White test

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In statistics, White’s test is a test which establishes whether the residual variance of a variable in a regression model is constant (homoscedasticity). To test for constant variance one regresses the squared residuals from a regression model onto the regressors, the cross-products of the regressors and the squared regressors. One then inspects the $R 2$ . If homoskedasticity is rejected one can use a GARCH model.

The LM test statistic is the product of the $R 2$ value and sample size. It follows a chi square distribution, with degrees of freedom equal to one less than the number of independent variables.

$\ LM = n \cdot R^2$