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https://github.com/OpenBB-finance/OpenBB.git
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fb42272c81
* add demark * add clenow * add model examples Co-authored-by: James Maslek <jmaslek11@gmail.com>
757 lines
21 KiB
Python
757 lines
21 KiB
Python
"""Momentum View"""
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__docformat__ = "numpy"
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import logging
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import os
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from typing import Optional, List
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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from pandas.plotting import register_matplotlib_converters
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import mplfinance as mpf
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from openbb_terminal.config_terminal import theme
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from openbb_terminal.common.technical_analysis import momentum_model
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from openbb_terminal.config_plot import PLOT_DPI
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.helper_funcs import (
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export_data,
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plot_autoscale,
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reindex_dates,
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is_valid_axes_count,
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print_rich_table,
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)
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from openbb_terminal.rich_config import console
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from openbb_terminal.common.technical_analysis import ta_helpers
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logger = logging.getLogger(__name__)
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register_matplotlib_converters()
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@log_start_end(log=logger)
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def display_cci(
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data: pd.DataFrame,
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window: int = 14,
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scalar: float = 0.0015,
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symbol: str = "",
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export: str = "",
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external_axes: Optional[List[plt.Axes]] = None,
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):
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"""Plots CCI Indicator
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Parameters
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----------
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data : pd.DataFrame
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Dataframe of OHLC
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window : int
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Length of window
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scalar : float
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Scalar variable
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symbol : str
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Stock ticker
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export : str
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Format to export data
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external_axes : Optional[List[plt.Axes]], optional
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External axes (2 axes are expected in the list), by default None
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"""
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df_ta = momentum_model.cci(data, window, scalar)
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plot_data = pd.merge(data, df_ta, how="outer", left_index=True, right_index=True)
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plot_data = reindex_dates(plot_data)
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# This plot has 2 axes
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if external_axes is None:
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_, axes = plt.subplots(
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2, 1, figsize=plot_autoscale(), sharex=True, dpi=PLOT_DPI
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)
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(ax1, ax2) = axes
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elif is_valid_axes_count(external_axes, 2):
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(ax1, ax2) = external_axes
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else:
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return
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close_col = ta_helpers.check_columns(data)
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if close_col is None:
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return
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ax1.set_title(f"{symbol} CCI")
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ax1.plot(
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plot_data.index,
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plot_data[close_col].values,
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)
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ax1.set_xlim(plot_data.index[0], plot_data.index[-1])
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ax1.set_ylabel("Share Price ($)")
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theme.style_primary_axis(
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ax1,
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data_index=plot_data.index.to_list(),
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tick_labels=plot_data["date"].to_list(),
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)
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ax2.plot(plot_data.index, plot_data[df_ta.columns[0]].values)
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ax2.set_xlim(plot_data.index[0], plot_data.index[-1])
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ax2.axhspan(100, ax2.get_ylim()[1], facecolor=theme.down_color, alpha=0.2)
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ax2.axhspan(ax2.get_ylim()[0], -100, facecolor=theme.up_color, alpha=0.2)
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theme.style_primary_axis(
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ax2,
