpreter": {
+                "hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
+            }
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 5
+}
\ No newline at end of file
diff --git a/openbb_terminal/reports/templates/portfolio.ipynb b/openbb_terminal/reports/templates/portfolio.ipynb
index 9ea982e03c5..9d16c8b95d4 100644
--- a/openbb_terminal/reports/templates/portfolio.ipynb
+++ b/openbb_terminal/reports/templates/portfolio.ipynb
@@ -1,511 +1,522 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "70ba2c8a",
-   "metadata": {},
-   "source": [
-    "## Notebook setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "driven-billion",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "import io\n",
-    "import warnings\n",
-    "import datetime\n",
-    "import numpy as np\n",
-    "import base64\n",
-    "import pytz\n",
-    "import pandas as pd\n",
-    "\n",
-    "from IPython.display import HTML\n",
-    "\n",
-    "import openbb_terminal.config_terminal as cfg\n",
-    "from openbb_terminal.reports import widget_helpers as widgets\n",
-    "from openbb_terminal.sdk import openbb\n",
-    "from openbb_terminal.sdk import helper\n",
-    "from openbb_terminal.helper_classes import TerminalStyle\n",
-    "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
-    "from openbb_terminal import OpenBBFigure\n",
-    "\n",
-    "warnings.filterwarnings(\"ignore\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "62d3ea0e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from openbb_terminal.core.session.current_user import get_current_user\n",
-    "\n",
-    "user = get_current_user()\n",
-    "\n",
-    "cfg.theme = TerminalStyle(\n",
-    "    user.preferences.MPL_STYLE,\n",
-    "    user.preferences.PMF_STYLE,\n",
-    "    user.preferences.RICH_STYLE,\n",
-    ")\n",
-    "\n",
-    "USER_PORTFOLIO_DATA_DIRECTORY = user.preferences.USER_PORTFOLIO_DATA_DIRECTORY"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4391e874",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "stylesheet = widgets.html_report_stylesheet()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "8136bf90",
-   "metadata": {},
-   "source": [
-    "### Header"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "theme = TerminalStyle(\"light\", \"light\", \"light\")\n",
-    "stylesheet = widgets.html_report_stylesheet()\n",
-    "user_time_zone = pytz.timezone(helper.get_user_timezone())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "daef64ec",
-   "metadata": {
-    "tags": [
-     "parameters"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "# Parameters that will be replaced when calling this notebook\n",
-    "# Do not leave parameters blank as notebook will not run otherwise\n",
-    "transactions = \"holdings_example.xlsx\"\n",
-    "report_name = \"Portfolio Report\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dd441a31",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "file_0 = (\n",
-    "    str(REPOSITORY_DIRECTORY)\n",
-    "    + \"/openbb_terminal/miscellaneous/portfolio/\"\n",
-    "    + transactions\n",
-    ")\n",
-    "file_1 = str(USER_PORTFOLIO_DATA_DIRECTORY) + \"/holdings/\" + transactions\n",
-    "\n",
-    "if os.path.isfile(file_0):\n",
-    "    transactions_path = file_0\n",
-    "elif os.path.isfile(file_1):\n",
-    "    transactions_path = file_1\n",
-    "else:\n",
-    "    raise FileNotFoundError(\"File not found: \" + transactions)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "_, transactions_file = os.path.split(transactions_path)\n",
-    "report_title = f\"Portfolio report for {transactions_file}\"\n",
-    "report_date = pd.Timestamp.now(tz=user_time_zone).strftime(\"%d %B, %Y\")\n",
-    "report_time = pd.Timestamp.now(tz=user_time_zone).strftime(\"%H:%M\")\n",
-    "report_timezone = pd.Timestamp.now(tz=user_time_zone).tzinfo\n",
-    "report_title, report_date, report_time, report_timezone"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "9363f19a",
-   "metadata": {},
-   "source": [
-    "## Data"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "eb3dbd48",
-   "metadata": {},
-   "source": [
-    "Loading"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b139556d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "try:\n",
-    "    P = openbb.portfolio.load(transactions_path)\n",
-    "    openbb.portfolio.show(P)\n",
-    "except Exception as e:\n",
-    "    raise Exception(\"Failed to load the transactions.\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "af24ed22",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "beta_chart = openbb.portfolio.rbeta_chart(P, external_axes=True)\n",
-    "\n",
-    "if beta_chart:\n",
-    "    beta_chart = beta_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "636c743d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sharpe_chart = openbb.portfolio.rsharpe_chart(P, external_axes=True)\n",
