跨國死亡率模型之建構：考慮世代效應

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姓名

馮耀文(Yao-wen Feng) 查詢紙本館藏

畢業系所

財務金融學系

論文名稱

跨國死亡率模型之建構：考慮世代效應
(A Framework of Multi-Countries mortality Model with Cohort Effect)

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摘要(中)

保險公司和退休金提供者所遭受的長壽風險日益嚴重，資本市場上的證券化商品是目前長壽風險的風險管理方法，而通常死亡率的證券化商品會連結死亡率指數，但由於曝險人口和避險人口的統計上的不匹配產生的基差風險，使得避險端無法完美避險，因此在使用死亡率連結的證券化商品時應該要有效地降低基差風險。本文主要提供一個架構去建構跨國死亡率模型，根據瑞士再保公司在2003年發行的死亡率債券所連結的死亡率指數，我們選用英格蘭與威爾士、法國、義大利和瑞士這四個國家的資料去建構模型，在跨國死亡率之時間效應考慮去趨勢和VAR模型來分析，跨國死亡率之世代效應則應用共整合分析的方法，本文選用誤差衡量的方法MAPE和RMSPE比較原始的方法和本文研究方法的配適和預測死亡率的準確性。

摘要(英)

Pension plans and Annuity providers are subjects to the threat of longevity risk. Most popular way to mitigate the risk is to trade mortality-linked securities in capital markets. In the mortality-linked securities, basis risk often relates to mismatches in demographics between the exposed populations and the hedging population. We must reduce the basis risk to manage the longevity risk effectively. This paper introduces a new framework for modeling the mortality rates for a pair related populations to aim consistent mortality forecasts. We propose an Lee-Carter with cohort effect model to fit the mortality rates which incorporate Time effects and Cohort effects. A VECM model is derived by the cohort parameters in multi-countries. We deal with time parameters by detrend method and conduct the VAR model by detrended data. This study illustrates the fitting and forecasting accuracy in new and original methods.

關鍵字(中)

★ 長壽風險
★ 世代效應
★ 共整合分析
★ 去趨勢

關鍵字(英)

★ Longevity risks,
★ Cohort effects
★ ,Cointegration
★ Detrend

論文目次

摘要 i
Abstract ii
誌謝 iii
表目錄 v
圖目錄 vi
一、研究動機 1
二、世代死亡率模型的介紹 5
2-1 RH世代死亡率模型 5
2-2 RH估計參數的結果 6
三、跨國死亡率之時間效應模型建構 10
3-1 跨國死亡率之時間效應的趨勢模型 10
3-2 多國死亡率時間效應去趨勢後的單根檢定 12
3-3 確定VAR的落後期數 12
3-4 建構跨國死亡率之時間效應的VAR模型 14
四、跨國死亡率之世代效應 15
4-1 確定跨國死亡率的世代效應呈現I(P)過程 15
4-2 確定VAR的落後期數 16
4-3 檢測共整合分析決定秩 (Rank) 17
4-4 建構跨國死亡率世代效應的VECM模型 19
五、跨國死亡率模型配適和預測分析 21
5-1 資料敘述和誤差衡量的方法 21
5-2 模型配適 22
5-3 模型預測 26
六、結論 29
參考文獻 30

參考文獻

[1]. Blake, D., A. J. G. Cairns and K. Dowd, 2006a, Living with Mortality: Longevity Bonds and Other Mortality-linked Securities, British Actuarial Journal, 12(1), 153-197.
[2]. Blake, D., A. Cairns, K. Dowd and R. MacMinn, 2006b, Longevity Bonds: Financial Engineering, Valuation and Hedging, Journal of Risk and Insurance, 73(4), 647-672.
[3]. Blake D. and W. Burrows, 2001, Survivor Bonds: Helping to Hedge Mortality Risk, The Journal of Risk and Insurance, 68(2), 339-348.
[4]. Cairns, A.J.G., Blake, D., and Dowd, K. (2006b) “A Two-Factor Model for Stochas-
tic Mortality with Parameter Uncertainty: Theory and Calibration,” Journal of
Risk and Insurance, 73, 687-718.
[5]. Cairns, A.J.G., Blake, D., Dowd, K., Coughlan, G.D., Epstein, D., Ong, A., and
Balevich, I., 2009, A quantitative comparison of stochastic mortality models using
data from England & Wales and the United States, North American Actuarial
Journal, 13, 1-35.
[6]. Cairns, A.J.G., Blake, D., Dowd, K., Coughlan, G.D. and Khalaf-Allah, M., 2011, Bayesian Stochastic Mortality Modelling for Two Populations, To appear in ASTIN Bulletin.
[7]. Coughlan, G.D., Khalaf-Allah, M., Ye, Y., Kumar, S., Cairns, A.J.G., Blake, D. and Dowd,K. (2011). Longevity Hedging: A Framework for Longevity Basis Risk Analysis and Hedge Eﬀectiveness. North American Actuarial Journal, to appear.
[8]. Currie, I.D. (2006) “Smoothing and forecasting mortality rates with P-splines,”
Talk given at the Institute of Actuaries, June 2006.See http://www.ma.hw.ac.uk/∼iain/research/talks.html
[9]. Currie I.D., Durban, M. and Eilers, P.H.C. (2004) “Smoothing and forecasting
mortality rates,” Statistical Modelling, 4, 279-298.
[10]. Dowd, K. 2003, Survivor Bonds: A Comment on Blake and Burrows, Journal of Risk and Insurance, 70(2), 339-348.
[11]. Dowd, K., Cairns, A.J.G., Blake, D., Coughlan, G.D. and Khalaf-Allah, M., 2011, A Gravity Model of Mortality rates for Two Related Populations.
[12]. Darkiewicz, G. and T. Hoedemakers, 2004, How the Cointegration Analysis Can
Help in Mortality Forecasting, in K. U. Leuven Host Document: DTEW Research
Report, K. U. Leuven, 1-24
[13]. Lee, R.D., and Carter, L.R. (1992) “Modeling and forecasting U.S. mortality,”
Journal of the American Statistical Association, 87, 659-675.
[14]. Li, J. S. H. and M. R. Hardy, 2011, Measuring Basis Risk in Longevity Hedges, North American Actuarial Journal 15(2): 177–200.
[15]. Li, N., and Lee, R., 2005, Coherent mortality forecasts for a group of populations:
An extension of the Lee-Carter method. Demography, 42(3), 575-594.
[16]. Lin, Y. and Cox, S. H., 2005, Securitization of mortality risks in life annuities, Journal of Risk and Insurance, 72, 227-252.
[17]. Richards, S. J. and G. Jones, 2004. Financial Aspects of Longevity Risk. Paper Presented at the Staple Inn Actuarial Society, London, October 26.
[18]. Stallard E. (2006), Demographic Issues in Longevity Risk Analysis, The Journal of Risk and Insurance, 73(4), 575-609.
[19]. Yang, S.S. and Wang, C.W., 2012, Pricing and Securitization of Multi-country Longevity Risk with Mortality Dependence, Insurance Mathematics and Economics.
[20]. Renshaw, A.E., and Haberman, S.,2003, Lee-Carter mortality forecasting with
age-speciﬁc enhancement, Insurance: Mathematics and Economics, 33, 255-272.
[21]. Renshaw, A.E., and Haberman, S., 2006, A cohort-based extension to the Lee-Carter model for mortality reduction factors, Insurance: Mathematics and Economics, 38, 556-570.

指導教授

楊曉文

審核日期

2013-7-17

推文