From bbd802bf02fd7c106c709108022b01c7ba77f895 Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 13:51:22 -0500
Subject: [PATCH 01/15] adding rmse, mse to regr

---
 .../forecast/forecast_controller.py           | 16 +++++++++-
 openbb_terminal/forecast/helpers.py           | 29 ++++++++++++++-----
 openbb_terminal/forecast/regr_model.py        |  4 +++
 openbb_terminal/forecast/regr_view.py         |  5 ++++
 4 files changed, 46 insertions(+), 8 deletions(-)

diff --git a/openbb_terminal/forecast/forecast_controller.py b/openbb_terminal/forecast/forecast_controller.py
index 1252f27731c..6d244bbb0bb 100644
--- a/openbb_terminal/forecast/forecast_controller.py
+++ b/openbb_terminal/forecast/forecast_controller.py
@@ -356,6 +356,7 @@ class ForecastController(BaseController):
         naive: bool = False,
         explainability_raw: bool = False,
         export_pred_raw: bool = False,
+        metric: bool = False,
     ):
         if hidden_size:
             parser.add_argument(
@@ -531,7 +532,7 @@ class ForecastController(BaseController):
                 action="store",
                 dest="model_type",
                 default="LSTM",
-                help='Either a string specifying the RNN module type ("RNN", "LSTM" or "GRU")',
+                help='Enter a string specifying the RNN module type ("RNN", "LSTM" or "GRU")',
             )
         if dropout is not None:
             parser.add_argument(
@@ -631,6 +632,17 @@ class ForecastController(BaseController):
                 help="Export predictions to a csv file.",
             )
 
+        if metric:
+            parser.add_argument(
+                "--metric",
+                type=str,
+                action="store",
+                dest="metric",
+                default="mape",
+                choices=["rmse", "mse", "mape"],
+                help="Calculate precision based on a specific metric (rmse, mse, mape)",
+            )
+
             # if user does not put in --dataset
         return parser
 
@@ -2561,6 +2573,7 @@ class ForecastController(BaseController):
             naive=True,
             explainability_raw=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -2595,6 +2608,7 @@ class ForecastController(BaseController):
                 naive=ns_parser.naive,
                 explainability_raw=ns_parser.explainability_raw,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)
diff --git a/openbb_terminal/forecast/helpers.py b/openbb_terminal/forecast/helpers.py
index 19df1151904..76b25664400 100644
--- a/openbb_terminal/forecast/helpers.py
+++ b/openbb_terminal/forecast/helpers.py
@@ -11,7 +11,7 @@ import pandas as pd
 from darts import TimeSeries
 from darts.dataprocessing.transformers import MissingValuesFiller, Scaler
 from darts.explainability.shap_explainer import ShapExplainer
-from darts.metrics import mape
+from darts.metrics import mape, rmse, mse
 from darts.models.forecasting.torch_forecasting_model import GlobalForecastingModel
 from darts.utils.statistics import plot_residuals_analysis
 from pytorch_lightning.callbacks.early_stopping import EarlyStopping
@@ -477,6 +477,7 @@ def plot_forecast(
     forecast_only: bool = False,
     naive: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     quant_kwargs = {}
@@ -503,7 +504,14 @@ def plot_forecast(
     if naive:
         # show naive forecast shift timeseries by 1
         naive_fcast = naive_fcast.drop_before(historical_fcast.start_time())
-        naive_precision = mape(ticker_series, naive_fcast)
+
+        # calculate precision based on metric
+        if metric == "rsme":
+            naive_precision = rmse(ticker_series, naive_fcast)
+        elif metric == "mse":
+            naive_precision = mse(ticker_series, naive_fcast)
+        elif metric == "mape":
+            naive_precision = mape(ticker_series, naive_fcast)
 
         naive_fcast.plot(
             label=f"Naive+1: {naive_precision:.2f}%",
@@ -516,7 +524,7 @@ def plot_forecast(
         pred_label += " w/ past covs"
     predicted_values.plot(label=pred_label, **quant_kwargs, color="#00AAFF")
     ax.set_title(
-        f"{name} for <{ticker_name}> for next [{n_predict}] days (MAPE={precision:.2f}%)"
+        f"{name} for <{ticker_name}> for next [{n_predict}] days ({metric.upper()}={precision:.2f}%)"
     )
     ax.set_ylabel(target_col)
     ax.set_xlabel("Date")
@@ -719,6 +727,7 @@ def get_prediction(
     train_split: float,
     forecast_horizon: int,
     n_predict: int,
+    metric: str,
 ):
     _, val = ticker_series.split_before(train_split)
 
@@ -771,10 +780,16 @@ def get_prediction(
         else:
             prediction = best_model.predict(series=ticker_series, n=n_predict)
 
-    precision = mape(
-        actual_series=val, pred_series=historical_fcast
-    )  # mape = mean average percentage error
-    console.print(f"{model_name} model obtains MAPE: {precision:.2f}% \n")
+    # calculate precision based on metric (rmse, mse, mape)
+    if metric == "rmse":
+        precision = rmse(actual_series=val, pred_series=historical_fcast)
+    elif metric == "mse":
+        precision = mse(actual_series=val, pred_series=historical_fcast)
+    elif metric == "mape":
+        precision = mape(actual_series=val, pred_series=historical_fcast)
+
+    # capalize metic name
+    console.print(f"{model_name} model obtains {metric.upper()}: {precision:.2f}% \n")
 
     # scale back
     if use_scalers and isinstance(scaler, Scaler):
diff --git a/openbb_terminal/forecast/regr_model.py b/openbb_terminal/forecast/regr_model.py
index 19871d10f24..12057e4bea3 100644
--- a/openbb_terminal/forecast/regr_model.py
+++ b/openbb_terminal/forecast/regr_model.py
@@ -26,6 +26,7 @@ def get_regression_data(
     forecast_horizon: int = 5,
     output_chunk_length: int = 5,
     lags: Union[int, List[int]] = 14,
+    metric: str = "mape",
 ) -> Tuple[
     List[TimeSeries], List[TimeSeries], List[TimeSeries], float, type[RegressionModel]
 ]:
@@ -49,6 +50,8 @@ def get_regression_data(
         The length of the forecast of the model. Defaults to 1.
     lags: Union[int, List[int]]
         lagged target values to predict the next time step
+    metric: str
+        Metric to use for evaluation. Defaults to "mape".
 