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data_index=plot_data.index.to_list(),
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tick_labels=plot_data["date"].to_list(),
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)
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ax3 = ax2.twinx()
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ax3.set_ylim(ax2.get_ylim())
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ax3.axhline(100, color=theme.down_color, ls="--")
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ax3.axhline(-100, color=theme.up_color, ls="--")
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theme.style_twin_axis(ax3)
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ax2.set_yticks([-100, 100])
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ax2.set_yticklabels(["OVERSOLD", "OVERBOUGHT"])
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if external_axes is None:
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theme.visualize_output()
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"cci",
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df_ta,
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)
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@log_start_end(log=logger)
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def display_macd(
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data: pd.Series,
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n_fast: int = 12,
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n_slow: int = 26,
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n_signal: int = 9,
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symbol: str = "",
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export: str = "",
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external_axes: Optional[List[plt.Axes]] = None,
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):
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"""Plots MACD signal
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Parameters
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----------
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data : pd.Series
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Values to input
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n_fast : int
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Fast period
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n_slow : int
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Slow period
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n_signal : int
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Signal period
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symbol : str
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Stock ticker
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export : str
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Format to export data
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external_axes : Optional[List[plt.Axes]], optional
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External axes (2 axes are expected in the list), by default None
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"""
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df_ta = momentum_model.macd(data, n_fast, n_slow, n_signal)
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plot_data = pd.merge(data, df_ta, how="outer", left_index=True, right_index=True)
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plot_data = reindex_dates(plot_data)
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# This plot has 2 axes
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if external_axes is None:
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_, axes = plt.subplots(
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2, 1, figsize=plot_autoscale(), sharex=True, dpi=PLOT_DPI
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)
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(ax1, ax2) = axes
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elif is_valid_axes_count(external_axes, 2):
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(ax1, ax2) = external_axes
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else:
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return
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ax1.set_title(f"{symbol} MACD")
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ax1.plot(plot_data.index, plot_data.iloc[:, 1].values)
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ax1.set_xlim(plot_data.index[0], plot_data.index[-1])
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ax1.set_ylabel("Share Price ($)")
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theme.style_primary_axis(
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ax1,
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data_index=plot_data.index.to_list(),
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tick_labels=plot_data["date"].to_list(),
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)
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ax2.plot(plot_data.index, plot_data.iloc[:, 2].values)
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ax2.plot(
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plot_data.index,
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plot_data.iloc[:, 4].values,
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color=theme.down_color,
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)
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ax2.bar(
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plot_data.index,
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plot_data.iloc[:, 3].values,
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width=theme.volume_bar_width,
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color=theme.up_color,
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)
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ax2.legend(
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[
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f"MACD Line {plot_data.columns[2]}",
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f"Signal Line {plot_data.columns[4]}",
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f"Histogram {plot_data.columns[3]}",
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],
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loc=2,
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prop={"size": 6},
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)
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ax2.set_xlim(plot_data.index[0], plot_data.index[-1])
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theme.style_primary_axis(
