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Version: v5

unitroot_test

Get unit root test results for a data series.

Applies the Augmented Dickey-Fuller (ADF) test, whose null hypothesis is the presence of a unit root, and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, whose null hypothesis is stationarity. Together they characterize whether the series is stationary.

Examples​

from openbb import obb
obb.quantitative.unitroot_test(target='close', 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​

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

target: str
Name of the column to analyze.

fuller_reg: str
Default: c
Constant/trend terms for the ADF test: 'c' constant, 'ct' constant and trend, 'ctt' constant, linear and quadratic trend, 'n' no constant or trend.

kpss_reg: str
Default: c
Null hypothesis for the KPSS test: 'c' level-stationary, 'ct' trend-stationary.

maxlag: int
Maximum lag for the ADF test. If None, a data-dependent default is used.

autolag: str
Default: AIC
Lag-selection method for the ADF test: 'AIC', 'BIC', or 't-stat'; None uses maxlag directly without selection.

nlags: int | str
Default: auto
Lags for the KPSS variance estimator: 'auto', 'legacy', or an explicit non-negative integer.

Returns​

results: UnitRootData

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​

adf_statistic: float
Augmented Dickey-Fuller test statistic.

adf_p_value: float
p-value of the ADF test.

adf_nlags: int
Number of lags used in the ADF test.

adf_nobs: int
Number of observations used in the ADF test.

adf_icbest: float
Best information criterion value of the ADF test (None when autolag is disabled).

kpss_statistic: float
KPSS test statistic.

kpss_p_value: float
p-value of the KPSS test.

kpss_nlags: int
Number of lags used in the KPSS test.

kpss_p_value_interpolated: bool
False when the KPSS p-value is clamped to a table boundary (the true p-value is more extreme than reported).

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