# Video Lecture for GARCH

GARCH, Generallized AutoRegressive Conditional Heteroskedasticity, is one of the popular methods of estimating volatility in finance.

GARCH estimates volatility similar to EWMA, however, it adds more information to the series related to mean reversion. Also some people use both EWMA and GARCH, EWMA has been widely superceded by GARCH.

There are three main steps in the GARCH process:

1. Estimate the best-fitting autoregressive model 2. Calculate autocorrelations of the error term 3. Test for significance

The following video demonstrates how GARCH(1,1) can be used to forecast volatility.

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