ols_regression_summary

Perform Ordinary Least Squares (OLS) regression.

This returns the summary object from statsmodels.

Examples

from openbb import obb
# Perform Ordinary Least Squares (OLS) regression and return the summary.
stock_data = obb.equity.price.historical(symbol='TSLA', start_date='2023-01-01', provider='fmp').to_df()
obb.econometrics.ols_regression_summary(data=stock_data, y_column="close", x_columns=["open", "high", "low"])
obb.econometrics.ols_regression_summary(y_column='close', x_columns=['open', 'high', 'low'], data=[{'date': '2023-01-02', 'open': 110.0, 'high': 120.0, 'low': 100.0, 'close': 115.0, 'volume': 10000.0}, {'date': '2023-01-03', 'open': 165.0, 'high': 180.0, 'low': 150.0, 'close': 172.5, 'volume': 15000.0}, {'date': '2023-01-04', 'open': 146.67, 'high': 160.0, 'low': 133.33, 'close': 153.33, 'volume': 13333.33}, {'date': '2023-01-05', 'open': 137.5, 'high': 150.0, 'low': 125.0, 'close': 143.75, 'volume': 12500.0}, {'date': '2023-01-06', 'open': 132.0, 'high': 144.0, 'low': 120.0, 'close': 138.0, 'volume': 12000.0}])

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Parameters

• standard

Name	Type	Description	Default	Optional
data	List[Data]	Input dataset.		False
y_column	str	Target column.		False
x_columns	List[str]	List of columns to use as exogenous variables.		False

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Returns

OBBject
    Data