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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

保險公司因應死亡率風險之避險策略 / Hedging strategy against mortality risk for insurance company

莊晉國, Chuang, Chin Kuo Unknown Date (has links)
本篇論文主要討論在死亡率改善不確定性之下的避險策略。當保險公司負債面的人壽保單是比年金商品來得多的時候,公司會處於死亡率的風險之下。我們假設死亡率和利率都是隨機的情況,部分的死亡率風險可以經由自然避險而消除,而剩下的死亡率風險和利率風險則由零息債券和保單貼現商品來達到最適避險效果。我們考慮mean variance、VaR和CTE當成目標函數時的避險策略,其中在mean variance的最適避險策略可以導出公式解。由數值結果我們可以得知保單貼現的確是死亡率風險的有效避險工具。 / This paper proposes hedging strategies to deal with the uncertainty of mortality improvement. When insurance company has more life insurance contracts than annuities in the liability, it will be under the exposure of mortality risk. We assume both mortality and interest rate risk are stochastic. Part of mortality risk is eliminated by natural hedging and the remaining mortality risk and interest rate risk will be optimally hedged by zero coupon bond and life settlement contract. We consider the hedging strategies with objective functions of mean variance, value at risk and conditional tail expectation. The closed-form optimal hedging formula for mean variance assumption is derived, and the numerical result show the life settlement is indeed a effective hedging instrument against mortality risk.
2

壽險公司責任準備金涉險值之估計 / The Estimation of Value at Risk for the Reserve of Life/Health Insurance Company

詹志清, Chihching Chan Unknown Date (has links)
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.

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