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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1998
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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 |