Exercise

Pick a winner based on AIC/BIC

In this exercise, you will practice using information criteria to choose a model with the best fit.

Information criteria intend to measure the trade-off between goodness of fit and model complexity. AIC and BIC are two commonly used information criteria for model selection. They both impose penalties on model with more parameters, or more complex models. The lower the AIC or BIC, the better the model.

A GJR-GARCH model and EGARCH model have been defined and fitted with the S&P 500 return data. Their results can be accessed in gjrgm_result and egarch_result respectively.

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Print the AIC in gjrgm_result and egarch_result respectively.
Print the BIC in gjrgm_result and egarch_result respectively.