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PRICING LONGEVITY-LINKED SECURITIES IN THE PRESENCE OF MORTALITY TREND CHANGES

Published online by Cambridge University Press:  10 March 2021

Arne Freimann*
Affiliation:
Institute for Finance and Actuarial Sciences (ifa) Lise-Meitner-Str. 14, 89081Ulm, Germany Institute of Insurance Science, University of Ulm Helmholtzstr. 20, 89069 Ulm, Germany E-Mail: a.freimann@ifa-ulm.de
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Abstract

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Even though the trend in mortality improvements has experienced several permanent changes in the past, the uncertainty regarding future mortality trends is often left unmodeled when pricing longevity-linked securities. In this paper, we present a stochastic modeling framework for the valuation of longevity-linked securities which explicitly considers the risk of random future changes in the long-term mortality trend. We construct a set of meaningful probability distortions which imply equivalent risk-adjusted pricing measures under which the basic model structure is preserved. Inspired by risk-based capital requirements for (re)insurers, we also establish a cost-of-capital pricing approach which then serves as the appropriate reference framework for finding a reasonable range for the market price of longevity risk. In a numerical application, we demonstrate that our model produces plausible risk loadings and show that a greater proportion of the risk loading is allocated to longer maturities when the risk of random future mortality trend changes is adequately modeled.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© 2021 by Astin Bulletin. All rights reserved

