autocorrelation
Perform the Durbin-Watson test for autocorrelation in regression residuals.
The Durbin-Watson statistic ranges from 0 to 4. A value near 2 suggests no autocorrelation; values toward 0 indicate positive autocorrelation and values toward 4 indicate negative autocorrelation.
Examples
from openbb import obb
obb.econometrics.autocorrelation(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.
Returns
results: AutocorrelationData
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
durbin_watson: float
Durbin-Watson statistic (near 2 = no autocorrelation).