Mortality risk: modelling, evaluation and risk management

死亡风险:建模、评估和风险管理

基本信息

  • 批准号:
    RGPIN-2014-04682
  • 负责人:
  • 金额:
    $ 0.8万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2014
  • 资助国家:
    加拿大
  • 起止时间:
    2014-01-01 至 2015-12-31
  • 项目状态:
    已结题

项目摘要

Pensions are a top of mind issue as more and more reports discuss the potential huge deficit in Government social security and health systems, and the threat of bankruptcy in many union's retirement plans. One of the main culprits is the unprecedented and unanticipated increase in life expectancy. Although mortality prediction has been a traditional topic in actuarial science and demography, past experience shows that the causes of mortality improvement have not been well understood. Uncertainty in mortality changes has become a major challenge for government, insurance companies and pension planners in most countries. Stochastic mortality models may be used to study the impact of mortality risk on plans and products. This new perspective about mortality indicates that we need new models as well as new evaluation and risk management methodologies for mortality risk. My research is about these newly emerging research topics. My proposed research is both a continuation and an expansion of my current work and can be grouped into three broad areas of research projects. 1. Markovian mortality modelling approach and its applications a. In this study, we continue our work on developing biological-based mortality modelling and prediction approach. The biological-based aging process will be characterized using either direct information from physiological variables or indirect information about health such as medical expenditures at different ages to enhance the mortality modelling and improve predictions. The research outcome of this project will deepen our understanding on human aging and mortality improvement. The applications of our results will not only be in modelling mortality for life insurance and annuity pricing, but also for modeling health care needs and cost projection. b. While phase-type (PH) models are useful in many fields of application, it is notoriously difficult to obtain efficient parameter estimation for PH models. However, for special structured PH aging model, we normally can obtain analytic functional expression for the distribution, and this allows us to employ maximum likelihood method and fast Bayesian approach to obtain parametric estimation. Our objective in this area is to provide efficient estimation methods for data from different sources and customize the PH model for different application purposes. The outcome of this research will not only advance mortality studies but also facilitate the application of PH models in many other areas. 2: Generalized modelling framework for the valuation of mortality-linked products My research in this area is motivated by the emergence of many modern insurance products with option-embedded features. A generalized valuation framework needs to be developed where both insurance and financial risks are stochastically modelled and correlated. We consider regime-switching models for interest and mortality risks because it can provide a coherent structure for both risks and a flexible dependence relationship in this joint modelling framework. This generalized modelling framework will allow hybrid products containing both insurance and financial risks to be properly valuated. Our approach also contributes to the theory of developing bivariate models in which the dependence structure between two risks are allowed to change under different measures. 3. Risk management through mortality-indexed product design I propose a risk-sharing strategy between an annuity provider and its policyholders, in which the benefit of the products will be adjusted according to a longevity index designed to reflect the unexpected mortality changes. This type of product design may provide a economic solution for all parties that are affected by the financial consequence of longevity risk.
随着越来越多的报告讨论政府社会保障和卫生系统潜在的巨额赤字,以及许多工会退休计划的破产威胁,养老金成为人们最关心的问题。罪魁祸首之一是预期寿命前所未有的、意想不到的增长。尽管死亡率预测一直是精算学和人口学的传统话题,但过去的经验表明,死亡率改善的原因尚未得到很好的理解。死亡率变化的不确定性已成为大多数国家政府、保险公司和养老金规划者面临的重大挑战。随机死亡率模型可用于研究死亡风险对计划和产品的影响。这种关于死亡率的新视角表明,我们需要新的死亡风险模型以及新的评估和风险管理方法。我的研究是关于这些新兴的研究课题。我提出的研究既是我当前工作的延续和扩展,可以分为三个广泛的研究项目领域。 1. 马尔可夫死亡率建模方法及其应用在这项研究中,我们继续致力于开发基于生物学的死亡率建模和预测方法。基于生物学的衰老过程将使用来自生理变量的直接信息或有关健康的间接信息(例如不同年龄的医疗支出)来表征,以增强死亡率模型并改进预测。该项目的研究成果将加深我们对人类衰老和死亡率改善的认识。我们的结果的应用不仅适用于人寿保险和年金定价的死亡率建模,还适用于医疗保健需求和成本预测建模。 b.虽然相位型 (PH) 模型在许多应用领域都很有用,但众所周知,获得 PH 模型的有效参数估计非常困难。然而,对于特殊结构的PH老化模型,我们通常可以获得分布的解析函数表达式,这使得我们能够采用最大似然法和快速贝叶斯方法来获得参数估计。我们在这一领域的目标是为不同来源的数据提供有效的估计方法,并针对不同的应用目的定制PH模型。这项研究的成果不仅将推进死亡率研究,还将促进 PH 模型在许多其他领域的应用。 2:死亡率相关产品估值的广义建模框架 我在这一领域的研究是受到许多具有期权嵌入功能的现代保险产品的出现的推动。需要开发一个通用的估值框架,对保险和金融风险进行随机建模和关联。我们考虑利率和死亡风险的制度转换模型,因为它可以为这两种风险提供连贯的结构,并在这个联合建模框架中提供灵活的依赖关系。这种通用的建模框架将允许对包含保险和金融风险的混合产品进行正确评估。我们的方法还有助于开发双变量模型的理论,其中允许两个风险之间的依赖结构在不同的措施下发生变化。 3. 通过死亡率指数产品设计进行风险管理 我提出了年金提供者与其投保人之间的风险分担策略,其中产品的收益将根据旨在反映意外死亡率变化的寿命指数进行调整。这种类型的产品设计可以为受长寿风险财务后果影响的所有各方提供经济解决方案。

