Applying stochastic programming to insurance portfolios stress-testing

G. Consigli, Vittorio Moriggia
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引用次数: 9

Abstract

The introduction of the Solvency II regulatory framework in 2011 and unprecendented property and casualty (P/C) claims experienced in recent years by large insurance firms have motivated the adoption of risk-based capital allocation policies in the insurance sector. In this article, we present the key features of a dynamic stochastic program leading to an optimal asset-liability management and capital allocation strategy by a large P/C insurance company and describe how from such formulation a specific, industry-relevant, stress-testing analysis can be derived. Throughout the article the investment manager of the insurance portfolio is regarded as the relevant decision-maker: he faces exogenous constraints determined by the core insurance division and is subject to the capital allocation policy decided by the management, consistently with the company's risk exposure. A novel approach to stress-testing analysis by the insurance management, based on a recursive solution of a large-scale dynamic stochastic program, is presented.
随机规划在保险组合压力测试中的应用
2011年偿付能力II监管框架的引入,以及近年来大型保险公司经历的前所未有的财产和意外(P/C)索赔,促使保险业采用基于风险的资本配置政策。在这篇文章中,我们提出了一个动态随机计划的关键特征,该计划导致了大型P/C保险公司的最优资产负债管理和资本配置策略,并描述了如何从这种公式中推导出具体的、与行业相关的压力测试分析。在整篇文章中,保险组合的投资经理被视为相关的决策者:他面临由核心保险部门决定的外生约束,并受制于管理层决定的资本配置政策,与公司的风险暴露一致。提出了一种基于大规模动态随机规划递归解的保险管理压力测试分析新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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