Stochastic mortality model in a state-space framework
The incorporation of the time-varying parameter in the mortality model has become one the main contributions in the actuarial field since it al- lows for the stochastic nature of the mortality rates. However, it has also become a growing concern among the researchers since the residu- als of the pro...
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| Format: | Article |
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Universiti Putra Malaysia
2019
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| _version_ | 1796864845979582464 |
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| author | Mohd. Nor, S. R. Yusof, F. Bahar, A. |
| author_facet | Mohd. Nor, S. R. Yusof, F. Bahar, A. |
| author_sort | Mohd. Nor, S. R. |
| collection | ePrints |
| description | The incorporation of the time-varying parameter in the mortality model has become one the main contributions in the actuarial field since it al- lows for the stochastic nature of the mortality rates. However, it has also become a growing concern among the researchers since the residu- als of the proposed model are evaluated independently. In this study, we extended the existing leading independent stochastic mortality model which is the O0Hare mortality model into the state-space representation of the O0Hare mortality model. The parameters of the extended model are estimated using the Expectation-Maximization algorithm of the max- imum likelihood estimation method. Using the Malaysian mortality data, we have found that our proposed model significantly improves the accu- racy of the in-sample fitting and the seven-year out-sample forecast as compared to the existing model considered. |
| first_indexed | 2024-03-05T20:48:00Z |
| format | Article |
| id | utm.eprints-89517 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T20:48:00Z |
| publishDate | 2019 |
| publisher | Universiti Putra Malaysia |
| record_format | dspace |
| spelling | utm.eprints-895172021-02-09T05:01:16Z http://eprints.utm.my/89517/ Stochastic mortality model in a state-space framework Mohd. Nor, S. R. Yusof, F. Bahar, A. QA Mathematics The incorporation of the time-varying parameter in the mortality model has become one the main contributions in the actuarial field since it al- lows for the stochastic nature of the mortality rates. However, it has also become a growing concern among the researchers since the residu- als of the proposed model are evaluated independently. In this study, we extended the existing leading independent stochastic mortality model which is the O0Hare mortality model into the state-space representation of the O0Hare mortality model. The parameters of the extended model are estimated using the Expectation-Maximization algorithm of the max- imum likelihood estimation method. Using the Malaysian mortality data, we have found that our proposed model significantly improves the accu- racy of the in-sample fitting and the seven-year out-sample forecast as compared to the existing model considered. Universiti Putra Malaysia 2019 Article PeerReviewed Mohd. Nor, S. R. and Yusof, F. and Bahar, A. (2019) Stochastic mortality model in a state-space framework. Malaysian Journal of Mathematical Sciences, 13 (2). pp. 251-264. ISSN 1823-8343 |
| spellingShingle | QA Mathematics Mohd. Nor, S. R. Yusof, F. Bahar, A. Stochastic mortality model in a state-space framework |
| title | Stochastic mortality model in a state-space framework |
| title_full | Stochastic mortality model in a state-space framework |
| title_fullStr | Stochastic mortality model in a state-space framework |
| title_full_unstemmed | Stochastic mortality model in a state-space framework |
| title_short | Stochastic mortality model in a state-space framework |
| title_sort | stochastic mortality model in a state space framework |
| topic | QA Mathematics |
| work_keys_str_mv | AT mohdnorsr stochasticmortalitymodelinastatespaceframework AT yusoff stochasticmortalitymodelinastatespaceframework AT bahara stochasticmortalitymodelinastatespaceframework |