     Returns
     -------
@@ -99,4 +102,5 @@ def get_regression_data(
         train_split,
         forecast_horizon,
         n_predict,
+        metric,
     )
diff --git a/openbb_terminal/forecast/regr_view.py b/openbb_terminal/forecast/regr_view.py
index 71e34bf4ea5..f680dedb590 100644
--- a/openbb_terminal/forecast/regr_view.py
+++ b/openbb_terminal/forecast/regr_view.py
@@ -35,6 +35,7 @@ def display_regression(
     naive: bool = False,
     explainability_raw: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display Regression Forecasting
@@ -74,6 +75,8 @@ def display_regression(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the same
         as the previous day's closing price. Defaults to False.
+    metric: str
+        The metric to use for the forecast. Defaults to "mape".
     external_axes: Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -100,6 +103,7 @@ def display_regression(
         forecast_horizon=forecast_horizon,
         output_chunk_length=output_chunk_length,
         lags=lags,
+        metric=metric,
     )
     probabilistic = False
     helpers.plot_forecast(
@@ -120,6 +124,7 @@ def display_regression(
         forecast_only=forecast_only,
         naive=naive,
         export_pred_raw=export_pred_raw,
+        metric=metric,
         external_axes=external_axes,
     )
     if residuals:

From 15fdbce93eb00da7b2fc742d0158486eb28ec68f Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 14:07:07 -0500
Subject: [PATCH 02/15] brnn metrics

---
 openbb_terminal/forecast/brnn_model.py        |  4 ++++
 openbb_terminal/forecast/brnn_view.py         |  7 +++++++
 .../forecast/forecast_controller.py           | 20 +++++++++++++++++++
 3 files changed, 31 insertions(+)

diff --git a/openbb_terminal/forecast/brnn_model.py b/openbb_terminal/forecast/brnn_model.py
index 4a1341f0a65..2cef8210b7c 100644
--- a/openbb_terminal/forecast/brnn_model.py
+++ b/openbb_terminal/forecast/brnn_model.py
@@ -38,6 +38,7 @@ def get_brnn_data(
     model_save_name: str = "brnn_model",
     force_reset: bool = True,
     save_checkpoints: bool = True,
+    metric: str = "mape",
 ) -> Tuple[
     Optional[List[TimeSeries]],
     Optional[List[TimeSeries]],
@@ -84,6 +85,8 @@ def get_brnn_data(
         discarded). Defaults to True.
     save_checkpoints: bool
         Whether or not to automatically save the untrained model and checkpoints from training. Defaults to True.
+    metric: str
+        Metric to use for model selection. Defaults to "mape".
 
     Returns
     -------
@@ -174,4 +177,5 @@ def get_brnn_data(
         train_split,
         forecast_horizon,
         n_predict,
+        metric,
     )
diff --git a/openbb_terminal/forecast/brnn_view.py b/openbb_terminal/forecast/brnn_view.py
index 34b4225001d..1bfdde3f3c2 100644
--- a/openbb_terminal/forecast/brnn_view.py
+++ b/openbb_terminal/forecast/brnn_view.py
@@ -43,6 +43,7 @@ def display_brnn_forecast(
     end_date: Optional[datetime] = None,
     naive: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display BRNN forecast
@@ -102,6 +103,10 @@ def display_brnn_forecast(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the same
         as the previous day's closing price. Defaults to False.
+    export_pred_raw: bool
+        Whether to export the raw predicted values. Defaults to False.
+    metric: str
+        The metric to use for the model. Defaults to "mape".
     external_axes: Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -137,6 +142,7 @@ def display_brnn_forecast(
         model_save_name=model_save_name,
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
+        metric=metric,
     )
     if ticker_series == []:
         return
@@ -160,6 +166,7 @@ def display_brnn_forecast(
         forecast_only=forecast_only,
         naive=naive,
         export_pred_raw=export_pred_raw,
+        metric=metric,
         external_axes=external_axes,
     )
     if residuals:
diff --git a/openbb_terminal/forecast/forecast_controller.py b/openbb_terminal/forecast/forecast_controller.py
index 6d244bbb0bb..cf7b1b96c7b 100644
--- a/openbb_terminal/forecast/forecast_controller.py
+++ b/openbb_terminal/forecast/forecast_controller.py
@@ -2126,6 +2126,7 @@ class ForecastController(BaseController):
             end=True,
             naive=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -2155,6 +2156,7 @@ class ForecastController(BaseController):
                 end_date=ns_parser.s_end_date,
                 naive=ns_parser.naive,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)
@@ -2187,6 +2189,7 @@ class ForecastController(BaseController):
             end=True,
             naive=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -2214,6 +2217,7 @@ class ForecastController(BaseController):
                 end_date=ns_parser.s_end_date,
                 naive=ns_parser.naive,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)
@@ -2273,6 +2277,7 @@ class ForecastController(BaseController):
             end=True,
             naive=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -2309,6 +2314,7 @@ class ForecastController(BaseController):
                 end_date=ns_parser.s_end_date,
                 naive=ns_parser.naive,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)
@@ -2385,6 +2391,7 @@ class ForecastController(BaseController):
             end=True,
             naive=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -2427,6 +2434,7 @@ class ForecastController(BaseController):
                 end_date=ns_parser.s_end_date,
                 naive=ns_parser.naive,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)
@@ -2494,6 +2502,7 @@ class ForecastController(BaseController):
             end=True,
             naive=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -2537,6 +2546,7 @@ class ForecastController(BaseController):
                 end_date=ns_parser.s_end_date,
                 naive=ns_parser.naive,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)
@@ -2644,6 +2654,7 @@ class ForecastController(BaseController):
             naive=True,
             explainability_raw=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -2677,6 +2688,7 @@ class ForecastController(BaseController):
                 naive=ns_parser.naive,
                 explainability_raw=ns_parser.explainability_raw,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)
@@ -2728,6 +2740,7 @@ class ForecastController(BaseController):
             end=True,
             naive=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -2769,6 +2782,7 @@ class ForecastController(BaseController):
                 end_date=ns_parser.s_end_date,
                 naive=ns_parser.naive,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)
@@ -2856,6 +2870,7 @@ class ForecastController(BaseController):
             end=True,
             naive=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -2899,6 +2914,7 @@ class ForecastController(BaseController):
                 end_date=ns_parser.s_end_date,
                 naive=ns_parser.naive,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)
@@ -2972,6 +2988,7 @@ class ForecastController(BaseController):
             end=True,
             naive=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -3015,6 +3032,7 @@ class ForecastController(BaseController):
                 end_date=ns_parser.s_end_date,
                 naive=ns_parser.naive,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)
@@ -3106,6 +3124,7 @@ class ForecastController(BaseController):
             end=True,
             naive=True,
             export_pred_raw=True,
+            metric=True,
         )
         ns_parser = self.parse_known_args_and_warn(
             parser,
@@ -3150,6 +3169,7 @@ class ForecastController(BaseController):
                 end_date=ns_parser.s_end_date,
                 naive=ns_parser.naive,
                 export_pred_raw=ns_parser.export_pred_raw,
+                metric=ns_parser.metric,
             )
 
