✦ LIBER ✦

The Volatility and Density Prediction Performance of Alternative GARCH Models

✍ Scribed by Teng-Hao Huang; Yaw-Huei Wang

Publisher: John Wiley and Sons
Year: 2011
Tongue: English
Weight: 174 KB
Volume: 31
Category: Article
ISSN: 0277-6693
DOI: 10.1002/for.1217

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✦ Synopsis

ABSTRACT

This study compares the volatility and density prediction performance of alternative GARCH models with different conditional distribution specifications. The conditional residuals are specified as normal, skewedHyphen;t or compound Poisson (jump) distribution based upon a nonlinear and asymmetric GARCH (NGARCH) model framework. The empirical results for the S&P 500 and FTSE 100 index returns suggest that the jump model outperforms all other models in terms of both volatility forecasting and density prediction. Nevertheless, the superiority of the nonHyphen;normal models is not always significant and diminished during the sample period on those occasions when volatility experiences an obvious structural change. Copyright © 2011 John Wiley & Sons, Ltd.

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