ols_regression_summary

Perform Ordinary Least Squares (OLS) regression and return the fit summary.

Returns the model-level goodness-of-fit statistics - R-squared, F-statistic, information criteria, log-likelihood, and degrees of freedom - along with the full statsmodels text summary.

Examples

from openbb import obb
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}])

Parameters

• standard

data: Data | DataFrame | Series | dict | list | list[DataFrame] | list[Data] | list[Series] | ndarray
Input dataset.

y_column: str
Name of the dependent (target) column.

x_columns: list[str]
Names of the independent (exogenous) columns.

cov_type: str
Default: nonrobust
Covariance estimator for the standard errors: 'nonrobust', or heteroskedasticity-robust 'HC0', 'HC1', 'HC2', or 'HC3'.

---

Returns

results: OlsRegressionSummaryData

Serializable results.

provider: str

Provider name.

warnings: Optional[list[Warning_]]

List of warnings.

chart: Optional[Chart]

Chart object.

extra: dict[str, Any]

Extra info.

---

Data

• standard

r_squared: float
Coefficient of determination.

adjusted_r_squared: float
R-squared adjusted for the number of regressors.

f_statistic: float
F-statistic of the overall regression.

f_p_value: float
p-value of the F-statistic.

aic: float
Akaike Information Criterion.

bic: float
Bayesian Information Criterion.

log_likelihood: float
Log-likelihood of the fitted model.

nobs: int
Number of observations.

df_model: float
Model degrees of freedom.

df_residuals: float
Residual degrees of freedom.

summary: str
Full statsmodels text summary.