     @log_start_end(log=logger)

From b47fcc878924efade7e1a9764099dba3c9468531 Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 14:11:50 -0500
Subject: [PATCH 03/15] expo metrics

---
 openbb_terminal/forecast/expo_model.py | 18 +++++++++++++++---
 openbb_terminal/forecast/expo_view.py  |  7 +++++++
 2 files changed, 22 insertions(+), 3 deletions(-)

diff --git a/openbb_terminal/forecast/expo_model.py b/openbb_terminal/forecast/expo_model.py
index 4c117a90f78..223ea088ae3 100644
--- a/openbb_terminal/forecast/expo_model.py
+++ b/openbb_terminal/forecast/expo_model.py
@@ -8,7 +8,7 @@ from typing import List, Optional, Tuple, Union
 
 import pandas as pd
 from darts import TimeSeries
-from darts.metrics import mape
+from darts.metrics import mape, rmse, mse
 from darts.models import ExponentialSmoothing
 from darts.utils.utils import ModelMode, SeasonalityMode
 from numpy import ndarray
@@ -40,6 +40,7 @@ def get_expo_data(
     n_predict: int = 5,
     start_window: float = 0.85,
     forecast_horizon: int = 5,
+    metric: str = "mape",
 ) -> Tuple[
     List[TimeSeries],
     List[TimeSeries],
@@ -76,6 +77,8 @@ def get_expo_data(
         Size of sliding window from start of timeseries and onwards
     forecast_horizon: int
         Number of days to forecast when backtesting and retraining historical
+    metric: str
+        Metric to use for backtesting. Defaults to MAPE.
 
     Returns
     -------
@@ -149,8 +152,17 @@ def get_expo_data(
     # we have the historical fcast, now lets train on entire set and predict.
     best_model.fit(ticker_series)
     probabilistic_forecast = best_model.predict(int(n_predict), num_samples=500)
-    precision = mape(actual_series=ticker_series, pred_series=historical_fcast_es)
-    console.print(f"Exponential smoothing obtains MAPE: {precision:.2f}% \n")
+
+    if metric == "rmse":
+        precision = rmse(actual_series=ticker_series, pred_series=historical_fcast_es)
+    elif metric == "mse":
+        precision = mse(actual_series=ticker_series, pred_series=historical_fcast_es)
+    elif metric == "mape":
+        precision = mape(actual_series=ticker_series, pred_series=historical_fcast_es)
+
+    console.print(
+        f"Exponential smoothing obtains {metric.upper()}: {precision:.2f}% \n"
+    )
 
     return (
         ticker_series,
diff --git a/openbb_terminal/forecast/expo_view.py b/openbb_terminal/forecast/expo_view.py
index de41d84f49c..79771b537c7 100644
--- a/openbb_terminal/forecast/expo_view.py
+++ b/openbb_terminal/forecast/expo_view.py
@@ -36,6 +36,7 @@ def display_expo_forecast(
     end_date: Optional[datetime] = None,
     naive: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display Probabilistic Exponential Smoothing forecast
@@ -80,6 +81,10 @@ def display_expo_forecast(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the same
         as the previous day's closing price. Defaults to False.
+    export_pred_raw: bool
+        Whether to export the raw predicted values. Defaults to False.
+    metric: str
+        The metric to use when backtesting. Defaults to "mape".
     external_axes: Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -103,6 +108,7 @@ def display_expo_forecast(
         n_predict=n_predict,
         start_window=start_window,
         forecast_horizon=forecast_horizon,
+        metric=metric,
     )
 
     if ticker_series == []:
@@ -127,6 +133,7 @@ def display_expo_forecast(
         forecast_only=forecast_only,
         naive=naive,
         export_pred_raw=export_pred_raw,
+        metric=metric,
         external_axes=external_axes,
     )
     if residuals:

From 477e4271db644b92acd8e496c984d348e6c0d775 Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 14:14:59 -0500
Subject: [PATCH 04/15] linregr metrics

---
 openbb_terminal/forecast/linregr_model.py | 4 ++++
 openbb_terminal/forecast/linregr_view.py  | 9 +++++++++
 2 files changed, 13 insertions(+)

diff --git a/openbb_terminal/forecast/linregr_model.py b/openbb_terminal/forecast/linregr_model.py
index 5e4e4d91fc4..70a60654cd0 100644
--- a/openbb_terminal/forecast/linregr_model.py
+++ b/openbb_terminal/forecast/linregr_model.py
@@ -27,6 +27,7 @@ def get_linear_regression_data(
     output_chunk_length: int = 5,
     lags: Union[int, List[int]] = 14,
     random_state: Optional[int] = None,
+    metric: str = "mape",
 ) -> Tuple[
     List[TimeSeries],
     List[TimeSeries],
@@ -56,6 +57,8 @@ def get_linear_regression_data(
         lagged target values to predict the next time step
     random_state: Optional[int]
         The state for the model
+    metric: str
+        The metric to use for the model. Defaults to "mape".
 
