Predictability Of The Klci Price Movement: Evidence From The Time Series Models
This study utilises autoregressive integrated moving average (ARIMA) time series models to predict the price movement of the Kuala Lumpur Composite Index (KLCI). ARIMAARCH models, which are ARIMA time series models with GARCH errors (relaxing the normality assumption), are also considered. All fitt...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
National Library Malaysia
2004
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/29608/1/Lim.pdf http://ir.unimas.my/id/eprint/29608/ http://intijournal.newinti.edu.my/ |
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| Summary: | This study utilises autoregressive integrated moving average (ARIMA) time series models to predict the price movement of the Kuala Lumpur Composite Index (KLCI). ARIMAARCH models, which are ARIMA time series
models with GARCH errors (relaxing the normality assumption), are also considered. All fitted models excluding those that exhibit nonstationary autoregressive roots are utilised to generate out-of-sample forecast over the forecast horizons of 1 day, 1 week, 1 month, 3
months, 6 months, 9 months and 1 year. |
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