Developed in collaboration with Professor Andrei Kirilenko at MIT Sloan. This notebook gives an intro to ARCH and GARCH models, which are commonly used in volatility forecasting. We also cover using maximum likelihood estimation and Generalized Method of Moments (GMM) to estimate parameters for a GARCH model. GMM is a very cool technique that performs a parameter optimization using an objective function based on statistical moments of residuals, and is useful when your model does not have an easily derivable MLE.
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