FORECASTING STOCK-MARKET VOLATILITY USING (NONLINEAR) GARCH MODELS

In this paper we study the performance of the GARCH model and two of i ts non-linear modifications to forecast weekly stock market volatility . The models are the Quadratic GARCH (Engle and Ng, 1993) and the Glos ten, Jagannathan and Runkle (1992) models which have been proposed to describe, for example, the often observed negative skewness in stock m arket indices. We find that the QGARCH model is best when the estimati on sample does not contain extreme observations such as the 1987 stock market crash and that the GJR model cannot be recommended for forecas ting.