     Returns
     -------
@@ -112,4 +115,5 @@ def get_linear_regression_data(
         train_split,
         forecast_horizon,
         n_predict,
+        metric,
     )
diff --git a/openbb_terminal/forecast/linregr_view.py b/openbb_terminal/forecast/linregr_view.py
index 6bc09879edc..2b3815338cd 100644
--- a/openbb_terminal/forecast/linregr_view.py
+++ b/openbb_terminal/forecast/linregr_view.py
@@ -35,6 +35,7 @@ def display_linear_regression(
     naive: bool = False,
     explainability_raw: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display Linear Regression Forecasting
@@ -74,6 +75,12 @@ def display_linear_regression(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the
         same as the previous day's closing price. Defaults to False.
+    explainability_raw: bool
+        Whether to show the raw explainability data. Defaults to False.
+    export_pred_raw: bool
+        Whether to export the raw prediction data. Defaults to False.
+    metric: str
+        The metric to use for the model. Defaults to "mape".
     external_axes: Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -100,6 +107,7 @@ def display_linear_regression(
         forecast_horizon=forecast_horizon,
         output_chunk_length=output_chunk_length,
         lags=lags,
+        metric=metric,
     )
 
     probabilistic = True
@@ -121,6 +129,7 @@ def display_linear_regression(
         forecast_only=forecast_only,
         naive=naive,
         export_pred_raw=export_pred_raw,
+        metric=metric,
         external_axes=external_axes,
     )
     if residuals:

From 0380c4d03ae342a0b782a6a9951698e1d19ab66e Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 14:20:22 -0500
Subject: [PATCH 05/15] nbeats metrics

---
 .gitignore                               | 3 +++
 openbb_terminal/forecast/nbeats_model.py | 4 ++++
 openbb_terminal/forecast/nbeats_view.py  | 7 +++++++
 3 files changed, 14 insertions(+)

diff --git a/.gitignore b/.gitignore
index f34aa31f0eb..502886f06cc 100644
--- a/.gitignore
+++ b/.gitignore
@@ -61,3 +61,6 @@ darts_logs/
 # User data
 custom_imports/*.csv
 custom_imports/*/*.csv
+
+# lightning logs
+lightning_logs/
diff --git a/openbb_terminal/forecast/nbeats_model.py b/openbb_terminal/forecast/nbeats_model.py
index acb8480bfbe..57bca236fce 100644
--- a/openbb_terminal/forecast/nbeats_model.py
+++ b/openbb_terminal/forecast/nbeats_model.py
@@ -37,6 +37,7 @@ def get_NBEATS_data(
     model_save_name: str = "nbeats_model",
     force_reset: bool = True,
     save_checkpoints: bool = True,
+    metric: str = "mape",
 ) -> Tuple[
     Optional[List[TimeSeries]],
     Optional[List[TimeSeries]],
@@ -88,6 +89,8 @@ def get_NBEATS_data(
     save_checkpoints: bool
         Whether or not to automatically save the untrained model and checkpoints from training.
         Defaults to True.
+    metric: str
+        Metric to use for model selection. Defaults to "mape".
 
     Returns
     -------
@@ -168,4 +171,5 @@ def get_NBEATS_data(
         train_split,
         forecast_horizon,
         n_predict,
+        metric,
     )
diff --git a/openbb_terminal/forecast/nbeats_view.py b/openbb_terminal/forecast/nbeats_view.py
index 283f6dac602..e790ce09aff 100644
--- a/openbb_terminal/forecast/nbeats_view.py
+++ b/openbb_terminal/forecast/nbeats_view.py
@@ -44,6 +44,7 @@ def display_nbeats_forecast(
     end_date: Optional[datetime] = None,
     naive: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display NBEATS forecast
@@ -108,6 +109,10 @@ def display_nbeats_forecast(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the same
         as the previous day's closing price. Defaults to False.
+    export_pred_raw: bool
+        Whether to export the raw predicted values. Defaults to False.
+    metric: str
+        Metric to use for evaluation. Defaults to "mape".
     external_axes: Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -145,6 +150,7 @@ def display_nbeats_forecast(
         model_save_name=model_save_name,
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
+        metric=metric,
     )
     if ticker_series == []:
         return
@@ -168,6 +174,7 @@ def display_nbeats_forecast(
         forecast_only=forecast_only,
         naive=naive,
         export_pred_raw=export_pred_raw,
+        metric=metric,
         external_axes=external_axes,
     )
     if residuals:

From 8ccb1ddd886107656c0351030ba870f79c10c540 Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 14:29:12 -0500
Subject: [PATCH 06/15] nhits metrics

---
 openbb_terminal/forecast/nhits_model.py | 4 ++++
 openbb_terminal/forecast/nhits_view.py  | 7 +++++++
 2 files changed, 11 insertions(+)

diff --git a/openbb_terminal/forecast/nhits_model.py b/openbb_terminal/forecast/nhits_model.py
index 43a3d1ed0f4..312b1d6e0ad 100644
--- a/openbb_terminal/forecast/nhits_model.py
+++ b/openbb_terminal/forecast/nhits_model.py
@@ -43,6 +43,7 @@ def get_nhits_data(
     model_save_name: str = "nhits_model",
     force_reset: bool = True,
     save_checkpoints: bool = True,
+    metric: str = "mape",
 ) -> Tuple[
     Optional[List[TimeSeries]],
     Optional[List[TimeSeries]],
@@ -109,6 +110,8 @@ def get_nhits_data(
         discarded). Defaults to True.
     save_checkpoints: bool
         Whether or not to automatically save the untrained model and checkpoints from training. Defaults to True.
+    metric: str
+        Metric to use for model selection. Defaults to "mape".
 
     Returns
     -------
@@ -197,4 +200,5 @@ def get_nhits_data(
         train_split,
         forecast_horizon,
         n_predict,
+        metric,
     )
diff --git a/openbb_terminal/forecast/nhits_view.py b/openbb_terminal/forecast/nhits_view.py
index d4ec81ecdee..42fc8d06d79 100644
--- a/openbb_terminal/forecast/nhits_view.py
+++ b/openbb_terminal/forecast/nhits_view.py
@@ -49,6 +49,7 @@ def display_nhits_forecast(
     end_date: Optional[datetime] = None,
     naive: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display Nhits forecast
@@ -128,6 +129,10 @@ def display_nhits_forecast(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the same
         as the previous day's closing price. Defaults to False.
+    export_pred_raw: bool
+        Whether to export the raw predicted values. Defaults to False.
+    metric: str
+        Metric to use for evaluation. Defaults to "mape".
     external_axes: Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -169,6 +174,7 @@ def display_nhits_forecast(
         model_save_name=model_save_name,
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
+        metric=metric,
     )
     if ticker_series == []:
         return
@@ -192,6 +198,7 @@ def display_nhits_forecast(
         forecast_only=forecast_only,
         naive=naive,
         export_pred_raw=export_pred_raw,
+        metric=metric,
         external_axes=external_axes,
     )
     if residuals:

From bd20473594e4158ae31525beabbebafdedd83f30 Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 14:36:20 -0500
Subject: [PATCH 07/15] rnn metric

---
 openbb_terminal/forecast/rnn_model.py | 4 ++++
 openbb_terminal/forecast/rnn_view.py  | 7 +++++++
 2 files changed, 11 insertions(+)

diff --git a/openbb_terminal/forecast/rnn_model.py b/openbb_terminal/forecast/rnn_model.py
index 5f860bb43e0..8744ef98338 100644
--- a/openbb_terminal/forecast/rnn_model.py
+++ b/openbb_terminal/forecast/rnn_model.py
@@ -36,6 +36,7 @@ def get_rnn_data(
     input_chunk_size: int = 14,
     force_reset: bool = True,
     save_checkpoints: bool = True,
+    metric: str = "mape",
 ) -> Tuple[
     Optional[List[type[TimeSeries]]],
     Optional[List[type[TimeSeries]]],
@@ -77,6 +78,8 @@ def get_rnn_data(
     save_checkpoints: bool
         Whether or not to automatically save the untrained model and checkpoints from training.
         Defaults to True.
+    metric: str
+        Metric to use for model selection. Defaults to "mape".
 