-    "\n",
-    "if sharpe_chart:\n",
-    "    sharpe_chart = sharpe_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ae0d9381",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "volatility_chart = openbb.portfolio.rvol_chart(P, external_axes=True)\n",
-    "\n",
-    "if volatility_chart:\n",
-    "    volatility_chart = volatility_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7e5e6fff",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sortino_chart = openbb.portfolio.rsort_chart(P, external_axes=True)\n",
-    "\n",
-    "if sortino_chart:\n",
-    "    sortino_chart = sortino_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3567b0ca",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "maxdd_chart = openbb.portfolio.maxdd_chart(P, external_axes=True)\n",
-    "\n",
-    "if maxdd_chart:\n",
-    "    maxdd_chart = maxdd_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5dbcc1eb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "country_allocation = openbb.portfolio.alloc.countries(P)\n",
-    "\n",
-    "country_allocation[\"Portfolio\"] = (country_allocation[\"Portfolio\"] * 100).map(\n",
-    "    \"{:.3}%\".format\n",
-    ")\n",
-    "country_allocation[\"Benchmark\"] = (country_allocation[\"Benchmark\"] * 100).map(\n",
-    "    \"{:.3}%\".format\n",
-    ")\n",
-    "country_allocation[\"Difference\"] = (country_allocation[\"Difference\"] * 100).map(\n",
-    "    \"{:.3}pp\".format\n",
-    ")\n",
-    "\n",
-    "country_allocation"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8e1a67a6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sector_allocation = openbb.portfolio.alloc.sectors(P)\n",
-    "\n",
-    "sector_allocation[\"Portfolio\"] = (sector_allocation[\"Portfolio\"] * 100).map(\n",
-    "    \"{:.3}%\".format\n",
-    ")\n",
-    "sector_allocation[\"Benchmark\"] = (sector_allocation[\"Benchmark\"] * 100).map(\n",
-    "    \"{:.3}%\".format\n",
-    ")\n",
-    "sector_allocation[\"Difference\"] = (sector_allocation[\"Difference\"] * 100).map(\n",
-    "    \"{:.3}pp\".format\n",
-    ")\n",
-    "\n",
-    "sector_allocation"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6e1260b4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "distr_chart = openbb.portfolio.distr_chart(P, external_axes=True)\n",
-    "\n",
-    "if distr_chart:\n",
-    "    distr_chart = distr_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a668a58b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "dret_chart = openbb.portfolio.dret_chart(P, external_axes=True)\n",
-    "\n",
-    "if dret_chart:\n",
-    "    dret_chart = dret_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1ea71ca6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "yret_chart = openbb.portfolio.yret_chart(P, external_axes=True)\n",
-    "\n",
-    "if yret_chart:\n",
-    "    yret_chart = yret_chart.to_html()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ac795b8e",
-   "metadata": {},
-   "source": [
-    "## Render the report template to a file"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ebe0799e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "body = f\"\"\"\n",
-    "<style>\n",
-    "@font-face {{\n",
-    "    font-family: \"Fira Code\";\n",
-    "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
-    "    font-weight: 400 700;\n",
-    "    font-stretch: 50%;\n",
-    "}}\n",
-    "</style>\n",
-    "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
-    "\"\"\"\n",
-    "\n",
-    "\n",
-    "img = (\n",
-    "    str(REPOSITORY_DIRECTORY)\n",
-    "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
-    ")\n",
-    "floppy_disk_img = (\n",
-    "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
-    ")\n",
-    "body += widgets.header(\n",
-    "    img,\n",
-    "    floppy_disk_img,\n",
-    "    \"OpenBB\",\n",
-    "    report_date,\n",
-    "    report_time,\n",
-    "    report_timezone,\n",
-    "    report_title,\n",
-    ")\n",
-    "\n",
-    "body += widgets.tablinks([\"SUMMARY\", \"In-Depth Analysis\", \"Statistics\"])\n",
-    "\n",
-    "# Summary\n",
-    "htmlcode = widgets.p(\n",
-    "    \"The total performance of the portfolio versus the benchmark is as follows. \"\n",
-    "    \"Please note this calculation assumes partially shares exist for the benchmark.\"\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Performance\") + openbb.portfolio.perf(P).to_html()]\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.p(\"In which the following yearly returns are achieved:\")\n",
-    "\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Yearly Performance\") + yret_chart])\n",
-    "\n",
-    "htmlcode += widgets.p(\n",
-    "    \"The portfolio and benchmark consists of the following allocations to countries and sectors.\"\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Country Allocation\") + country_allocation.to_html()]\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Sector Allocation\") + sector_allocation.to_html()]\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.p(\n",
