ABSTRACT

This paper describes a general approach for the stochastic modeling of assets returns and liability cash-flows of a typical pensions insurer. On the asset side, we model the investment returns on equities and various classes of fixed-income instruments including short- and long-maturity fixed-rate bonds as well as index-linked and corporate bonds. On the liability side, the risks are driven by future mortality developments as well as price and wage inflation. All the risk factors are modeled as a multivariate stochastic process that captures the dynamics and the dependencies across different risk factors. The model is easy to interpret and to calibrate to both historical data and to forecasts or expert views concerning the future. This feature is particularly useful in unprecedented circumstances like pandemics when historical data alone does not give a reasonable description of the future. The simple structure of the model allows for efficient computations. The construction of a million scenarios takes only a few minutes on a personal computer. The approach is illustrated with an asset-liability analysis of a defined benefit pension fund, pre- and post-COVID-19.

摘要

本文描述了对典型养老金保险公司的资产回报和负债现金流进行随机建模的一般方法。在资产方面，我们对股票和各类固定收益工具的投资回报进行建模，包括短期和长期固定利率债券以及指数挂钩债券和公司债券。在负债方面，风险是由未来死亡率发展以及价格和工资通胀驱动的。所有风险因素都被建模为一个多元随机过程，该过程捕捉了不同风险因素之间的动态和相关性。该模型易于解释并根据历史数据和关于未来的预测或专家观点进行校准。此功能在前所未有的情况下特别有用，例如流行病，当仅凭历史数据无法对未来进行合理描述时。模型的简单结构允许有效的计算。在个人电脑上构建百万场景只需几分钟。该方法通过对 COVID-19 之前和之后的固定受益养老基金的资产负债分析进行说明。