论文标题
定价股权与神经网络具有多种风险因素的人寿保险合同
Pricing equity-linked life insurance contracts with multiple risk factors by neural networks
论文作者
论文摘要
本文考虑了具有多种随机风险因素的通用模型中与股权相关的人寿保险合同的定价：利率，权益，波动性，非系统性和系统的死亡率。我们通过假设保险人对冲净资产价值过程的本地差异的风险来为股权关联的合同定价，并要求以即时标准偏差风险利润率的形式为不可避免的责任赔偿。然后，价格可以表示为非线性偏微分方程系统的解决方案。我们将问题重新制定为一种跳跃的向后随机微分方程，并通过使用有效的神经网络来数字解决。对初始参数进行了灵敏度分析，并提供了对我们神经网络的真实价格近似的准确性的分析。
This paper considers the pricing of equity-linked life insurance contracts with death and survival benefits in a general model with multiple stochastic risk factors: interest rate, equity, volatility, unsystematic and systematic mortality. We price the equity-linked contracts by assuming that the insurer hedges the risks to reduce the local variance of the net asset value process and requires a compensation for the non-hedgeable part of the liability in the form of an instantaneous standard deviation risk margin. The price can then be expressed as the solution of a system of non-linear partial differential equations. We reformulate the problem as a backward stochastic differential equation with jumps and solve it numerically by the use of efficient neural networks. Sensitivity analysis is performed with respect to initial parameters and an analysis of the accuracy of the approximation of the true price with our neural networks is provided.
