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Performance of GARCH models in forecasting stock market volatility.


Citation

Choo, Wei Chong and Ahmad, Muhammad Idrees and Abdullah, Mat Yusoff (1999) Performance of GARCH models in forecasting stock market volatility. Journal of Forecasting, 18 (5). pp. 333-343. ISSN 1099-131X

Abstract / Synopsis

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.


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Additional Metadata

Item Type: Article
Subject: Finance - Mathematical models
Subject: Stock price forecasting - Mathematical models.
Subject: Investments - Mathematical models.
Divisions: Faculty of Economics and Management
Publisher: John Wiley and Sons
Keywords: Forecasting volatility; GARCH; Time-series; Rate of returns.
Depositing User: Emelda Mohd Hamid
Date Deposited: 04 Jun 2013 09:46
Last Modified: 27 Nov 2015 10:35
URI: http://psasir.upm.edu.my/id/eprint/16140
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