責任準備金的風險管理是人壽保險公司營運的重要課題之一，其牽涉到保單現金流量的數階動差及分佈之估計，為此我們必須清楚的設定隨機脫退和隨機利率模型，並將保單之重要特性—利率敏感性現金流量納入考慮，否則將誤導保險公司過度規避利率風險及高估其破產的危險性。 本文採用蒙地卡羅模擬法進行責任準備金的模擬，在模擬模型中考慮三個風險因子：死亡率風險、利率風險和解約率風險。透過死亡率的變異數估計死亡率風險對責任準備金的影響；透過隨機利率模型估計隨機利率對責任準備金的影響；於解約率模型中考慮利率與解約率的關係，估計解約率對責任準備金的影響；當中並將隨機利率模型與解約率模型的參數風險納入考慮。最後，將五個險種的現金流量加權平均，以建構保險商品組合，而具有最小的最大分散（maximum dispersion）的保險商品組合即為最佳商品組合，所謂責任準備金的最大分散即責任準備金之第95個百分位數與其平均數之差距。 由模擬結果發現，保險公司應密切注意其責任準備金之利率風險管理，但這並不表示保險公司可忽視解約率風險對責任準備金的影響，而過度規避利率風險，此模擬結果幫助保險公司評估其業務之風險。 / One of the major topics in insurance companies’ operations is the risk management of the reserves. Sound risk management of reserves involves the estimation of the moments and distribution of cash flows associated with sold policies. To estimate the moments or the distribution of future cash flows, one must model stochastic decrements and stochastic discount rates explicitly. Besides, one must consider an important feature of insurance policies: future cash flows may be interest-rate-sensitive. Ignorance of such characteristic may mislead the insurer to over-hedge the interest rate risk and jeopardize the solvency of insurers. In this paper we use Monte Carlo simulation to estimate reserve. We identify three risk factors embedded in life insurers’ reserves in our simulation model: mortality risk, interest rate risk, and lapse rate risk. We use the mortality risk to decide the reserve from the variances of mortality rates. We choose a term structure to decide the reserve from the interest rate risk. Furthermore, we incorporate lapse rate risk into the decision of reserve by recognizing the relationship between lapse rates and interest rates. We also estimate the parameter risk associated with the parameter estimation errors in the term structure model and the lapse rate model. Finally, we construct insurance portfolios by summing weighted cash flow of five insurance policies. According to the minimum maximum dispersion, we intend to find the optimal portfolio and identify that the maximum dispersion of the distribution of terminal reserve is the difference between reserve’s 95th percentile and mean. We find that the maximum dispersion generated from mortality risk is insignificant while maximum dispersion from interest rate risk is substantial. This result is consistent with the observation that life insurers suffer more from the interest rate risk than from the mortality rate risk. The marginal contribution of lapse rate risk to the maximum dispersion, surprisingly, is negative. One possible reason is that the duration of the reserve decreases if policies lapse and lower duration means less interest rate related risk. This seemingly surprising result implies that we would overestimate the maximum dispersion if we neglect the lapse rate risk. We also find that the parameter risks of the interest rate model and the lapse rate model are significant. Our findings suggest that life insurers should pay close attention to interest rate risk management. However, be careful not to neglect the effect of lapse rate and over-manage the interest rate risk. In addition, insurers should be aware of the significance of parameter estimation risks in pricing models. The results of portfolios show that the maximum dispersion is deeply affected by the considered risk and the diversification effect. Our results can help life insurers to access the riskiness of their business.

中文摘要 在本文中，我們依據模擬的風險因子變動，包括死亡率風險，利率風險，解約率風險以及模型的參數風險，來估計第一個保單年度的期末責任準備金之涉險值 (Value at Risk)。本文中，雖僅計算生死合險保單的準備金之涉險值，但是本文所提供的方法以及計算過程可以很容易的應用到其它險種，甚至配合資產面的考量來計算保險公司盈餘(Surplus)的涉險值，進而作為清償能力的監測系統。 本文的特點包括下列幾項：第一，本文提供了一個不同於傳統短期間(Short Horizon)的涉險值計算方式，來估計壽險商品的保單責任準備金(Policy Reserve)的涉險值。第二，本文利用生命表來估計死亡率風險所造成的涉險值。第三，我們利用隨機利率模型來捕捉隨機利率對於責任準備金涉險值的影響。第四，我們考慮解約率對於責任準備金涉險值的影響，值得注意的是，在我們的解約率模型中，引入的利率對於解約率的影響。第五，本文亦考慮風險因子模型當中的參數風險對於涉險值的影響。最後，我們利用無母數方法計算出涉險值的信賴區間，而信賴區間的估計在模擬過程當中尤其重要，因為它可以用來決定模擬次數的多寡。 本文包含六節：第一節為導論。第二節為計算死亡率風險的責任準備金涉險值。第三節是計算加上利率風險後責任準備金涉險值的變化。第四節則為加上解約率後對涉險值的影響。第五節為計算涉險值的信賴區間。第六節是我們的結論以及後續研究的方向探討。 本文包含六節：第一節為導論。第二節為計算死亡率風險的責任準備金涉險值。第三節是計算加上利率風險後責任準備金涉險值的變化。第四節則為加上解約率後對涉險值的影響。第五節為計算涉險值的信賴區間。第六節是我們的結論以及後續研究的方向探討。 / ABSTRACT In this paper, we estimate the VAR of life insurer's terminal reserve of the first policy year by the simulated risk factors, including mortality risk, interest rate risk, lapse rate risk, and estimation risks, of future twenty years. We found that the difference between the VAR under the mortality risk and the interest rate risk is very large because interest rate is a stochastic process but not mortality rate. Thus, the dispersion of interest rate is more then mortality rate. In addition, the VAR will reduce a lot after adding the impact of lapses because the duration of the reserve reduced. If we neglect the impact of lapses to VAR, we will overestimate the VAR significantly. The features of this paper are as follows. First, we provide an approach to measure the VAR of a life insurer's reserve, and it is rather different from traditional VAR with short horizons. Second, we use mortality table to estimate the VAR of a life insurer's reserve. Third, we use stochastic interest rate model to capture the effect of random interest rate to the VAR of a life insurer's reserve. Fourth, we relate the future cash outflows to interest rate and produce a reasonable estimator of VAR. Fifth, we consider the effect of estimation errors to the VAR of a life insurer's reserve. Last, we calculate the confidence interval of the VAR estimates of the policy reserves. This paper consists of six sections. The first section is an introduction. In the second section, we present the method used to estimate the variance of the mortality rate and then estimate the VAR of reserves from these variances. In the third section, we explore how to use stochastic interest rate model to estimate the reserve's VAR and the VAR associated with the parameter risk of the interest rate model. In the fourth section, we analyze the contribution of the lapse rate risk and the parameter risk of the lapse rate model to the reserve's VAR. We also analyze the relative significance of the interest rate risk, the lapse rate risk, and the mortality rate risk in terms of their marginal contributions to the VAR of an insurer's reserves in this section. In the fifth section, we calculate the confidence intervals of the VAR estimates discussed in the previous sections. The last section is the conclusion section containing our conclusions and discussions about potential future researches.