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ax2,
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data_index=plot_data.index.to_list(),
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tick_labels=plot_data["date"].to_list(),
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)
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if external_axes is None:
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theme.visualize_output()
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"macd",
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df_ta,
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)
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@log_start_end(log=logger)
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def display_rsi(
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data: pd.Series,
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window: int = 14,
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scalar: float = 100.0,
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drift: int = 1,
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symbol: str = "",
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export: str = "",
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external_axes: Optional[List[plt.Axes]] = None,
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):
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"""Plots RSI Indicator
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Parameters
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----------
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data : pd.Series
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Values to input
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window : int
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Length of window
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scalar : float
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Scalar variable
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drift : int
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Drift variable
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symbol : str
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Stock ticker
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export : str
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Format to export data
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external_axes : Optional[List[plt.Axes]], optional
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External axes (2 axes are expected in the list), by default None
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"""
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if isinstance(data, pd.DataFrame):
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console.print("[red]Please send a series and not a dataframe[/red]\n")
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return
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df_ta = momentum_model.rsi(data, window, scalar, drift)
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# This plot has 2 axes
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if external_axes is None:
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_, axes = plt.subplots(
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2, 1, figsize=plot_autoscale(), sharex=True, dpi=PLOT_DPI
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)
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(ax1, ax2) = axes
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elif is_valid_axes_count(external_axes, 2):
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(ax1, ax2) = external_axes
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else:
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return
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plot_data = pd.merge(data, df_ta, how="outer", left_index=True, right_index=True)
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plot_data = reindex_dates(plot_data)
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ax1.plot(plot_data.index, plot_data.iloc[:, 1].values)
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ax1.set_title(f"{symbol} RSI{window}")
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ax1.set_xlim(plot_data.index[0], plot_data.index[-1])
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ax1.set_ylabel("Share Price ($)")
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theme.style_primary_axis(
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ax=ax1,
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data_index=plot_data.index.to_list(),
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tick_labels=plot_data["date"].to_list(),
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)
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ax2.plot(plot_data.index, plot_data[df_ta.columns[0]].values)
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ax2.set_xlim(plot_data.index[0], plot_data.index[-1])
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ax2.axhspan(0, 30, facecolor=theme.up_color, alpha=0.2)
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ax2.axhspan(70, 100, facecolor=theme.down_color, alpha=0.2)
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ax2.set_ylim([0, 100])
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theme.style_primary_axis(
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ax=ax2,
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data_index=plot_data.index.to_list(),
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tick_labels=plot_data["date"].to_list(),
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)
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ax3 = ax2.twinx()
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ax3.set_ylim(ax2.get_ylim())
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ax3.axhline(30, color=theme.up_color, ls="--")
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ax3.axhline(70, color=theme.down_color, ls="--")
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ax2.set_yticks([30, 70])
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ax2.set_yticklabels(["OVERSOLD", "OVERBOUGHT"])
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if external_axes is None:
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theme.visualize_output()
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"rsi",
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df_ta,
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)
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@log_start_end(log=logger)
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def display_stoch(
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data: pd.DataFrame,
