死亡率预测中的风险建模

Oper. Res. Pub Date : 2022-02-15 DOI:10.1287/opre.2021.2255
Nan Zhu, Daniel Bauer
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引用次数: 2

摘要

对保险公司、养老基金和退休制度来说,未来寿命的不确定性是一个重大的风险因素。在“死亡率预测中的风险建模”中,Zhu和Bauer提出了新的随机模型来分析这种长寿风险,该模型关注与长期死亡率预测相关的不确定性,并捕捉了过去几十年死亡率预测的演变。他们通过在正向建模框架中分析死亡率预测的时间序列来得出他们的模型,这与传统的基于特定年龄实现死亡率的随机死亡率模型形成对比。作者展示了他们的模型在传统寿险市场和新兴长寿风险转移市场的金融应用。一个关键的结论是,在他们的模型下,依赖于死亡率长期演变的位置的不确定性比传统模型所显示的要大得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling the Risk in Mortality Projections
Capturing the Uncertainty in Long-Term Mortality Forecasts The uncertainty in future longevity presents a substantial risk factor for insurance companies, pension funds, and retirement systems. In “Modeling the Risk in Mortality Projections,” Zhu and Bauer present novel stochastic models for analyzing this longevity risk that focus on the uncertainty associated with long-term mortality projections and capture the evolution of mortality forecasts over the past decades. They arrive at their models by analyzing time series of mortality forecasts in a forward modeling framework, which contrasts with conventional stochastic mortality models that are built on age-specific realized mortality rates. The authors showcase their models in exemplifying financial applications in both traditional life insurance markets and the emerging longevity risk transfer market. A key takeaway is that uncertainty in positions that depend on the long-term evolution of mortality is substantially greater under their models than suggested by conventional models.
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