I have a time series Y that I know exhibits autocorrelation and heteroscedasticity. Using the estimate function, I fit a conditional mean and variance model to Y. I then use the infer function and get the residuals from the model fit to Y.
Two questions: 1) If the residuals exhibit autocorrelation, how should I change the conditional mean and variance model that was just fit (add more AR or MA lags?)? 2) If the residuals exhibit heteroscedasticity, how should I change the model (add more GARCH or ARCH terms to the variance model?)? Thank you.
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