     Returns
     -------
@@ -145,4 +148,5 @@ def get_rnn_data(
         train_split,
         forecast_horizon,
         n_predict,
+        metric,
     )
diff --git a/openbb_terminal/forecast/rnn_view.py b/openbb_terminal/forecast/rnn_view.py
index 31f25916575..cbf1360f8cd 100644
--- a/openbb_terminal/forecast/rnn_view.py
+++ b/openbb_terminal/forecast/rnn_view.py
@@ -42,6 +42,7 @@ def display_rnn_forecast(
     end_date: Optional[datetime] = None,
     naive: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display RNN forecast
@@ -94,6 +95,10 @@ def display_rnn_forecast(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the same
         as the previous day's closing price. Defaults to False.
+    export_pred_raw: bool
+        Whether to export the raw predictions. Defaults to False.
+    metric: str
+        The metric to use for the forecast. Defaults to "mape".
     external_axes: Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -124,6 +129,7 @@ def display_rnn_forecast(
         input_chunk_size=input_chunk_size,
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
+        metric=metric,
     )
     if ticker_series == []:
         return
@@ -148,6 +154,7 @@ def display_rnn_forecast(
         forecast_only=forecast_only,
         naive=naive,
         export_pred_raw=export_pred_raw,
+        metric=metric,
         external_axes=external_axes,
     )
     if residuals:

From 56eba54a3e69af664759633bfb2bdb345b811c6d Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 14:40:05 -0500
Subject: [PATCH 08/15] tcn metrics

---
 openbb_terminal/forecast/tcn_model.py | 4 ++++
 openbb_terminal/forecast/tcn_view.py  | 7 +++++++
 2 files changed, 11 insertions(+)

diff --git a/openbb_terminal/forecast/tcn_model.py b/openbb_terminal/forecast/tcn_model.py
index 1d0c7467d39..fe4604b1404 100644
--- a/openbb_terminal/forecast/tcn_model.py
+++ b/openbb_terminal/forecast/tcn_model.py
@@ -37,6 +37,7 @@ def get_tcn_data(
     model_save_name: str = "tcn_model",
     force_reset: bool = True,
     save_checkpoints: bool = True,
+    metric: str = "mape",
 ) -> Tuple[
     List[Optional[TimeSeries]],
     List[Optional[TimeSeries]],
@@ -86,6 +87,8 @@ def get_tcn_data(
     save_checkpoints: bool
         Whether or not to automatically save the untrained model and checkpoints from training.
         Defaults to True.
+    metric: str
+        Metric to use for model selection. Defaults to "mape".
 
     Returns
     -------
@@ -166,4 +169,5 @@ def get_tcn_data(
         train_split,
         forecast_horizon,
         n_predict,
+        metric,
     )
diff --git a/openbb_terminal/forecast/tcn_view.py b/openbb_terminal/forecast/tcn_view.py
index 5e7cf5aec94..13ff4003761 100644
--- a/openbb_terminal/forecast/tcn_view.py
+++ b/openbb_terminal/forecast/tcn_view.py
@@ -44,6 +44,7 @@ def display_tcn_forecast(
     end_date: Optional[datetime] = None,
     naive: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display TCN forecast
@@ -104,6 +105,10 @@ def display_tcn_forecast(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the same
         as the previous day's closing price. Defaults to False.
+    export_pred_raw: bool
+        Whether to export the raw predicted values. Defaults to False.
+    metric: str
+        The metric to use for the model. Defaults to "mape".
     external_axes: Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -141,6 +146,7 @@ def display_tcn_forecast(
         model_save_name=model_save_name,
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
+        metric=metric,
     )
     if ticker_series == []:
         return
@@ -165,6 +171,7 @@ def display_tcn_forecast(
         naive=naive,
         export_pred_raw=export_pred_raw,
         external_axes=external_axes,
+        metric=metric,
     )
     if residuals:
         helpers.plot_residuals(

From 39ab07d9a3ac62059727c18845b39b867c6951bc Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 14:42:26 -0500
Subject: [PATCH 09/15] tft metric

---
 openbb_terminal/forecast/tft_model.py | 4 ++++
 openbb_terminal/forecast/tft_view.py  | 5 +++++
 2 files changed, 9 insertions(+)

diff --git a/openbb_terminal/forecast/tft_model.py b/openbb_terminal/forecast/tft_model.py
index 136ab21f074..41420ee2af3 100644
--- a/openbb_terminal/forecast/tft_model.py
+++ b/openbb_terminal/forecast/tft_model.py
@@ -43,6 +43,7 @@ def get_tft_data(
     model_save_name: str = "tft_model",
     force_reset: bool = True,
     save_checkpoints: bool = True,
+    metric: str = "mape",
 ) -> Tuple[
     Optional[List[TimeSeries]],
     Optional[List[TimeSeries]],
@@ -101,6 +102,8 @@ def get_tft_data(
     save_checkpoints: (bool, optional)
         Whether or not to automatically save the untrained model and checkpoints from training.
         Defaults to True.
+    metric: (str, optional)
+        Metric to use for model selection. Defaults to "mape".
 
