UPM Institutional Repository

Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility


Choo, Wei Chong (1998) Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility. Masters thesis, Universiti Putra Malaysia.


The performance of generalised autoregressive conditional heteroscedasticity (GARCH) model and its modifications in forecasting stock market volatility are evaluated using the rate of returns from the daily stock market indices of Kuala Lumpur Stock Exchange (KLSE). These indices include Composite Index, Tins Index, Plantations Index, Properties Index and Finance Index. The models are stationary GARCH, unconstrained GARCH, non-negative GARCH, GARCH in mean (GARCH-M), exponential GARCH (EGARCH) and integrated GARCH. The parameters of these models and variance processes are estimated jointly using maximum likelihood method. The performance of the within-sample estimation is assessed using several goodness-of-fit statistics and the accuracy of the out-of-sample forecasts is judged using mean squared error.

Download File

[img] PDF

Download (939kB)

Additional Metadata

Item Type: Thesis (Masters)
Subject: GARCH model - Evaluation
Subject: Stock exchanges - Kuala Lumpur
Call Number: FSAS 1998 1
Chairman Supervisor: Associate Professor Muhammad Idrees Ahmad, PhD
Divisions: Faculty of Environmental Studies
Depositing User: Mohd Nezeri Mohamad
Date Deposited: 18 Jul 2011 01:29
Last Modified: 09 May 2012 01:14
URI: http://psasir.upm.edu.my/id/eprint/11298
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item