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fastkperiod: int = 14,
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slowdperiod: int = 3,
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slowkperiod: int = 3,
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symbol: str = "",
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export: str = "",
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external_axes: Optional[List[plt.Axes]] = None,
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) -> None:
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"""Plots stochastic oscillator signal
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Parameters
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----------
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data : pd.DataFrame
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Dataframe of OHLC prices
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fastkperiod : int
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Fast k period
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slowdperiod : int
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Slow d period
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slowkperiod : int
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Slow k period
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symbol : str
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Stock ticker symbol
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export : str
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Format to export data
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external_axes : Optional[List[plt.Axes]], optional
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External axes (3 axes are expected in the list), by default None
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"""
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close_col = ta_helpers.check_columns(data)
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if close_col is None:
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return
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df_ta = momentum_model.stoch(
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data,
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fastkperiod,
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slowdperiod,
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slowkperiod,
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)
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# This plot has 3 axes
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if not external_axes:
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_, axes = plt.subplots(
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2, 1, sharex=True, figsize=plot_autoscale(), dpi=PLOT_DPI
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)
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ax1, ax2 = axes
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ax3 = ax2.twinx()
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elif is_valid_axes_count(external_axes, 3):
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(ax1, ax2, ax3) = external_axes
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else:
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return
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plot_data = pd.merge(data, df_ta, how="outer", left_index=True, right_index=True)
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plot_data = reindex_dates(plot_data)
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ax1.plot(plot_data.index, plot_data[close_col].values)
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ax1.set_title(f"Stochastic Relative Strength Index (STOCH RSI) on {symbol}")
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ax1.set_xlim(plot_data.index[0], plot_data.index[-1])
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ax1.set_ylabel("Share Price ($)")
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theme.style_primary_axis(
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ax1,
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data_index=plot_data.index.to_list(),
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tick_labels=plot_data["date"].to_list(),
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)
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ax2.plot(plot_data.index, plot_data[df_ta.columns[0]].values)
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ax2.plot(plot_data.index, plot_data[df_ta.columns[1]].values, ls="--")
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ax2.set_xlim(plot_data.index[0], plot_data.index[-1])
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theme.style_primary_axis(
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ax2,
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data_index=plot_data.index.to_list(),
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tick_labels=plot_data["date"].to_list(),
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)
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ax3.set_ylim(ax2.get_ylim())
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ax3.axhspan(80, 100, facecolor=theme.down_color, alpha=0.2)
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ax3.axhspan(0, 20, facecolor=theme.up_color, alpha=0.2)
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ax3.axhline(80, color=theme.down_color, ls="--")
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ax3.axhline(20, color=theme.up_color, ls="--")
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theme.style_twin_axis(ax3)
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ax2.set_yticks([20, 80])
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ax2.set_yticklabels(["OVERSOLD", "OVERBOUGHT"])
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ax2.legend(
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[f"%K {df_ta.columns[0]}", f"%D {df_ta.columns[1]}"],
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loc=2,
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prop={"size": 6},
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)
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if external_axes is None:
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theme.visualize_output()
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"stoch",
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df_ta,
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)
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@log_start_end(log=logger)
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def display_fisher(
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data: pd.DataFrame,