References

Bauer, D., Börger, M. and Russ, J. (2010) On the pricing of longevity-linked securities. Insurance: Mathematics and Economics, 46(1), 139149.Google Scholar
Blake, D., Cairns, A.J.G., Dowd, K. and Kessler, A.R. (2019) Still living with mortality: The longevity risk transfer market after one decade. British Actuarial Journal, 24, e1, 1–80.CrossRefGoogle Scholar
Börger, M. (2010) Deterministic shock vs. stochastic value-at-risk – an analysis of the Solvency II standard model approach to longevity risk. Blätter der DGVFM, 31(2), 225259.Google Scholar
Börger, M., Schönfeld, J. and Schupp, J. (2019a) Calibrating mortality processes with trend changes to multi-population data. Ulm University working paper.Google Scholar
Börger, M. and Schupp, J. (2018) Modeling trend processes in parametric mortality models. Insurance: Mathematics and Economics, 78, 369380.Google Scholar
Börger, M., Schupp, J. and Russ, J. (2019b) It takes two: Why mortality trend modeling is more than modeling one mortality trend. Ulm University working paper.Google Scholar
Boyer, M.M. and Stentoft, L. (2013) If we can simulate it, we can insure it: An application to longevity risk management. Insurance: Mathematics and Economics, 52(1), 3545.Google Scholar
Cairns, A.J.G., Blake, D. and Dowd, K. (2006) A two-factor model for stochastic mortality with parameter uncertainty: Theory and calibration. The Journal of Risk and Insurance, 73(4), 687718.CrossRefGoogle Scholar
Cairns, A.J.G., Dowd, K., Blake, D. and Coughlan, G.D. (2014) Longevity hedge effectiveness: A decomposition. Quantitative Finance, 14(2), 217235.CrossRefGoogle Scholar
Chen, H. and Cox, S.H. (2009) Modeling mortality with jumps: Applications to mortality securitization. The Journal of Risk and Insurance, 76(3), 727751.CrossRefGoogle Scholar
Chow, G.C. (1960) Tests of equality between sets of coefficients in two linear regressions. Econometrica: Journal of the Econometric Society, 28(3), 591605.CrossRefGoogle Scholar
Dickey, D.A. and Fuller, W.A. (1979) Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427431.Google Scholar
Haberman, S., Kaishev, V., Millossovich, P., Villegas, A.M., Baxter, S., Gaches, A., Gunnlaugsson, S. and Sison, M. (2014) Longevity basis risk: A methodology for assessing basis risk. Institute and Faculty of Actuaries, Sessional Research Paper.Google Scholar
Kwiatkowski, D., Phillips, P.C., Schmidt, P. and Shin, Y. (1992) Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54(1–3), 159178.CrossRefGoogle Scholar
Leung, M., Fung, M.C. and O’Hare, C. (2018) A comparative study of pricing approaches for longevity instruments. Insurance: Mathematics and Economics, 82, 95116.Google Scholar
Levantesi, S. and Menzietti, M. (2017) Maximum market price of longevity risk under solvency regimes: The case of Solvency II. Risks, 5(2), 121.CrossRefGoogle Scholar
Li, J.S.-H., Chan, W.-S. and Cheung, S.-H. (2011) Structural changes in the Lee-Carter mortality indexes: detection and implications. North American Actuarial Journal, 15(1), 1331.CrossRefGoogle Scholar
Li, J.S.-H., Chan, W.-S. and Zhou, R. (2017) Semicoherent multipopulation mortality modeling: The impact on longevity risk securitization. The Journal of Risk and Insurance, 84(3), 10251065.CrossRefGoogle Scholar
Lin, Y. and Cox, S.H. (2005) Securitization of mortality risks in life annuities. The Journal of Risk and Insurance, 72(2), 227252.CrossRefGoogle Scholar
Liu, Y. and Li, J.S.-H. (2016) The locally linear Cairns-Blake-Dowd model: A note on delta-nuga hedging of longevity risk. ASTIN Bulletin, 47(1), 79151.CrossRefGoogle Scholar
Loeys, J., Panigirtzoglou, N. and Ribeiro, R.M. (2007) Longevity: A market in the making. JPMorgan Global Market Strategy.Google Scholar
O’hare, C. and Li, Y. (2015) Identifying structural breaks in stochastic mortality models. Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 1(2), 114. https://doi.org/10.1115/1.4029740.Google Scholar
Schupp, J. (2019) On the modeling of variable mortality trend processes. Ulm University working paper.Google Scholar
Sweeting, P. (2011) A trend-change extension of the Cairns-Blake-Dowd model. Annals of Actuarial Science, 5(2), 143162.CrossRefGoogle Scholar
Tan, C.I., Li, J., Li, J.S.-H. and Balasooriya, U. (2014) Parametric mortality indexes: From index construction to hedging strategies. Insurance: Mathematics and Economics, 59, 285299.Google Scholar
Van Berkum, F., Antonio, K. and Vellekoop, M. (2016) The impact of multiple structural changes on mortality predictions. Scandinavian Actuarial Journal, 2016(7), 581603.CrossRefGoogle Scholar
Villegas, A.M. and Haberman, S. (2014) On the modeling and forecasting of socioeconomic mortality differentials: An application to deprivation and mortality in England. North American Actuarial Journal, 18(1), 168193.CrossRefGoogle Scholar
Villegas, A.M., Haberman, S., Kaishev, V.K. and Millossovich, P. (2017) A comparative study of two-population models for the assessment of basis risk in longevity hedges. ASTIN Bulletin, 47(3), 631679.CrossRefGoogle Scholar
Wang, S. (2002) A universal framework for pricing financial and insurance risks. ASTIN Bulletin, 32(2), 213234.CrossRefGoogle Scholar
Wang, S. (2007) Normalized exponential tilting. North American Actuarial Journal, 11(3), 8999.CrossRefGoogle Scholar
Wüthrich, M.V. (2016) Market-Consistent Actuarial Valuation. New York: Springer.CrossRefGoogle Scholar
Wüthrich, M.V. and Merz, M. (2013) Financial Modeling, Actuarial Valuation and Solvency in Insurance. New York: Springer.CrossRefGoogle Scholar
Zeddouk, F. and Devolder, P. (2019) Pricing of longevity derivatives and cost of capital. Risks, 7(2), 129.CrossRefGoogle Scholar