-    "    \"The portfolio consists of the following trades including returns.\"\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Portfolio Trades\") + P.portfolio_trades.to_html()]\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.p(\n",
-    "    \"The benchmark consists of the following trades including returns.\"\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Benchmark Trades\") + P.benchmark_trades.to_html()]\n",
-    ")\n",
-    "\n",
-    "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
-    "\n",
-    "# In Depth Analysis\n",
-    "htmlcode = widgets.p(\n",
-    "    \"The following metrics, Tracking Error and Information Ratio, measure whether you are \"\n",
-    "    \"closely aligned with the benchmark. If the Tracking Error is not close to 1, a different benchmark \"\n",
-    "    \"might be a better fit.\"\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Tracking Error\") + openbb.portfolio.metric.trackerr(P)[0].to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [\n",
-    "        widgets.h(3, \"Information Ratio\")\n",
-    "        + openbb.portfolio.metric.information(P).to_html()\n",
-    "    ]\n",
-    ")\n",
-    "\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Beta Chart\") + beta_chart])\n",
-    "\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Sharpe Ratio\") + openbb.portfolio.metric.sharpe(P).to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Sharpe Ratio Chart\") + sharpe_chart])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Volatility\") + openbb.portfolio.metric.volatility(P).to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Volatility Chart\") + volatility_chart])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Sortino Ratio\") + openbb.portfolio.metric.sortino(P).to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Sortino Chart\") + sortino_chart])\n",
-    "\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Maximum Drawdown\") + maxdd_chart])\n",
-    "\n",
-    "\n",
-    "body += widgets.add_tab(\"In-Depth Analysis\", htmlcode)\n",
-    "\n",
-    "# Statistics\n",
-    "htmlcode = widgets.row([widgets.h(3, \"Distribution\") + distr_chart])\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Daily Returns\") + dret_chart])\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Volatility\") + openbb.portfolio.metric.volatility(P).to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Kurtosis\") + openbb.portfolio.metric.kurtosis(P).to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Skew\") + openbb.portfolio.metric.skew(P).to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Value at Risk (VaR)\") + openbb.portfolio.var(P).to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Expected Shortfall (cVaR)\") + openbb.portfolio.es(P).to_html()]\n",
-    ")\n",
-    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Omega Ratio\") + openbb.portfolio.om(P).to_html()]\n",
-    ")\n",
-    "\n",
-    "body += widgets.add_tab(\"Statistics\", htmlcode)\n",
-    "\n",
-    "body += widgets.tab_clickable_and_save_evt()\n",
-    "\n",
-    "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
-    "\n",
-    "# to save the results\n",
-    "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
-    "    fh.write(report)"
-   ]
-  }
- ],
- "metadata": {
-  "celltoolbar": "Tags",
-  "kernelspec": {
-   "display_name": "obb",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.9"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "100174a9203096c0c10fb537684ff280825ee9e252451beb8786068677204f06"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "id": "70ba2c8a",
+            "metadata": {},
+            "source": [
+                "## Notebook setup"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "driven-billion",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import os\n",
+                "import io\n",
+                "import warnings\n",
+                "import datetime\n",
+                "import numpy as np\n",
+                "import base64\n",
+                "import pytz\n",
+                "import pandas as pd\n",
+                "\n",
+                "from IPython.display import HTML\n",
+                "\n",
+                "import openbb_terminal.config_terminal as cfg\n",
+                "from openbb_terminal.helper_classes import TerminalStyle\n",
+                "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
+                "from openbb_terminal import OpenBBFigure\n",
+                "\n",
+                "warnings.filterwarnings(\"ignore\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "49032d55",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Suppressing sdk logs\n",
+                "cfg.change_logging_suppress(new_value=True)\n",