项目成果

期刊论文数量(0)
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Liu, Xiaoming其他文献

Climate-driven range shifts of the king penguin in a fragmented ecosystem
  • DOI:
    10.1038/s41558-018-0084-2
  • 发表时间:
    2018-03-01
  • 期刊:
  • 影响因子:
    30.7
  • 作者:
    Cristofari, Robin;Liu, Xiaoming;Trucchi, Emiliano
  • 通讯作者:
    Trucchi, Emiliano
Automatic fluid segmentation in retinal optical coherence tomography images using attention based deep learning
  • DOI:
    10.1016/j.neucom.2020.07.143
  • 发表时间:
    2021-06-08
  • 期刊:
  • 影响因子:
    6
  • 作者:
    Liu, Xiaoming;Wang, Shaocheng;Hu, Wei
  • 通讯作者:
    Hu, Wei
Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition
Mn versus Al in Layered Oxide Cathodes in Lithium-Ion Batteries: A Comprehensive Evaluation on Long-Term Cyclability
  • DOI:
    10.1002/aenm.201703154
  • 发表时间:
    2018-05-25
  • 期刊:
  • 影响因子:
    27.8
  • 作者:
    Li, Wangda;Liu, Xiaoming;Manthiram, Arumugam
  • 通讯作者:
    Manthiram, Arumugam
dbMTS: A comprehensive database of putative human microRNA target site SNVs and their functional predictions
  • DOI:
    10.1002/humu.24020
  • 发表时间:
    2020-06-01
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    Li, Chang;Mou, Chengcheng;Liu, Xiaoming
  • 通讯作者:
    Liu, Xiaoming

Liu, Xiaoming的其他文献

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{{ truncateString('Liu, Xiaoming', 18)}}的其他基金

Mortality risk: modelling, evaluation and risk management
死亡风险:建模、评估和风险管理
  • 批准号:
    RGPIN-2014-04682
  • 财政年份:
    2021
  • 资助金额:
    $ 0.8万
  • 项目类别:
    Discovery Grants Program - Individual
Mortality risk: modelling, evaluation and risk management
死亡风险:建模、评估和风险管理
  • 批准号:
    RGPIN-2014-04682
  • 财政年份:
    2020
  • 资助金额:
    $ 0.8万
  • 项目类别:
    Discovery Grants Program - Individual
Mortality risk: modelling, evaluation and risk management
死亡风险:建模、评估和风险管理
  • 批准号:
    RGPIN-2014-04682
  • 财政年份:
    2019
  • 资助金额:
    $ 0.8万
  • 项目类别:
    Discovery Grants Program - Individual
Mortality risk: modelling, evaluation and risk management
死亡风险:建模、评估和风险管理
  • 批准号:
    RGPIN-2014-04682
  • 财政年份:
    2018
  • 资助金额:
    $ 0.8万
  • 项目类别:
    Discovery Grants Program - Individual
Mortality risk: modelling, evaluation and risk management
死亡风险:建模、评估和风险管理
  • 批准号:
    RGPIN-2014-04682
  • 财政年份:
    2017
  • 资助金额:
    $ 0.8万
  • 项目类别:
    Discovery Grants Program - Individual
Mortality risk: modelling, evaluation and risk management
死亡风险:建模、评估和风险管理
  • 批准号:
    RGPIN-2014-04682
  • 财政年份:
    2016
  • 资助金额:
    $ 0.8万
  • 项目类别:
    Discovery Grants Program - Individual
Mortality risk: modelling, evaluation and risk management
死亡风险:建模、评估和风险管理
  • 批准号:
    RGPIN-2014-04682
  • 财政年份:
    2015
  • 资助金额:
    $ 0.8万
  • 项目类别:
    Discovery Grants Program - Individual
Stochastic mortality modelling and its applications
随机死亡率模型及其应用
  • 批准号:
    342387-2008
  • 财政年份:
    2012
  • 资助金额:
    $ 0.8万
  • 项目类别:
    Discovery Grants Program - Individual
Stochastic mortality modelling and its applications
随机死亡率模型及其应用
  • 批准号:
    342387-2008
  • 财政年份:
    2011
  • 资助金额:
    $ 0.8万
  • 项目类别:
    Discovery Grants Program - Individual
Stochastic mortality modelling and its applications
随机死亡率模型及其应用
  • 批准号:
    342387-2008
  • 财政年份:
    2010
  • 资助金额:
    $ 0.8万
  • 项目类别:
    Discovery Grants Program - Individual

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