An analysis of the flexibility of Asymmetric Power GARCH models

Abstract

The Asymmetric Power GARCH (APGARCH) model allows a wider class of power transformations than simply taking the absolute value or squaring the data as in classical heteroscedastic models. A dynamic estimation is used to compare the three GARCH families and examine their forecasting performances in a value-at-risk setting. The results suggest that the optimal power transformation obtained with the APGARCH model is virtually never statistically different from 1 or 2. Moreover, although some indices switch between these two values over the time, the measures of accuracy and efficiency used to assess the performance of VaR forecasts indicate that the additional flexibility brought by the APGARCH model provides little, if any, improvements for risk management.