     Returns
     -------
@@ -204,4 +207,5 @@ def get_tft_data(
         train_split,
         forecast_horizon,
         n_predict,
+        metric,
     )
diff --git a/openbb_terminal/forecast/tft_view.py b/openbb_terminal/forecast/tft_view.py
index 3064027500c..8264b921d2a 100644
--- a/openbb_terminal/forecast/tft_view.py
+++ b/openbb_terminal/forecast/tft_view.py
@@ -45,6 +45,7 @@ def display_tft_forecast(
     end_date: Optional[datetime] = None,
     naive: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display Temporal Fusion Transformer forecast
@@ -105,6 +106,8 @@ def display_tft_forecast(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the same
         as the previous day's closing price. Defaults to False.
+    metric: str
+        The metric to use for the model. Defaults to "mape".
     external_axes:Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -143,6 +146,7 @@ def display_tft_forecast(
         model_save_name=model_save_name,
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
+        metric=metric,
     )
     if ticker_series == []:
         return
@@ -166,6 +170,7 @@ def display_tft_forecast(
         forecast_only=forecast_only,
         naive=naive,
         export_pred_raw=export_pred_raw,
+        metric=metric,
         external_axes=external_axes,
     )
     if residuals:

From fe074dd3c06e6aff771d74ddc2f39daf4e828e2b Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 14:45:15 -0500
Subject: [PATCH 10/15] theta metrics

---
 openbb_terminal/forecast/theta_model.py | 24 ++++++++++++++++++------
 openbb_terminal/forecast/theta_view.py  |  7 +++++++
 2 files changed, 25 insertions(+), 6 deletions(-)

diff --git a/openbb_terminal/forecast/theta_model.py b/openbb_terminal/forecast/theta_model.py
index 74ef6523933..5f0e266b094 100644
--- a/openbb_terminal/forecast/theta_model.py
+++ b/openbb_terminal/forecast/theta_model.py
@@ -8,7 +8,7 @@ from typing import List, Optional, Tuple, Union
 import numpy as np
 import pandas as pd
 from darts import TimeSeries
-from darts.metrics import mape
+from darts.metrics import mape, rmse, mse
 from darts.models import Theta
 from darts.utils.utils import SeasonalityMode
 from statsmodels.tools.sm_exceptions import ConvergenceWarning
@@ -34,6 +34,7 @@ def get_theta_data(
     n_predict: int = 5,
     start_window: float = 0.85,
     forecast_horizon: int = 5,
+    metric: str = "mape",
 ) -> Tuple[
     Optional[List[TimeSeries]],
     Optional[List[TimeSeries]],
@@ -64,7 +65,9 @@ def get_theta_data(
     start_window: float
         Size of sliding window from start of timeseries and onwards
     forecast_horizon: int
-        Number of days to forecast when backtesting and retraining historical
+        Number of days to forecast when backtesting and retraining historical data
+    metric: str
+        Metric to use when backtesting and retraining historical data. Defaults to "mape".
 
     Returns
     -------
@@ -135,10 +138,19 @@ def get_theta_data(
     # fit model on entire series for final prediction
     best_theta_model_final.fit(ticker_series)
     prediction = best_theta_model_final.predict(int(n_predict))
-    precision = mape(
-        actual_series=ticker_series, pred_series=historical_fcast_theta
-    )  # mape = mean average precision error
-    console.print(f"Theta Model obtains MAPE: {precision:.2f}% \n")
+
+    if metric == "rmse":
+        precision = rmse(
+            actual_series=ticker_series, pred_series=historical_fcast_theta
+        )
+    elif metric == "mse":
+        precision = mse(actual_series=ticker_series, pred_series=historical_fcast_theta)
+    elif metric == "mape":
+        precision = mape(
+            actual_series=ticker_series, pred_series=historical_fcast_theta
+        )
+
+    console.print(f"Theta Model obtains {metric.upper()}: {precision:.2f}% \n")
 
     return (
         ticker_series,
diff --git a/openbb_terminal/forecast/theta_view.py b/openbb_terminal/forecast/theta_view.py
index 428e95c1663..041b865fbf7 100644
--- a/openbb_terminal/forecast/theta_view.py
+++ b/openbb_terminal/forecast/theta_view.py
@@ -34,6 +34,7 @@ def display_theta_forecast(
     end_date: Optional[datetime] = None,
     naive: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display Theta forecast
@@ -73,6 +74,10 @@ def display_theta_forecast(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the same
         as the previous day's closing price. Defaults to False.
+    export_pred_raw: bool
+        Whether to export the raw predicted values. Defaults to False.
+    metric: str
+        The metric to use for backtesting. Defaults to "mape".
     external_axes:Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -95,6 +100,7 @@ def display_theta_forecast(
         target_column=target_column,
         start_window=start_window,
         forecast_horizon=forecast_horizon,
+        metric=metric,
     )
     if ticker_series == []:
         return
@@ -119,6 +125,7 @@ def display_theta_forecast(
         naive=naive,
         export_pred_raw=export_pred_raw,
         external_axes=external_axes,
+        metric=metric,
     )
 
     if residuals:

From 168bb0a5d731cd091cdc69291285f5221e9a9271 Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 14:48:38 -0500
Subject: [PATCH 11/15] trans metric

---
 openbb_terminal/forecast/trans_model.py | 4 ++++
 openbb_terminal/forecast/trans_view.py  | 7 +++++++
 2 files changed, 11 insertions(+)

diff --git a/openbb_terminal/forecast/trans_model.py b/openbb_terminal/forecast/trans_model.py
index ac89b255820..21cac569567 100644
--- a/openbb_terminal/forecast/trans_model.py
+++ b/openbb_terminal/forecast/trans_model.py
@@ -40,6 +40,7 @@ def get_trans_data(
     model_save_name: str = "trans_model",
     force_reset: bool = True,
     save_checkpoints: bool = True,
+    metric: str = "mape",
 ) -> Tuple[
     Optional[List[TimeSeries]],
     Optional[List[TimeSeries]],
@@ -94,6 +95,8 @@ def get_trans_data(
         discarded). Defaults to True.
     save_checkpoints: bool
         Whether or not to automatically save the untrained model and checkpoints from training. Defaults to True.
+    metric: str
+        Metric to use for model selection. Defaults to "mape".
 
