Interactively assess whether a series has volatility clustering by inspecting correlograms of the squared residuals and by testing for significant ARCH lags.
Test for autocorrelation in the squared residuals, or conduct Engle’s ARCH test.
Estimate the ACF and PACF, or conduct the Ljung-Box Q-test.
This example shows how to estimate multiple linear regression models of time series data in the presence of heteroscedastic or autocorrelated (nonspherical) innovations.
Plot corrected confidence bands using Newey-West robust standard errors.
Change the bandwidth when estimating a HAC coefficient covariance, and compare estimates over varying bandwidths and kernels.
Convert between ARMAX and regression models with ARMA errors.
Create a composite conditional mean and variance model.