在具有随机利率的莱维模型中加强变额年金的估值

Ludovic Goudenège, Andrea Molent, Xiao Wei, Antonino Zanette
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引用次数: 0

摘要

本文通过纳入赫尔-怀特模型所描述的随机利率,扩展了在 L\'evy 股票市场环境下具有最低收益保证的变额年金的估值和最优退保框架。与之前的文献相比,这种方法构建了一个更加动态和现实的财务设置框架。我们采用了一种混合数值方法,将利率建模的树形方法与基础资产价格的有限差分技术相结合,从而建立了一种稳健的估值机制。这种方法对于解决变额年金的复杂性尤为有效,因为变额年金的定期费用和死亡率风险是重要因素。我们的研究结果揭示了随机利率对这些金融工具退保战略决策过程的影响。通过全面的数字实验,并将我们的结果与 Longstaff-SchwartzMonte Carlo 方法得出的结果进行比较,我们说明了我们改进后的模型如何指导保险公司设计公平平衡双方利益的合同。这对于阻止过早退保,同时适应金融市场的现实波动尤为重要。最后,通过对不同利率参数的比较静态分析,强调了利率对最优退保策略成本的影响,强调了准确模拟随机利率的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Valuation of Variable Annuities in Lévy Models with Stochastic Interest Rate
This paper extends the valuation and optimal surrender framework for variable annuities with guaranteed minimum benefits in a L\'evy equity market environment by incorporating a stochastic interest rate described by the Hull-White model. This approach frames a more dynamic and realistic financial setting compared to previous literature. We exploit a robust valuation mechanism employing a hybrid numerical method that merges tree methods for interest rate modeling with finite difference techniques for the underlying asset price. This method is particularly effective for addressing the complexities of variable annuities, where periodic fees and mortality risks are significant factors. Our findings reveal the influence of stochastic interest rates on the strategic decision-making process concerning the surrender of these financial instruments. Through comprehensive numerical experiments, and by comparing our results with those obtained through the Longstaff-Schwartz Monte Carlo method, we illustrate how our refined model can guide insurers in designing contracts that equitably balance the interests of both parties. This is particularly relevant in discouraging premature surrenders while adapting to the realistic fluctuations of financial markets. Lastly, a comparative statics analysis with varying interest rate parameters underscores the impact of interest rates on the cost of the optimal surrender strategy, emphasizing the importance of accurately modeling stochastic interest rates.
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