     Returns
     -------
@@ -176,4 +179,5 @@ def get_trans_data(
         train_split,
         forecast_horizon,
         n_predict,
+        metric,
     )
diff --git a/openbb_terminal/forecast/trans_view.py b/openbb_terminal/forecast/trans_view.py
index fda46a687a6..4ca64c1b5b4 100644
--- a/openbb_terminal/forecast/trans_view.py
+++ b/openbb_terminal/forecast/trans_view.py
@@ -47,6 +47,7 @@ def display_trans_forecast(
     end_date: Optional[datetime] = None,
     naive: bool = False,
     export_pred_raw: bool = False,
+    metric: str = "mape",
     external_axes: Optional[List[plt.axes]] = None,
 ):
     """Display Transformer forecast
@@ -112,6 +113,10 @@ def display_trans_forecast(
     naive: bool
         Whether to show the naive baseline. This just assumes the closing price will be the same
         as the previous day's closing price. Defaults to False.
+    export_pred_raw: bool
+        Whether to export the raw predicted values. Defaults to False.
+    metric: str
+        The metric to use for the model. Defaults to "mape".
     external_axes: Optional[List[plt.axes]]
         External axes to plot on
     """
@@ -152,6 +157,7 @@ def display_trans_forecast(
         model_save_name=model_save_name,
         force_reset=force_reset,
         save_checkpoints=save_checkpoints,
+        metric=metric,
     )
     if ticker_series == []:
         return
@@ -176,6 +182,7 @@ def display_trans_forecast(
         naive=naive,
         export_pred_raw=export_pred_raw,
         external_axes=external_axes,
+        metric=metric,
     )
     if residuals:
         helpers.plot_residuals(

From 2e67ceb63fed95d005b166ffd4fc6a5539c381fd Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 15:00:28 -0500
Subject: [PATCH 12/15] linting

---
 openbb_terminal/forecast/helpers.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/openbb_terminal/forecast/helpers.py b/openbb_terminal/forecast/helpers.py
index 76b25664400..b16fdfb9f7e 100644
--- a/openbb_terminal/forecast/helpers.py
+++ b/openbb_terminal/forecast/helpers.py
@@ -788,7 +788,6 @@ def get_prediction(
     elif metric == "mape":
         precision = mape(actual_series=val, pred_series=historical_fcast)
 
-    # capalize metic name
     console.print(f"{model_name} model obtains {metric.upper()}: {precision:.2f}% \n")
 
     # scale back

From c04b1e8d55aee5b74fc8bb102ed5446853d9ec4e Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 15:12:16 -0500
Subject: [PATCH 13/15] linting #2

---
 openbb_terminal/forecast/expo_model.py  | 2 +-
 openbb_terminal/forecast/helpers.py     | 2 +-
 openbb_terminal/forecast/theta_model.py | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/openbb_terminal/forecast/expo_model.py b/openbb_terminal/forecast/expo_model.py
index 223ea088ae3..cde29361c48 100644
--- a/openbb_terminal/forecast/expo_model.py
+++ b/openbb_terminal/forecast/expo_model.py
@@ -8,7 +8,7 @@ from typing import List, Optional, Tuple, Union
 
 import pandas as pd
 from darts import TimeSeries
-from darts.metrics import mape, rmse, mse
+from darts.metrics import mape, rmse, mse  # noqa: I001
 from darts.models import ExponentialSmoothing
 from darts.utils.utils import ModelMode, SeasonalityMode
 from numpy import ndarray
diff --git a/openbb_terminal/forecast/helpers.py b/openbb_terminal/forecast/helpers.py
index b16fdfb9f7e..a67411aa7af 100644
--- a/openbb_terminal/forecast/helpers.py
+++ b/openbb_terminal/forecast/helpers.py
@@ -11,7 +11,7 @@ import pandas as pd
 from darts import TimeSeries
 from darts.dataprocessing.transformers import MissingValuesFiller, Scaler
 from darts.explainability.shap_explainer import ShapExplainer
-from darts.metrics import mape, rmse, mse
+from darts.metrics import mape, rmse, mse  # noqa: I001
 from darts.models.forecasting.torch_forecasting_model import GlobalForecastingModel
 from darts.utils.statistics import plot_residuals_analysis
 from pytorch_lightning.callbacks.early_stopping import EarlyStopping
diff --git a/openbb_terminal/forecast/theta_model.py b/openbb_terminal/forecast/theta_model.py
index 5f0e266b094..0a1d4b171ef 100644
--- a/openbb_terminal/forecast/theta_model.py
+++ b/openbb_terminal/forecast/theta_model.py
@@ -8,7 +8,7 @@ from typing import List, Optional, Tuple, Union
 import numpy as np
 import pandas as pd
 from darts import TimeSeries
-from darts.metrics import mape, rmse, mse
+from darts.metrics import mape, rmse, mse  # noqa: I001
 from darts.models import Theta
 from darts.utils.utils import SeasonalityMode
 from statsmodels.tools.sm_exceptions import ConvergenceWarning

From 9d2509a000fe997b4068a8930afd18b07ef6a371 Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Wed, 8 Feb 2023 16:10:31 -0500
Subject: [PATCH 14/15] smape

---
 openbb_terminal/forecast/expo_model.py          | 4 +++-
 openbb_terminal/forecast/forecast_controller.py | 2 +-
 openbb_terminal/forecast/helpers.py             | 6 +++++-
 openbb_terminal/forecast/theta_model.py         | 6 +++++-
 4 files changed, 14 insertions(+), 4 deletions(-)

diff --git a/openbb_terminal/forecast/expo_model.py b/openbb_terminal/forecast/expo_model.py
index cde29361c48..6c47acb9785 100644
--- a/openbb_terminal/forecast/expo_model.py
+++ b/openbb_terminal/forecast/expo_model.py
@@ -8,7 +8,7 @@ from typing import List, Optional, Tuple, Union
 
 import pandas as pd
 from darts import TimeSeries
-from darts.metrics import mape, rmse, mse  # noqa: I001
+from darts.metrics import mape, rmse, mse, smape  # noqa: I001
 from darts.models import ExponentialSmoothing
 from darts.utils.utils import ModelMode, SeasonalityMode
 from numpy import ndarray
@@ -159,6 +159,8 @@ def get_expo_data(
         precision = mse(actual_series=ticker_series, pred_series=historical_fcast_es)
     elif metric == "mape":
         precision = mape(actual_series=ticker_series, pred_series=historical_fcast_es)
+    elif metric == "smape":
+        precision = smape(actual_series=ticker_series, pred_series=historical_fcast_es)
 
     console.print(
         f"Exponential smoothing obtains {metric.upper()}: {precision:.2f}% \n"
diff --git a/openbb_terminal/forecast/forecast_controller.py b/openbb_terminal/forecast/forecast_controller.py
index cf7b1b96c7b..2da91ffbfa5 100644
--- a/openbb_terminal/forecast/forecast_controller.py
+++ b/openbb_terminal/forecast/forecast_controller.py
@@ -639,7 +639,7 @@ class ForecastController(BaseController):
                 action="store",
                 dest="metric",
                 default="mape",
-                choices=["rmse", "mse", "mape"],
+                choices=["rmse", "mse", "mape", "smape"],
                 help="Calculate precision based on a specific metric (rmse, mse, mape)",
             )
 