+                "\n",
+                "# Import the OpenBB SDK\n",
+                "from openbb_terminal.sdk import openbb, widgets, helper"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "62d3ea0e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from openbb_terminal.core.session.current_user import get_current_user\n",
+                "\n",
+                "user = get_current_user()\n",
+                "\n",
+                "cfg.theme = TerminalStyle(\n",
+                "    user.preferences.MPL_STYLE,\n",
+                "    user.preferences.PMF_STYLE,\n",
+                "    user.preferences.RICH_STYLE,\n",
+                ")\n",
+                "\n",
+                "USER_PORTFOLIO_DATA_DIRECTORY = user.preferences.USER_PORTFOLIO_DATA_DIRECTORY"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "4391e874",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "stylesheet = widgets.html_report_stylesheet()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "8136bf90",
+            "metadata": {},
+            "source": [
+                "### Header"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "theme = TerminalStyle(\"light\", \"light\", \"light\")\n",
+                "stylesheet = widgets.html_report_stylesheet()\n",
+                "user_time_zone = pytz.timezone(helper.get_user_timezone())"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "daef64ec",
+            "metadata": {
+                "tags": [
+                    "parameters"
+                ]
+            },
+            "outputs": [],
+            "source": [
+                "# Parameters that will be replaced when calling this notebook\n",
+                "# Do not leave parameters blank as notebook will not run otherwise\n",
+                "transactions = \"holdings_example.xlsx\"\n",
+                "report_name = \"Portfolio Report\""
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "dd441a31",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "file_0 = (\n",
+                "    str(REPOSITORY_DIRECTORY)\n",
+                "    + \"/openbb_terminal/miscellaneous/portfolio/\"\n",
+                "    + transactions\n",
+                ")\n",
+                "file_1 = str(USER_PORTFOLIO_DATA_DIRECTORY) + \"/holdings/\" + transactions\n",
+                "\n",
+                "if os.path.isfile(file_0):\n",
+                "    transactions_path = file_0\n",
+                "elif os.path.isfile(file_1):\n",
+                "    transactions_path = file_1\n",
+                "else:\n",
+                "    raise FileNotFoundError(\"File not found: \" + transactions)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "_, transactions_file = os.path.split(transactions_path)\n",
+                "report_title = f\"Portfolio report for {transactions_file}\"\n",
+                "report_date = pd.Timestamp.now(tz=user_time_zone).strftime(\"%d %B, %Y\")\n",
+                "report_time = pd.Timestamp.now(tz=user_time_zone).strftime(\"%H:%M\")\n",
+                "report_timezone = pd.Timestamp.now(tz=user_time_zone).tzinfo\n",
+                "report_title, report_date, report_time, report_timezone"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "9363f19a",
+            "metadata": {},
+            "source": [
+                "## Data"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "eb3dbd48",
+            "metadata": {},
+            "source": [
+                "Loading"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "b139556d",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "try:\n",
+                "    P = openbb.portfolio.load(transactions_path)\n",
+                "    openbb.portfolio.show(P)\n",
+                "except Exception as e:\n",
+                "    raise Exception(\"Failed to load the transactions.\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "af24ed22",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "beta_chart = openbb.portfolio.rbeta_chart(P, external_axes=True)\n",
+                "\n",
+                "if beta_chart:\n",
+                "    beta_chart = beta_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "636c743d",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "sharpe_chart = openbb.portfolio.rsharpe_chart(P, external_axes=True)\n",
+                "\n",
+                "if sharpe_chart:\n",
+                "    sharpe_chart = sharpe_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "ae0d9381",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "volatility_chart = openbb.portfolio.rvol_chart(P, external_axes=True)\n",
+                "\n",
+                "if volatility_chart:\n",
+                "    volatility_chart = volatility_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "7e5e6fff",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "sortino_chart = openbb.portfolio.rsort_chart(P, external_axes=True)\n",
