TY  - JOUR
T1  - Performance of GARCH models in forecasting stock market volatility.
A1  - Choo, Wei Chong
LA  - English
LA  - English
LA  - English
PB  - John Wiley and Sons
YR  - 1999
UL  - http://discoverylib.upm.edu.my/discovery/Record/oai:psasir.upm.edu.my:16140
AB  - This paper studies the performance of GARCH model and its modifications, using the rate of returns from the daily stock market indices of the Kuala Lumpur Stock Exchange (KLSE) including Composite Index, Tins Index, Plantations Index, Properties Index, and Finance Index. The models
are stationary GARCH, unconstrained GARCH, non-negative GARCH, GARCH-M, exponential GARCH and integrated GARCH. The parameters of these models and variance processes are estimated jointly using the maximum likelihood method. The performance of the within-sample estimation is diagnosed using several goodness-of-fit statistics. We observed
that, among the models, even though exponential GARCH is not the best model in the goodness-of-fit statistics, it performs best in describing the often-observed skewness in stock market indices and in out-of-sample (one-step-ahead) forecasting. The integrated GARCH, on the other hand, is the
poorest model in both respects.
KW  - Finance - Mathematical models
KW  - Stock price forecasting - Mathematical models.
KW  - Investments - Mathematical models.
ER  -