Long memory and asymmetric volatility behaviour of the Malaysian stock market: a statistical modelling approach
This paper analyzes the asymmetric long memory volatility dependency of the interday prices of Composite Index (CI) at Bursa Malaysia by using GARCH family models. The GARCH type models are used with the assumption that the innovations series follow either one of the following distributions: Gaussia...
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my-ukm.journal.39772012-03-28T01:22:18Z http://journalarticle.ukm.my/3977/ Long memory and asymmetric volatility behaviour of the Malaysian stock market: a statistical modelling approach Abu Hassan Shaari Mohd Nor, Chin , Wen Cheong This paper analyzes the asymmetric long memory volatility dependency of the interday prices of Composite Index (CI) at Bursa Malaysia by using GARCH family models. The GARCH type models are used with the assumption that the innovations series follow either one of the following distributions: Gaussian, Student -t and skewed Student -t. The stock returns' long memory dependency is determined using the Hurst parameter. The long memory and asymmetric volatility are modelled by fractionally integrated GARCH models. It is found that the asymmetric and long memory GARCH models with skewed student-t distribution give better predictive ability on the volatility of the Kuala Lumpur Composite Index (KLCI). Universiti Kebangsaan Malaysia 2006-07 Article PeerReviewed Abu Hassan Shaari Mohd Nor, and Chin , Wen Cheong (2006) Long memory and asymmetric volatility behaviour of the Malaysian stock market: a statistical modelling approach. Sains Malaysiana, 35 (1). pp. 67-73. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol35num1_2006/vol35num1_06page67-73.html |
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This paper analyzes the asymmetric long memory volatility dependency of the interday prices of Composite Index (CI) at Bursa Malaysia by using GARCH family models. The GARCH type models are used with the assumption that the innovations series follow either one of the following distributions: Gaussian, Student -t and skewed Student -t. The stock returns' long memory dependency is determined using the Hurst parameter. The long memory and asymmetric volatility are modelled by fractionally integrated GARCH models. It is found that the asymmetric and long memory GARCH models with skewed student-t distribution give better predictive ability on the volatility of the Kuala Lumpur Composite Index (KLCI). |
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Abu Hassan Shaari Mohd Nor, Chin , Wen Cheong |
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Abu Hassan Shaari Mohd Nor, Chin , Wen Cheong Long memory and asymmetric volatility behaviour of the Malaysian stock market: a statistical modelling approach |
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Abu Hassan Shaari Mohd Nor, Chin , Wen Cheong |
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Abu Hassan Shaari Mohd Nor, |
title |
Long memory and asymmetric volatility behaviour of the Malaysian stock market: a statistical modelling approach |
title_short |
Long memory and asymmetric volatility behaviour of the Malaysian stock market: a statistical modelling approach |
title_full |
Long memory and asymmetric volatility behaviour of the Malaysian stock market: a statistical modelling approach |
title_fullStr |
Long memory and asymmetric volatility behaviour of the Malaysian stock market: a statistical modelling approach |
title_full_unstemmed |
Long memory and asymmetric volatility behaviour of the Malaysian stock market: a statistical modelling approach |
title_sort |
long memory and asymmetric volatility behaviour of the malaysian stock market: a statistical modelling approach |
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Universiti Kebangsaan Malaysia |
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2006 |
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http://journalarticle.ukm.my/3977/ http://www.ukm.my/jsm/english_journals/vol35num1_2006/vol35num1_06page67-73.html |
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