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

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

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 Composi...

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Main Author: Choo, Wei Chong
Format: Thesis
Language:English
English
Published: 1998
Subjects:
GARCH model - Evaluation
Stock exchanges - Kuala Lumpur
Online Access:http://psasir.upm.edu.my/id/eprint/11298/1/FSAS_1998_1_A.pdf
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spelling my-upm-ir.112982012-05-09T01:14:39Z Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility 1998-04 Choo, Wei Chong 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. GARCH model - Evaluation Stock exchanges - Kuala Lumpur 1998-04 Thesis http://psasir.upm.edu.my/id/eprint/11298/ http://psasir.upm.edu.my/id/eprint/11298/1/FSAS_1998_1_A.pdf application/pdf en public masters Universiti Putra Malaysia GARCH model - Evaluation Stock exchanges - Kuala Lumpur Faculty of Environmental studies English
institution Universiti Putra Malaysia
collection PSAS Institutional Repository
language English
English
topic GARCH model - Evaluation
Stock exchanges - Kuala Lumpur
spellingShingle GARCH model - Evaluation
Stock exchanges - Kuala Lumpur

Choo, Wei Chong
Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility
description 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.
format Thesis
qualification_level Master's degree
author Choo, Wei Chong
author_facet Choo, Wei Chong
author_sort Choo, Wei Chong
title Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility
title_short Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility
title_full Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility
title_fullStr Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility
title_full_unstemmed Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility
title_sort generalised autoregressive conditional heteroscedasticity (garch) models for stock market volatility
granting_institution Universiti Putra Malaysia
granting_department Faculty of Environmental studies
publishDate 1998
url http://psasir.upm.edu.my/id/eprint/11298/1/FSAS_1998_1_A.pdf
_version_ 1747811236545822720

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