Modeling and Forecasting Volatility of the Malaysian and the Singaporean Stock Indices using Asymmetric GARCH Models and Non-normal Densities

Mohd Nor, Abu Hassan Shaari and Shamiri, Ahmad (2007) Modeling and Forecasting Volatility of the Malaysian and the Singaporean Stock Indices using Asymmetric GARCH Models and Non-normal Densities. Malaysian Journal of Mathematical Sciences, 1 (1). pp. 83-102. ISSN 1823-8343

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Abstract

This paper examines and estimates the three GARCH(1,1) models (GARCH, EGARCH and GJR-GARCH) using daily price data. Two Asian stock indices KLCI and STI were studied using daily data over a 14-years period. The competing models include GARCH, EGARCH and GJR-GARCH using the Gaussian normal, Student-t and Generalized Error Distributions. The estimates showed that the forecasting performance of asymmetric GARCH Models (GJR-GARCH and EGARCH), especially when fattailed densities are taken into account in the conditional volatility, are better than symmetric GARCH. Moreover, it was found that the AR(1)-GJR model provides the best out-of-sample forecast for the Malaysian stock market, while AR(1)-EGARCH provides a better estimation for the Singaporean stock market.

Item Type:Article
Keyword:ARCH-Models, Asymmetry, Stock market indices and volatility modeling JEL classification: G14;C13;C22.
Faculty or Institute:Institute for Mathematical Research
Publisher:UPM Press
ID Code:12561
Deposited By: Najwani Amir Sariffudin
Deposited On:03 Jun 2011 07:07
Last Modified:27 May 2013 07:52

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