Prediction of Financial Downside-Risk with Heavy-Tailed Conditional Distributions

Abstract

The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution illustrates their usefulness in predicting the downside risk of financial assets in the context of modeling foreign exchange-rates and demonstrates their superiority over use of normal or Student's t GARCH models.

Keywords: Risk Management, Value at Risk, Density Forecasting, Predictive Likelihood

JEL Classification: C22, C51, G10