Garch models is a methodological framework within econometrics and time series analysis designed to model and forecast the conditional variance of a stochastic process. This class of models is particularly significant for its ability to capture phenomena such as volatility clustering, where periods of high volatility tend to be followed by periods of high volatility, and vice versa.