Two stages fitting techniques using generalized lambda distribution: application on Malaysian financial return
The underline distribution assumption used in the analysis of share market returns is crucial in risk management. An important aspect related to stock return modelling is to obtain accurate prediction. This paper presents an innovative fitting method called two stages (TS) method for modelling daily...
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my.utm.911122021-05-31T13:29:30Z http://eprints.utm.my/id/eprint/91112/ Two stages fitting techniques using generalized lambda distribution: application on Malaysian financial return Marsani, Muhammad Fadhil Shabri, Ani QA Mathematics The underline distribution assumption used in the analysis of share market returns is crucial in risk management. An important aspect related to stock return modelling is to obtain accurate prediction. This paper presents an innovative fitting method called two stages (TS) method for modelling daily stock returns. The proposed approach by first establishing trend in the series, and then separately performing L-moment estimation on the generalized lambda distribution (GLD) parameter. The performance of the TS-GLD models had been evaluated using Monte Carlo simulation and Malaysian Kuala Lumpur Composite Index (KLCI) returns from year 2001 to 2015. Based on k-sample Anderson darling goodness of fit test, the two stages GLD model in location parameter (GLD.1) performed well in all studied cases. The GLD.1 model benefits risk management by providing effective distribution fitting. Penerbit Universiti Kebangsaan Malaysia 2020-05 Article PeerReviewed Marsani, Muhammad Fadhil and Shabri, Ani (2020) Two stages fitting techniques using generalized lambda distribution: application on Malaysian financial return. Sains Malaysiana, 49 (5). pp. 1153-1164. ISSN 0126-6039 http://dx.doi.org/10.17576/jsm-2020-4905-21 |
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QA Mathematics Marsani, Muhammad Fadhil Shabri, Ani Two stages fitting techniques using generalized lambda distribution: application on Malaysian financial return |
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The underline distribution assumption used in the analysis of share market returns is crucial in risk management. An important aspect related to stock return modelling is to obtain accurate prediction. This paper presents an innovative fitting method called two stages (TS) method for modelling daily stock returns. The proposed approach by first establishing trend in the series, and then separately performing L-moment estimation on the generalized lambda distribution (GLD) parameter. The performance of the TS-GLD models had been evaluated using Monte Carlo simulation and Malaysian Kuala Lumpur Composite Index (KLCI) returns from year 2001 to 2015. Based on k-sample Anderson darling goodness of fit test, the two stages GLD model in location parameter (GLD.1) performed well in all studied cases. The GLD.1 model benefits risk management by providing effective distribution fitting. |
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Article |
author |
Marsani, Muhammad Fadhil Shabri, Ani |
author_facet |
Marsani, Muhammad Fadhil Shabri, Ani |
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Marsani, Muhammad Fadhil |
title |
Two stages fitting techniques using generalized lambda distribution: application on Malaysian financial return |
title_short |
Two stages fitting techniques using generalized lambda distribution: application on Malaysian financial return |
title_full |
Two stages fitting techniques using generalized lambda distribution: application on Malaysian financial return |
title_fullStr |
Two stages fitting techniques using generalized lambda distribution: application on Malaysian financial return |
title_full_unstemmed |
Two stages fitting techniques using generalized lambda distribution: application on Malaysian financial return |
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two stages fitting techniques using generalized lambda distribution: application on malaysian financial return |
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Penerbit Universiti Kebangsaan Malaysia |
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2020 |
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http://eprints.utm.my/id/eprint/91112/ http://dx.doi.org/10.17576/jsm-2020-4905-21 |
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