+                "\n",
+                "if sortino_chart:\n",
+                "    sortino_chart = sortino_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "3567b0ca",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "maxdd_chart = openbb.portfolio.maxdd_chart(P, external_axes=True)\n",
+                "\n",
+                "if maxdd_chart:\n",
+                "    maxdd_chart = maxdd_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "5dbcc1eb",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "country_allocation = openbb.portfolio.alloc.countries(P)\n",
+                "\n",
+                "country_allocation[\"Portfolio\"] = (country_allocation[\"Portfolio\"] * 100).map(\n",
+                "    \"{:.3}%\".format\n",
+                ")\n",
+                "country_allocation[\"Benchmark\"] = (country_allocation[\"Benchmark\"] * 100).map(\n",
+                "    \"{:.3}%\".format\n",
+                ")\n",
+                "country_allocation[\"Difference\"] = (country_allocation[\"Difference\"] * 100).map(\n",
+                "    \"{:.3}pp\".format\n",
+                ")\n",
+                "\n",
+                "country_allocation"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "8e1a67a6",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "sector_allocation = openbb.portfolio.alloc.sectors(P)\n",
+                "\n",
+                "sector_allocation[\"Portfolio\"] = (sector_allocation[\"Portfolio\"] * 100).map(\n",
+                "    \"{:.3}%\".format\n",
+                ")\n",
+                "sector_allocation[\"Benchmark\"] = (sector_allocation[\"Benchmark\"] * 100).map(\n",
+                "    \"{:.3}%\".format\n",
+                ")\n",
+                "sector_allocation[\"Difference\"] = (sector_allocation[\"Difference\"] * 100).map(\n",
+                "    \"{:.3}pp\".format\n",
+                ")\n",
+                "\n",
+                "sector_allocation"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "6e1260b4",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "distr_chart = openbb.portfolio.distr_chart(P, external_axes=True)\n",
+                "\n",
+                "if distr_chart:\n",
+                "    distr_chart = distr_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "a668a58b",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "dret_chart = openbb.portfolio.dret_chart(P, external_axes=True)\n",
+                "\n",
+                "if dret_chart:\n",
+                "    dret_chart = dret_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "1ea71ca6",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "yret_chart = openbb.portfolio.yret_chart(P, external_axes=True)\n",
+                "\n",
+                "if yret_chart:\n",
+                "    yret_chart = yret_chart.to_html()"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "id": "ac795b8e",
+            "metadata": {},
+            "source": [
+                "## Render the report template to a file"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "ebe0799e",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "body = f\"\"\"\n",
+                "<style>\n",
+                "@font-face {{\n",
+                "    font-family: \"Fira Code\";\n",
+                "    src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
+                "    font-weight: 400 700;\n",
+                "    font-stretch: 50%;\n",
+                "}}\n",
+                "</style>\n",
+                "<script src=\"/{OpenBBFigure.plotlyjs_path.as_uri()}\"></script>\n",
+                "\"\"\"\n",
+                "\n",
+                "\n",
+                "img = (\n",
+                "    str(REPOSITORY_DIRECTORY)\n",
+                "    + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
+                ")\n",
+                "floppy_disk_img = (\n",
+                "    str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
+                ")\n",
+                "body += widgets.header(\n",
+                "    img,\n",
+                "    floppy_disk_img,\n",
+                "    \"OpenBB\",\n",
+                "    report_date,\n",
+                "    report_time,\n",
+                "    report_timezone,\n",
+                "    report_title,\n",
+                ")\n",
+                "\n",
+                "body += widgets.tablinks([\"SUMMARY\", \"In-Depth Analysis\", \"Statistics\"])\n",
+                "\n",
+                "# Summary\n",
+                "htmlcode = widgets.p(\n",
+                "    \"The total performance of the portfolio versus the benchmark is as follows. \"\n",
+                "    \"Please note this calculation assumes partially shares exist for the benchmark.\"\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Performance\") + openbb.portfolio.perf(P).to_html()]\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.p(\"In which the following yearly returns are achieved:\")\n",
