arch.unitroot.cointegration.EngleGrangerTestResults¶

class arch.unitroot.cointegration.EngleGrangerTestResults(stat: float, pvalue: float, crit_vals: pandas.Series, null: str = 'No Cointegration', alternative: str = 'Cointegration', trend: str = 'c', order: int = 2, adf: ADF | None = None, xsection: RegressionResults | None = None)[source]¶

Results class for Engle-Granger cointegration tests.

Parameters:¶

stat: float¶

The Engle-Granger test statistic.

pvalue: float¶

The pvalue of the Engle-Granger test statistic.

crit_vals: pandas.Series¶

The critical values of the Engle-Granger specific to the sample size and model dimension.

null: str = 'No Cointegration'¶

The null hypothesis.

alternative: str = 'Cointegration'¶

The alternative hypothesis.

trend: str = 'c'¶

The model’s trend description.

order: int = 2¶

The number of stochastic trends in the null distribution.

adf: ADF | None = None¶

The ADF instance used to perform the test and lag selection.

xsection: RegressionResults | None = None¶

The OLS results used in the cross-sectional regression.

Methods

plot([axes, title])	Plot the cointegration residuals.
summary()	Summary of test, containing statistic, p-value and critical values

Properties

alternative_hypothesis	The alternative hypothesis
cointegrating_vector	The estimated cointegrating vector.
critical_values	Critical Values
distribution_order	The number of stochastic trends under the null hypothesis.
lags	The number of lags used in the Augmented Dickey-Fuller regression.
max_lags	The maximum number of lags used in the lag-length selection.
name	Sets or gets the name of the cointegration test
null_hypothesis	The null hypothesis
pvalue	The p-value of the test statistic.
resid	The residual from the cointegrating regression.
rho	The estimated coefficient in the Dickey-Fuller Test
stat	The test statistic.
trend	The trend used in the cointegrating regression