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window: int = 14,
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symbol: str = "",
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export: str = "",
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external_axes: Optional[List[plt.Axes]] = None,
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):
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"""Plots Fisher Indicator
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Parameters
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----------
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data : pd.DataFrame
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Dataframe of OHLC prices
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window : int
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Length of window
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symbol : str
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Ticker string
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export : str
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Format to export data
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external_axes : Optional[List[plt.Axes]], optional
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External axes (3 axes are expected in the list), by default None
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"""
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df_ta = momentum_model.fisher(data, window)
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if df_ta.empty:
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return
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plot_data = pd.merge(data, df_ta, how="outer", left_index=True, right_index=True)
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plot_data = reindex_dates(plot_data)
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# This plot has 3 axes
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if not external_axes:
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_, axes = plt.subplots(
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2, 1, sharex=True, figsize=plot_autoscale(), dpi=PLOT_DPI
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)
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ax1, ax2 = axes
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ax3 = ax2.twinx()
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elif is_valid_axes_count(external_axes, 3):
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(ax1, ax2, ax3) = external_axes
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else:
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return
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ax1.set_title(f"{symbol} Fisher Transform")
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close_col = ta_helpers.check_columns(data)
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if close_col is None:
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return
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ax1.plot(plot_data.index, plot_data[close_col].values)
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ax1.set_xlim(plot_data.index[0], plot_data.index[-1])
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ax1.set_ylabel("Price")
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theme.style_primary_axis(
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ax1,
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data_index=plot_data.index.to_list(),
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tick_labels=plot_data["date"].to_list(),
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)
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ax2.plot(
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plot_data.index,
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plot_data[df_ta.columns[0]].values,
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label="Fisher",
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)
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ax2.plot(
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plot_data.index,
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plot_data[df_ta.columns[1]].values,
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label="Signal",
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)
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ax2.set_xlim(plot_data.index[0], plot_data.index[-1])
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theme.style_primary_axis(
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ax2,
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data_index=plot_data.index.to_list(),
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tick_labels=plot_data["date"].to_list(),
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)
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ax3.set_ylim(ax2.get_ylim())
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ax3.axhspan(2, ax2.get_ylim()[1], facecolor=theme.down_color, alpha=0.2)
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ax3.axhspan(ax2.get_ylim()[0], -2, facecolor=theme.up_color, alpha=0.2)
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ax3.axhline(2, color=theme.down_color, ls="--")
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ax3.axhline(-2, color=theme.up_color, ls="--")
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theme.style_twin_axis(ax3)
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ax2.set_yticks([-2, 0, 2])
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ax2.set_yticklabels(["-2 STDEV", "0", "+2 STDEV"])
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ax2.legend(loc=2, prop={"size": 6})
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if external_axes is None:
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theme.visualize_output()
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"fisher",
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df_ta,
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)
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@log_start_end(log=logger)
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def display_cg(
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data: pd.Series,
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window: int = 14,
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symbol: str = "",
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export: str = "",
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external_axes: Optional[List[plt.Axes]] = None,
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):
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"""Plots center of gravity Indicator
