TY - JOUR
T1 - Forecasting stock market volatility using (non-linear) Garch models
AU - Franses, Philip Hans
AU - Van Dijk, Dick
PY - 1996/4
Y1 - 1996/4
N2 - In this paper we study the performance of the GARCH model and two of its non-linear modifications to forecast weekly stock market volatility. The models are the Quadratic GARCH (Engle and Ng, 1993) and the Glosten, Jagannathan and Runkle (1992) models which have been proposed to describe, for example, the often observed negative skewness in stock market indices. We find that the QGARCH model is best when the estimation sample does not contain extreme observations such as the 1987 stock market crash and that the GJR model cannot be recommended for forecasting.
AB - In this paper we study the performance of the GARCH model and two of its non-linear modifications to forecast weekly stock market volatility. The models are the Quadratic GARCH (Engle and Ng, 1993) and the Glosten, Jagannathan and Runkle (1992) models which have been proposed to describe, for example, the often observed negative skewness in stock market indices. We find that the QGARCH model is best when the estimation sample does not contain extreme observations such as the 1987 stock market crash and that the GJR model cannot be recommended for forecasting.
UR - http://www.scopus.com/inward/record.url?scp=0000557541&partnerID=8YFLogxK
U2 - 10.1002/(sici)1099-131x(199604)15:3<229::aid-for620>3.0.co;2-3
DO - 10.1002/(sici)1099-131x(199604)15:3<229::aid-for620>3.0.co;2-3
M3 - Article
AN - SCOPUS:0000557541
SN - 0277-6693
VL - 15
SP - 229
EP - 235
JO - Journal of Forecasting
JF - Journal of Forecasting
IS - 3
ER -