Longevity/Mortality Risk Modeling and Securities Pricing

32 Pages Posted: 17 Aug 2010 Last revised: 8 Oct 2010

See all articles by Patrick L. Brockett

Patrick L. Brockett

University of Texas at Austin - Department of Information, Risk and Operations Management

Richard D. MacMinn

National Chengchi University; The University of Texas

Yinglu Deng

Red McCombs School of Business

Multiple version iconThere are 2 versions of this paper

Date Written: August 15, 2010

Abstract

Securitization of longevity/mortality risk provides insurers and pension funds an effective, low-cost approach to transferring the longevity/mortality risk from their balance sheets to capital markets. The modeling and forecasting of the mortality rate is the key point in pricing mortality-linked securities that facilitates the emergence of liquid markets. The catastrophic longevity jumps and mortality jumps are significant in historical data and have a critical effect on securities pricing. This paper introduces a stochastic diffusion model with a Double Exponential Jump Diffusion (DEJD) process for mortality time-series, which is the first to capture both asymmetric jump features and cohort effect as the underlying reason for the mortality trend. The DEJD model has the advantage of easy calibration and mathematical tractability. The form of the DEJD model is neat, concise and practical. Compared with previous stochastic models with or without jumps, the DEJD model fits the actual data better. To apply the model, the implied risk premium is calculated based on the Swiss Re mortality bond price. The DEJD model is the first to provide a close-form solution to price the q-forward, which is the standard product contingent on the LifeMetrics index for hedging longevity or mortality risk.

Keywords: Longevity Risk, Mortality Risk, Securitization, Double Exponential Jump Diffussion Model, Lee-Carter Framework

Suggested Citation

Brockett, Patrick L. and MacMinn, Richard D. and Deng, Yinglu, Longevity/Mortality Risk Modeling and Securities Pricing (August 15, 2010). McCombs Research Paper Series No. IROM-05-10, Available at SSRN: https://ssrn.com/abstract=1659294 or http://dx.doi.org/10.2139/ssrn.1659294

Patrick L. Brockett

University of Texas at Austin - Department of Information, Risk and Operations Management ( email )

CBA 5.202
Austin, TX 78712
United States

Richard D. MacMinn

National Chengchi University ( email )

Taipei
Taiwan

The University of Texas ( email )

2317 Speedway
Austin, TX 78712
United States

Yinglu Deng (Contact Author)

Red McCombs School of Business ( email )

CBA 5.202
Austin, TX 78712
United States

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