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https://github.com/OpenBB-finance/OpenBB.git
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13283fbfce
* BIGGGG LINTING * fixing lints * fixing lints * black * very ruff * no export * fix hedge_view again * lints * platform lints * lints * black * black it @hjoaquim * fix some more linting --------- Co-authored-by: hjoaquim <h.joaquim@campus.fct.unl.pt>
99 lines
2.7 KiB
Python
99 lines
2.7 KiB
Python
"""Beta 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, Union
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import pandas as pd
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from openbb_terminal import OpenBBFigure
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.helper_funcs import export_data
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from openbb_terminal.rich_config import console
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from openbb_terminal.stocks.quantitative_analysis.beta_model import beta_model
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logger = logging.getLogger(__name__)
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@log_start_end(log=logger)
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def beta_view(
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symbol: str,
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ref_symbol: str,
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data: Optional[pd.DataFrame] = None,
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ref_data: Optional[pd.DataFrame] = None,
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interval: int = 1440,
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export: str = "",
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sheet_name: Optional[str] = None,
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external_axes: bool = False,
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) -> Union[None, OpenBBFigure]:
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"""Display the beta scatterplot + linear regression.
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Parameters
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----------
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symbol : str
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A ticker to calculate beta for
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ref_symbol : str
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A reference ticker symbol for the beta calculation (default in terminal is SPY)
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data : pd.DataFrame
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The selected ticker symbols price data
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ref_data : pd.DataFrame
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The reference ticker symbols price data
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interval: int
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The interval of the ref_data. This will ONLY be used if ref_data is None
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export : str
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Export dataframe data or plot to csv,json,xlsx,jpeg,pdf,png,svg file
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sheet_name : str
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Optionally specify the name of the sheet the data is exported to.
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external_axes : bool, optional
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Whether to return the figure object or not, by default False
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"""
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try:
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sr, rr, beta, alpha = beta_model(
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symbol, ref_symbol, data, ref_data, interval=interval
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)
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except Exception as e:
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if str(e) == "Invalid ref ticker":
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return console.print(str(e) + "\n")
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raise e
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beta_text = f"Raw Beta={round(beta, 2)}<br>Alpha={round(alpha, 2)}"
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fig = OpenBBFigure(
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xaxis_title=f"{ref_symbol} Returns (%)", yaxis_title=f"{symbol} Returns (%)"
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)
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fig.set_title(f"Beta of {symbol} with respect to {ref_symbol}")
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fig.add_scatter(x=rr, y=sr, mode="markers", name="Returns")
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fig.add_scatter(
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x=[min(rr), max(rr)],
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y=[x * beta + alpha for x in [min(rr), max(rr)]],
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mode="lines",
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name="Linear Regression",
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)
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fig.add_annotation(
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x=0.9,
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y=0.1,
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text=beta_text,
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xref="paper",
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yref="paper",
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xanchor="right",
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yanchor="bottom",
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)
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fig.update_layout(showlegend=False)
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df = pd.DataFrame({"sr": sr, "rr": rr})
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)),
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f"beta_alpha={alpha}_beta={beta}",
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df,
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sheet_name,
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fig,
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)
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return fig.show(external=external_axes)
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