diff --git a/openbb_terminal/forecast/helpers.py b/openbb_terminal/forecast/helpers.py
index a67411aa7af..cd790ed5f61 100644
--- a/openbb_terminal/forecast/helpers.py
+++ b/openbb_terminal/forecast/helpers.py
@@ -11,7 +11,7 @@ import pandas as pd
 from darts import TimeSeries
 from darts.dataprocessing.transformers import MissingValuesFiller, Scaler
 from darts.explainability.shap_explainer import ShapExplainer
-from darts.metrics import mape, rmse, mse  # noqa: I001
+from darts.metrics import mape, rmse, mse, smape  # noqa: I001
 from darts.models.forecasting.torch_forecasting_model import GlobalForecastingModel
 from darts.utils.statistics import plot_residuals_analysis
 from pytorch_lightning.callbacks.early_stopping import EarlyStopping
@@ -512,6 +512,8 @@ def plot_forecast(
             naive_precision = mse(ticker_series, naive_fcast)
         elif metric == "mape":
             naive_precision = mape(ticker_series, naive_fcast)
+        elif metric == "smape":
+            naive_precision = smape(ticker_series, naive_fcast)
 
         naive_fcast.plot(
             label=f"Naive+1: {naive_precision:.2f}%",
@@ -787,6 +789,8 @@ def get_prediction(
         precision = mse(actual_series=val, pred_series=historical_fcast)
     elif metric == "mape":
         precision = mape(actual_series=val, pred_series=historical_fcast)
+    elif metric == "smape":
+        precision = smape(actual_series=val, pred_series=historical_fcast)
 
     console.print(f"{model_name} model obtains {metric.upper()}: {precision:.2f}% \n")
 
diff --git a/openbb_terminal/forecast/theta_model.py b/openbb_terminal/forecast/theta_model.py
index 0a1d4b171ef..77af956c483 100644
--- a/openbb_terminal/forecast/theta_model.py
+++ b/openbb_terminal/forecast/theta_model.py
@@ -8,7 +8,7 @@ from typing import List, Optional, Tuple, Union
 import numpy as np
 import pandas as pd
 from darts import TimeSeries
-from darts.metrics import mape, rmse, mse  # noqa: I001
+from darts.metrics import mape, rmse, mse, smape  # noqa: I001
 from darts.models import Theta
 from darts.utils.utils import SeasonalityMode
 from statsmodels.tools.sm_exceptions import ConvergenceWarning
@@ -149,6 +149,10 @@ def get_theta_data(
         precision = mape(
             actual_series=ticker_series, pred_series=historical_fcast_theta
         )
+    elif metric == "smape":
+        precision = smape(
+            actual_series=ticker_series, pred_series=historical_fcast_theta
+        )
 
     console.print(f"Theta Model obtains {metric.upper()}: {precision:.2f}% \n")
 

From 09f7a041906651cf5232606b57e9ed28ff671dec Mon Sep 17 00:00:00 2001
From: martinb-bb <105685594+martinb-bb@users.noreply.github.com>
Date: Thu, 9 Feb 2023 14:25:40 -0500
Subject: [PATCH 15/15] linting #3

---
 build/conda/conda-3-9-env-full.yaml     | 2 +-
 openbb_terminal/forecast/expo_model.py  | 2 +-
 openbb_terminal/forecast/helpers.py     | 2 +-
 openbb_terminal/forecast/theta_model.py | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/build/conda/conda-3-9-env-full.yaml b/build/conda/conda-3-9-env-full.yaml
index 33392f4c800..634a3c6692e 100644
--- a/build/conda/conda-3-9-env-full.yaml
+++ b/build/conda/conda-3-9-env-full.yaml
@@ -5,4 +5,4 @@ dependencies:
   - python=3.9.6
   - pip
   - poetry=1.1.13
-  - lightgbm=3.3.3
+  - lightgbm=3.3.5
diff --git a/openbb_terminal/forecast/expo_model.py b/openbb_terminal/forecast/expo_model.py
index 6c47acb9785..74ace57dd59 100644
--- a/openbb_terminal/forecast/expo_model.py
+++ b/openbb_terminal/forecast/expo_model.py
@@ -8,7 +8,7 @@ from typing import List, Optional, Tuple, Union
 
 import pandas as pd
 from darts import TimeSeries
-from darts.metrics import mape, rmse, mse, smape  # noqa: I001
+from darts.metrics import mape, mse, rmse, smape
 from darts.models import ExponentialSmoothing
 from darts.utils.utils import ModelMode, SeasonalityMode
 from numpy import ndarray
diff --git a/openbb_terminal/forecast/helpers.py b/openbb_terminal/forecast/helpers.py
index cd790ed5f61..6e6750bcd23 100644
--- a/openbb_terminal/forecast/helpers.py
+++ b/openbb_terminal/forecast/helpers.py
@@ -11,7 +11,7 @@ import pandas as pd
 from darts import TimeSeries
 from darts.dataprocessing.transformers import MissingValuesFiller, Scaler
 from darts.explainability.shap_explainer import ShapExplainer
-from darts.metrics import mape, rmse, mse, smape  # noqa: I001
+from darts.metrics import mape, mse, rmse, smape
 from darts.models.forecasting.torch_forecasting_model import GlobalForecastingModel
 from darts.utils.statistics import plot_residuals_analysis
 from pytorch_lightning.callbacks.early_stopping import EarlyStopping
diff --git a/openbb_terminal/forecast/theta_model.py b/openbb_terminal/forecast/theta_model.py
index 77af956c483..0f3f1c1ebe3 100644
--- a/openbb_terminal/forecast/theta_model.py
+++ b/openbb_terminal/forecast/theta_model.py
@@ -8,7 +8,7 @@ from typing import List, Optional, Tuple, Union
 import numpy as np
 import pandas as pd
 from darts import TimeSeries
-from darts.metrics import mape, rmse, mse, smape  # noqa: I001
+from darts.metrics import mape, mse, rmse, smape
 from darts.models import Theta
 from darts.utils.utils import SeasonalityMode
 from statsmodels.tools.sm_exceptions import ConvergenceWarning