保險公司轉嫁長壽風險最適負債管理策略探討

Abstract

人類高齡化的趨勢增加了保險公司承擔年金與退休金商品負債面的長壽風險。長壽風險對保險公司而言，是具系統性的，並且無法透過大數法則來分散。本研究依據年金與壽險具有自然避險(natural hedging)的效果，提出一個最低條件風險值模型(minimize Conditional Value at Risk, CVaR)之最適負債配置策略，能夠提供保險公司有效的長壽風險避險策略。 本研究參考Cox et al. (2007)所提出的自然避險策略與Cairns, Blake and Dowd (2006b) 的二因子死亡率隨機模型建構自然避險的最適負債配置比率，模型中也加入Milevsky et al. (2006)建議的夏普指數定價模型來計算系統性長壽風險的風險溢酬率用率。不同於過去文獻，本研究考慮死亡率隨機模型中的參數風險，並進一步修正過去研究文獻必須假設死亡率必須平行移動的缺點，此外，本模型也可以應用到三種以上之多角化商品組合。本研究之模擬分析結果可以檢證最低條件風險值模型是否提供較佳的避險結果?因此，本研究所提出的模型將提供學術界與實務界對於保險公司長壽風險避險策略有更完備與正確的了解。

By incorporating the mortality nature hedging strategy of Cox and Lin (2007) and the two-factor stochastic mortality model of Cairns et al. (2006b), this research proposes a minimize Conditional Value at Risk (CVaR) model to calculate an optimal liability strategy that insurance companies may use to hedge against the systematic mortality risk under parameter uncertainty. We further integrate the risk premium loadings of systematic risk into the proposed model with the Sharpe ratio pricing principle, as suggested by Milevsky et al. (2006), to re‡ect the importance of risk-adjusted pricing. In a multiple liabilities framework, the results can confirm whether the minimize CVaR model can lead to an optimal liability structure that has smaller quantiles liability distribution under the required loading return. In addition, we also examine whether the minimize CVaR method has a better distribution risk reduction effect for hedging longevity risk when the mortality shifts are non-parallel and the mortality process of parameters uncertainty is included.