Prediction of mortality rates using a model with stochastic parameters
Prediction of future mortality rates is crucial to insurance companies because they face longevity risks while providing retirement benefits to a population whose life expectancy is increasing. In the past literature, a time series model based on multivariate power-normal distribution has been appli...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing
2016
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| Subjects: | |
| Online Access: | http://eprints.sunway.edu.my/428/1/Pooi%20Ah%20Hin%205.pdf http://eprints.sunway.edu.my/428/ http://www.aip.scitation.org http://dx.doi.org/10.1063/1.4966106 |
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| Summary: | Prediction of future mortality rates is crucial to insurance companies because they face longevity risks while providing retirement benefits to a population whose life expectancy is increasing. In the past literature, a time series model based on multivariate power-normal distribution has been applied on mortality data from the United States for the years 1933 till 2000 to forecast the future mortality rates for the years 2001 till 2010. In this paper, a more dynamic approach based on the multivariate time series will be proposed where the model uses stochastic parameters that vary with time. The resulting prediction intervals obtained using the model with stochastic parameters perform better because apart from having good ability in covering the observed future mortality rates, they also tend to have distinctly shorter interval lengths. |
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