+                "\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Yearly Performance\") + yret_chart])\n",
+                "\n",
+                "htmlcode += widgets.p(\n",
+                "    \"The portfolio and benchmark consists of the following allocations to countries and sectors.\"\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Country Allocation\") + country_allocation.to_html()]\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Sector Allocation\") + sector_allocation.to_html()]\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.p(\n",
+                "    \"The portfolio consists of the following trades including returns.\"\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Portfolio Trades\") + P.portfolio_trades.to_html()]\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.p(\n",
+                "    \"The benchmark consists of the following trades including returns.\"\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Benchmark Trades\") + P.benchmark_trades.to_html()]\n",
+                ")\n",
+                "\n",
+                "body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
+                "\n",
+                "# In Depth Analysis\n",
+                "htmlcode = widgets.p(\n",
+                "    \"The following metrics, Tracking Error and Information Ratio, measure whether you are \"\n",
+                "    \"closely aligned with the benchmark. If the Tracking Error is not close to 1, a different benchmark \"\n",
+                "    \"might be a better fit.\"\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Tracking Error\") + openbb.portfolio.metric.trackerr(P)[0].to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [\n",
+                "        widgets.h(3, \"Information Ratio\")\n",
+                "        + openbb.portfolio.metric.information(P).to_html()\n",
+                "    ]\n",
+                ")\n",
+                "\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Beta Chart\") + beta_chart])\n",
+                "\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Sharpe Ratio\") + openbb.portfolio.metric.sharpe(P).to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Sharpe Ratio Chart\") + sharpe_chart])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Volatility\") + openbb.portfolio.metric.volatility(P).to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Volatility Chart\") + volatility_chart])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Sortino Ratio\") + openbb.portfolio.metric.sortino(P).to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Sortino Chart\") + sortino_chart])\n",
+                "\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Maximum Drawdown\") + maxdd_chart])\n",
+                "\n",
+                "\n",
+                "body += widgets.add_tab(\"In-Depth Analysis\", htmlcode)\n",
+                "\n",
+                "# Statistics\n",
+                "htmlcode = widgets.row([widgets.h(3, \"Distribution\") + distr_chart])\n",
+                "htmlcode += widgets.row([widgets.h(3, \"Daily Returns\") + dret_chart])\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Volatility\") + openbb.portfolio.metric.volatility(P).to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Kurtosis\") + openbb.portfolio.metric.kurtosis(P).to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Skew\") + openbb.portfolio.metric.skew(P).to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Value at Risk (VaR)\") + openbb.portfolio.var(P).to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Expected Shortfall (cVaR)\") + openbb.portfolio.es(P).to_html()]\n",
+                ")\n",
+                "htmlcode += widgets.row(\n",
+                "    [widgets.h(3, \"Omega Ratio\") + openbb.portfolio.om(P).to_html()]\n",
+                ")\n",
+                "\n",
+                "body += widgets.add_tab(\"Statistics\", htmlcode)\n",
+                "\n",
+                "body += widgets.tab_clickable_and_save_evt()\n",
+                "\n",
+                "report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
+                "\n",
+                "# to save the results\n",
+                "with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
+                "    fh.write(report)"
+            ]
+        }
+    ],
+    "metadata": {
+        "celltoolbar": "Tags",
+        "kernelspec": {
+            "display_name": "obb",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.10.9"
+        },
+        "vscode": {
+            "interpreter": {
+                "hash": "100174a9203096c0c10fb537684ff280825ee9e252451beb8786068677204f06"
+            }
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 5
+}
\ No newline at end of file