Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/54597
DC Field | Value | Language |
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dc.contributor.advisor | 黃泓智<br>楊曉文 | zh_TW |
dc.contributor.author | 莊晉國 | zh_TW |
dc.contributor.author | Chuang, Chin Kuo | en_US |
dc.creator | 莊晉國 | zh_TW |
dc.creator | Chuang, Chin Kuo | en_US |
dc.date | 2011 | en_US |
dc.date.accessioned | 2012-10-30T03:24:37Z | - |
dc.date.available | 2012-10-30T03:24:37Z | - |
dc.date.issued | 2012-10-30T03:24:37Z | - |
dc.identifier | G0099358007 | en_US |
dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/54597 | - |
dc.description | 碩士 | zh_TW |
dc.description | 國立政治大學 | zh_TW |
dc.description | 風險管理與保險研究所 | zh_TW |
dc.description | 99358007 | zh_TW |
dc.description | 100 | zh_TW |
dc.description.abstract | 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。 | zh_TW |
dc.description.abstract | 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. | en_US |
dc.description.tableofcontents | ABSTRACT I\nCONTENTS II\nLIST OF TABLES III\nLIST OF FIGURES IV\n1.INTRODUCTION 1\n2.MODELS SETTING 2\n2.1 INTEREST RATE AND MORTALITY RATE MODEL 2\n2.2.THE PROFIT FUNCTION 4\n2.3.ADJUSTING MORTALITY TABLE 6\n3.HEDGING APPROACHES 8\n4.NUMERICAL EXAMPLES 11\n5.CONCLUSIONS 22\nREFERENCE: 24\nAPPENDIX: 26\n1.KARUSH-KUHN-TUCKER (KKT) OPTIMALITY CONDITIONS: 26\n2.SOLUTION OF THE OPTIMAL HEDGING PROBLEM 26 | zh_TW |
dc.language.iso | en_US | - |
dc.source.uri | http://thesis.lib.nccu.edu.tw/record/#G0099358007 | en_US |
dc.subject | 死亡率風險 | zh_TW |
dc.subject | Lee Carter model | zh_TW |
dc.subject | CIR model | zh_TW |
dc.subject | Maximum Entropy principle | zh_TW |
dc.subject | Value at risk | zh_TW |
dc.subject | Conditional tail expectation | zh_TW |
dc.subject | Karush-Kuhn-Tucker | zh_TW |
dc.subject | Mortality risk | en_US |
dc.subject | Lee Carter model | en_US |
dc.subject | CIR model | en_US |
dc.subject | Maximum Entropy principle | en_US |
dc.subject | Value at risk | en_US |
dc.subject | Conditional tail expectation | en_US |
dc.subject | Karush-Kuhn-Tucker | en_US |
dc.title | 保險公司因應死亡率風險之避險策略 | zh_TW |
dc.title | Hedging strategy against mortality risk for insurance company | en_US |
dc.type | thesis | en |
dc.relation.reference | Blake, D., and Burrows, W., 2001. “Survivor Bonds: Helping to Hedge Mortality Risk”, Journal of Risk and Insurance 68: 339-348.\nBrockett, P. L., 1991. Information Theoretic Approach to Actuarial Science: A Unification and Extention of Relevant Theory and Applications, Transactions of the Society of Actuaries, 42: 73-115\nCox, J. C., Ingersoll, Jr., J. E., and Ross, S. A., 1985. “A Theory of the Term Structure of Interest Rates”, Econometrica 53: 385-408.\nCox, S. H. and Y. Lin, 2007. Natural Hedging of Life and Annuity Mortality Risks,North American Actuarial Journal, 11(3): 1-15.\nDowd, K., Blake, D., Cairns, A. J. G., and Dawson, P., 2006. “Survivor Swaps”, Journal of Risk & Insurance 73: 1-17.\nHua Chen, Samuel H. Cox and Zhiqiang Yan, 2010. Hedging Longevity Risk in Life Settlements. Working paper.\nJohnny Siu-Hang Li, 2010. Pricing longevity risk with the parametric bootstrap: A maximum entropy approach, Insurance: Mathematics and Economics, 47:176-186.\nJohnny Siu-Hang Li and Andrew Cheuk-Yin NG.,2011. Canonical valuation of mortality-linked securities, The Journal of Risk and Insurance, Vol. 78, No. 4, 853-884\nKogure., A., and Kurachi, Y., 2010. A Bayesian Approach to Pricing Longevity Risk Based on Risk-Neutral Predictive Distributions, Insurance: Mathematics and Economics, 46:162-172.\nKuhn, H. W.; Tucker, A. W., 1951. "Nonlinear programming". Proceedings of 2nd Berkeley Symposium. Berkeley: University of California press. pp. 481-492.\nKullback, S., and R. A. Leibler, 1951. On Information and Sufficiency, Annals of Mathematical Statistics, 22: 79-86.\nLee, R.D., Carter, L.R., 1992. Modeling and forecasting US mortality. Journal of the\nAmerican Statistical Association 87, 659_675.\nPflug, G., 2000. Some Remarks on the Value-at-Risk and the Conditional\nValue-at-Risk. S. Uryasev, ed. Probabilistic Constrained Optimization\nMethodology and Applications. Kluwer, Dordrecht, The Netherlands, 272–281.\nTrindade, A. A., S. Uryasev, A. Shapiro, and G. Zrazhevsky, 2007. Financial\nPrediction with Constrained Tail Risk. Journal of Banking and Finance 31 3524–\n3538.\nTsai, J.T., J.L. Wang, and L.Y. Tzeng, 2010. On the optimal product mix in life insurance companies using conditional Value at Risk, Insurance: Mathematics and Economics, 46, 235-241.\nWang, J.L., H.C. Huang, S.S. Yang, J.T. Tsai, 2010. An optimal product mix\nfor hedging longevity risk in life insurance companies: The immunization theory\napproach, The Journal of Risk and Insurance, Vol. 77, No. 2, 473-497. | zh_TW |
item.grantfulltext | open | - |
item.openairetype | thesis | - |
item.openairecristype | http://purl.org/coar/resource_type/c_46ec | - |
item.languageiso639-1 | en_US | - |
item.cerifentitytype | Publications | - |
item.fulltext | With Fulltext | - |
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