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Parameters
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----------
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data : pd.Series
|
|
Series of values
|
|
window : int
|
|
Length of window
|
|
symbol : str
|
|
Stock ticker
|
|
export : str
|
|
Format to export data
|
|
external_axes : Optional[List[plt.Axes]], optional
|
|
External axes (2 axes are expected in the list), by default None
|
|
"""
|
|
df_ta = momentum_model.cg(data, window)
|
|
plot_data = pd.merge(data, df_ta, how="outer", left_index=True, right_index=True)
|
|
plot_data = reindex_dates(plot_data)
|
|
|
|
# This plot has 2 axes
|
|
if external_axes is None:
|
|
_, axes = plt.subplots(
|
|
2, 1, figsize=plot_autoscale(), sharex=True, dpi=PLOT_DPI
|
|
)
|
|
(ax1, ax2) = axes
|
|
elif is_valid_axes_count(external_axes, 2):
|
|
(ax1, ax2) = external_axes
|
|
else:
|
|
return
|
|
|
|
ax1.set_title(f"{symbol} Centre of Gravity")
|
|
ax1.plot(plot_data.index, plot_data[data.name].values)
|
|
ax1.set_xlim(plot_data.index[0], plot_data.index[-1])
|
|
ax1.set_ylabel("Share Price ($)")
|
|
theme.style_primary_axis(
|
|
ax1,
|
|
data_index=plot_data.index.to_list(),
|
|
tick_labels=plot_data["date"].to_list(),
|
|
)
|
|
|
|
ax2.plot(plot_data.index, plot_data[df_ta.columns[0]].values, label="CG")
|
|
# shift cg 1 bar forward for signal
|
|
signal = np.roll(plot_data[df_ta.columns[0]].values, 1)
|
|
ax2.plot(plot_data.index, signal, label="Signal")
|
|
ax2.set_xlim(plot_data.index[0], plot_data.index[-1])
|
|
ax2.legend()
|
|
theme.style_primary_axis(
|
|
ax2,
|
|
data_index=plot_data.index.to_list(),
|
|
tick_labels=plot_data["date"].to_list(),
|
|
)
|
|
|
|
if external_axes is None:
|
|
theme.visualize_output()
|
|
|
|
export_data(
|
|
export,
|
|
os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
|
|
"cg",
|
|
df_ta,
|
|
)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
def display_clenow_momentum(
|
|
data: pd.Series,
|
|
symbol: str = "",
|
|
window: int = 90,
|
|
export: str = "",
|
|
external_axes: Optional[List[plt.Axes]] = None,
|
|
):
|
|
"""Prints table and plots clenow momentum
|
|
|
|
Parameters
|
|
----------
|
|
data : pd.Series
|
|
Series of values
|
|
symbol : str
|
|
Symbol that the data corresponds to
|
|
window : int
|
|
Length of window
|
|
export : str
|
|
Format to export data
|
|
external_axes : Optional[List[plt.Axes]], optional
|
|
External axes (2 axes are expected in the list), by default None
|
|
|
|
Examples
|
|
--------
|
|
>>> from openbb_terminal.sdk import openbb
|
|
>>> df = openbb.stocks.load("AAPL")
|
|
>>> openbb.ta.clenow_chart(df["Close"])
|
|
"""
|
|
r2, coef, fit_data = momentum_model.clenow_momentum(data, window)
|
|
|
|
df = pd.DataFrame.from_dict(
|
|
{
|
|
"R^2": f"{r2:.5f}",
|
|
"Fit Coef": f"{coef:.5f}",
|
|
"Factor": f"{coef * r2:.5f}",
|
|
},
|
|
orient="index",
|
|
)
|
|
print_rich_table(
|
|
df,
|
|
show_index=True,
|
|
headers=[""],
|
|
title=f"Clenow Exponential Regression Factor on {symbol}",
|
|
show_header=False,
|
|
)
|
|
|
|
# This plot has 2 axes
|
|
if external_axes is None:
|
|
_, ax1 = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
|
|
|
|
elif is_valid_axes_count(external_axes, 1):
|
|
ax1 = external_axes
|
|
else:
|
|
return
|
|
|
|
ax1.plot(data.index, np.log(data.values))
|
|
ax1.plot(data.index[-window:], fit_data, linewidth=2)
|
|
|
|
ax1.set_title(f"Clenow Momentum Exponential Regression on {symbol}")
|
|
ax1.set_xlim(data.index[0], data.index[-1])
|
|
ax1.set_ylabel("Log Price")
|
|
theme.style_primary_axis(
|
|
ax1,
|
|
)
|
|
if external_axes is None:
|
|
theme.visualize_output()
|
|
|
|
export_data(
|
|
export,
|
|
os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
|
|
"clenow",
|
|
)
|
|
|
|
|
|
def display_demark(
|
|
data: pd.DataFrame,
|
|
symbol: str = "",
|
|
min_to_show: int = 5,
|
|
export: str = "",
|
|
external_axes: Optional[List[plt.Axes]] = None,
|
|
):
|
|
"""Plot demark sequential indicator
|
|
|
|
Parameters
|
|
----------
|
|
data : pd.DataFrame
|
|
DataFrame of values
|
|
symbol : str
|
|
Symbol that the data corresponds to
|
|
min_to_show: int
|
|
Minimum value to show
|
|
export : str
|
|
Format to export data
|
|
external_axes : Optional[List[plt.Axes]], optional
|
|
External axes (1 axes are expected in the list), by default None
|
|
|
|
Examples
|
|
--------
|
|
>>> from openbb_terminal.sdk import openbb
|
|
>>> df = openbb.stocks.load("AAPL")
|
|
>>> openbb.ta.demark_chart(df)
|
|
"""
|
|
close_col = ta_helpers.check_columns(data, high=False, low=False)
|
|
if close_col is None:
|
|
return
|
|
demark_df = momentum_model.demark_seq(data[close_col])
|
|
demark_df.index = data.index
|
|
|
|
stock_data = data.copy()
|
|
stock_data["up"] = demark_df.TD_SEQ_UPa
|
|
stock_data["down"] = demark_df.TD_SEQ_DNa
|
|
|
|
# MPLfinance can do series of markers :)
|
|
markersUP = (
|
|
stock_data["up"]
|
|
.apply(lambda x: f"${x}$" if x > min_to_show else None)
|
|
.to_list()
|
|
)
|
|
markersDOWN = (
|
|
stock_data["down"]
|
|
.apply(lambda x: f"${x}$" if x > min_to_show else None)
|
|
.to_list()
|
|
)
|
|
|
|
adp = [
|
|
mpf.make_addplot(
|
|
0.98 * stock_data["Low"],
|
|
type="scatter",
|
|
markersize=30,
|
|
marker=markersDOWN,
|
|
color="r",
|
|
),
|
|
mpf.make_addplot(
|
|
1.012 * stock_data["High"],
|
|
type="scatter",
|
|
markersize=30,
|
|
marker=markersUP,
|
|
color="b",
|
|
),
|
|
]
|
|
|
|
# Stuff for mplfinance
|
|
candle_chart_kwargs = {
|
|
"type": "ohlc",
|
|
"style": theme.mpf_style,
|
|
"volume": False,
|
|
"addplot": adp,
|
|
"xrotation": theme.xticks_rotation,
|
|
"scale_padding": {"left": 0.3, "right": 1, "top": 0.8, "bottom": 0.8},
|
|
"update_width_config": {
|
|
"candle_linewidth": 0.6,
|
|
"candle_width": 0.8,
|
|
"volume_linewidth": 0.8,
|
|
"volume_width": 0.8,
|
|
},
|
|
"warn_too_much_data": 10000,
|
|
}
|
|
if external_axes is None:
|
|
candle_chart_kwargs["returnfig"] = True
|
|
candle_chart_kwargs["figratio"] = (10, 7)
|
|
candle_chart_kwargs["figscale"] = 1.10
|
|
candle_chart_kwargs["figsize"] = plot_autoscale()
|
|
candle_chart_kwargs["warn_too_much_data"] = 100_000
|
|
|
|
fig, _ = mpf.plot(stock_data, **candle_chart_kwargs)
|
|
fig.suptitle(
|
|
f"{symbol} Demark Sequential",
|
|
x=0.055,
|
|
y=0.965,
|
|
horizontalalignment="left",
|
|
)
|
|
theme.visualize_output(force_tight_layout=False)
|
|
|
|
else:
|
|
if len(external_axes) != 1:
|
|
logger.error("Expected list of one axis item.")
|
|
console.print("[red]Expected list of 1 axis items.\n[/red]")
|
|
ax1 = external_axes
|
|
candle_chart_kwargs["ax"] = ax1
|
|
mpf.plot(stock_data, **candle_chart_kwargs)
|
|
|
|
export_data(
|
|
export,
|
|
os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
|
|
"demark",
|
|
stock_data,
|
|
)
|