Using bootstrapping to incorporate model error for risk-neutral pricing of longevity risk

Where mortality projection is concerned, it is essential to quantify the extent of the prediction error. This is especially important in light of the aggravating risk of longevity and as a result the increasing demand for longevity-linked products. In the literature so far, only parameter error and...

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Main Authors: Yang, B., Li, Ka Ki Jackie, Balasooriya, U.
Format: Journal Article
Published: Elsevier BV 2015
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/46974
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author Yang, B.
Li, Ka Ki Jackie
Balasooriya, U.
author_facet Yang, B.
Li, Ka Ki Jackie
Balasooriya, U.
author_sort Yang, B.
building Curtin Institutional Repository
collection Online Access
description Where mortality projection is concerned, it is essential to quantify the extent of the prediction error. This is especially important in light of the aggravating risk of longevity and as a result the increasing demand for longevity-linked products. In the literature so far, only parameter error and process error have been considered jointly while the issue of model error has yet been systematically studied. In this paper, we propose a method to account for process error, parameter error and model error in an integrated manner by modifying the semi-parametric bootstrapping technique. We apply the method to two data sets from the Continuous Mortality Investigation (CMI) and use the simulated scenarios to price the qq-forward contracts via the maximum entropy approach. We find that model selection has a significant impact on the risk-neutral valuation results and thus it is crucial to incorporate model error in mortality projection.
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publishDate 2015
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spelling curtin-20.500.11937-469742017-09-13T15:57:24Z Using bootstrapping to incorporate model error for risk-neutral pricing of longevity risk Yang, B. Li, Ka Ki Jackie Balasooriya, U. Risk-neutral pricing Longevity risk Model error Bootstrapping Maximum entropy method Where mortality projection is concerned, it is essential to quantify the extent of the prediction error. This is especially important in light of the aggravating risk of longevity and as a result the increasing demand for longevity-linked products. In the literature so far, only parameter error and process error have been considered jointly while the issue of model error has yet been systematically studied. In this paper, we propose a method to account for process error, parameter error and model error in an integrated manner by modifying the semi-parametric bootstrapping technique. We apply the method to two data sets from the Continuous Mortality Investigation (CMI) and use the simulated scenarios to price the qq-forward contracts via the maximum entropy approach. We find that model selection has a significant impact on the risk-neutral valuation results and thus it is crucial to incorporate model error in mortality projection. 2015 Journal Article http://hdl.handle.net/20.500.11937/46974 10.1016/j.insmatheco.2015.02.004 Elsevier BV restricted
spellingShingle Risk-neutral pricing
Longevity risk
Model error
Bootstrapping
Maximum entropy method
Yang, B.
Li, Ka Ki Jackie
Balasooriya, U.
Using bootstrapping to incorporate model error for risk-neutral pricing of longevity risk
title Using bootstrapping to incorporate model error for risk-neutral pricing of longevity risk
title_full Using bootstrapping to incorporate model error for risk-neutral pricing of longevity risk
title_fullStr Using bootstrapping to incorporate model error for risk-neutral pricing of longevity risk
title_full_unstemmed Using bootstrapping to incorporate model error for risk-neutral pricing of longevity risk
title_short Using bootstrapping to incorporate model error for risk-neutral pricing of longevity risk
title_sort using bootstrapping to incorporate model error for risk-neutral pricing of longevity risk
topic Risk-neutral pricing
Longevity risk
Model error
Bootstrapping
Maximum entropy method
url http://hdl.handle.net/20.500.11937/46974