IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/34236.html
   My bibliography  Save this paper

Longevity hedge effectiveness: a decomposition

Author

Listed:
  • Cairns, Andrew
  • Dowd, Kevin
  • Blake, David
  • Coughlan, Guy

Abstract

We use a case study of a pension plan wishing to hedge the longevity risk in its pension liabilities at a future date. The plan has the choice of using either a customised hedge or an index hedge, with the degree of hedge effectiveness being closely related to the correlation between the value of the hedge and the value of the pension liability. The key contribution of this paper is to show how correlation and, therefore, hedge effectiveness can be broken down into contributions from a number of distinct types of risk factor. Our decomposition of the correlation indicates that population basis risk has a significant influence on the correlation. But recalibration risk as well as the length of the recalibration window are also important, as is cohort effect uncertainty. Having accounted for recalibration risk, parameter uncertainty and Poisson risk have only a marginal impact on hedge effectiveness. Our case study shows that longevity risk can be substantially hedged using index hedges as an alternative to customised longevity hedges and that, as a consequence, index longevity hedges - in conjunction with the other components of an ALM strategy - can provide an effective and lower cost alternative to both a full buy-out of pension liabilities or even to a strategy using customised longevity hedges.

Suggested Citation

  • Cairns, Andrew & Dowd, Kevin & Blake, David & Coughlan, Guy, 2011. "Longevity hedge effectiveness: a decomposition," MPRA Paper 34236, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:34236
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/34236/1/MPRA_paper_34236.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cairns, Andrew J.G. & Blake, David & Dowd, Kevin & Coughlan, Guy D. & Epstein, David & Khalaf-Allah, Marwa, 2011. "Mortality density forecasts: An analysis of six stochastic mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 48(3), pages 355-367, May.
    2. Jarner, Søren Fiig & Kryger, Esben Masotti, 2011. "Modelling Adult Mortality in Small Populations: The Saint Model," ASTIN Bulletin, Cambridge University Press, vol. 41(2), pages 377-418, November.
    3. Kevin Dowd & Andrew Cairns & David Blake & Guy Coughlan & Marwa Khalaf-Allah, 2011. "A Gravity Model of Mortality Rates for Two Related Populations," North American Actuarial Journal, Taylor & Francis Journals, vol. 15(2), pages 334-356.
    4. David Blake & Tom Boardman & Andrew Cairns, 2014. "Sharing Longevity Risk: Why Governments Should Issue Longevity Bonds," North American Actuarial Journal, Taylor & Francis Journals, vol. 18(1), pages 258-277.
    5. Andrew Cairns & David Blake & Kevin Dowd & Guy Coughlan & David Epstein & Alen Ong & Igor Balevich, 2009. "A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States," North American Actuarial Journal, Taylor & Francis Journals, vol. 13(1), pages 1-35.
    6. Denuit, M. & Haberman, S. & Renshaw, A.E., 2010. "Comonotonic Approximations to Quantiles of Life Annuity Conditional Expected Present Values: Extensions to General Arima Models and Comparison with the Bootstrap," ASTIN Bulletin, Cambridge University Press, vol. 40(1), pages 331-349, May.
    7. Denuit, Michel & Haberman, S. & Renshaw, A.E., 2010. "Comonotonic Approximations To Quantiles of Life Annuity Conditional Expected Present Values: Extensions To General ARIMA Models and Comparison With the Bootstrap," LIDAM Discussion Papers ISBA 2010011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Andrew J. G. Cairns & David Blake & Kevin Dowd, 2006. "A Two‐Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(4), pages 687-718, December.
    9. Wolfgang Reichmuth & Samad Sarferaz, 2008. "Bayesian Demographic Modeling and Forecasting: An Application to U.S. Mortality," SFB 649 Discussion Papers SFB649DP2008-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Blake, D. & Cairns, A. J. G. & Dowd, K., 2006. "Living with Mortality: Longevity Bonds and Other Mortality-Linked Securities," British Actuarial Journal, Cambridge University Press, vol. 12(1), pages 153-197, March.
    11. Nan Li & Ronald Lee, 2005. "Coherent mortality forecasts for a group of populations: An extension of the lee-carter method," Demography, Springer;Population Association of America (PAA), vol. 42(3), pages 575-594, August.
    12. Czado, Claudia & Delwarde, Antoine & Denuit, Michel, 2005. "Bayesian Poisson log-bilinear mortality projections," Insurance: Mathematics and Economics, Elsevier, vol. 36(3), pages 260-284, June.
    13. Coughlan, Guy & Khalaf-Allah, Marwa & Ye, Yijing & Kumar, Sumit & Cairns, Andrew & Blake, David & Dowd, Kevin, 2011. "Longevity hedging 101: A framework for longevity basis risk analysis and hedge effectiveness," MPRA Paper 35743, University Library of Munich, Germany.
    14. Denuit, Michel & Haberman, S. & Renshaw, A. E., 2010. "Comonotonic Approximations To Quantiles of Life Annuity Conditional Expected Present Values: Extensions To General Arima Models and Comparison With the Bootstrap," LIDAM Reprints ISBA 2010028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. Kogure, Atsuyuki & Kurachi, Yoshiyuki, 2010. "A Bayesian approach to pricing longevity risk based on risk-neutral predictive distributions," Insurance: Mathematics and Economics, Elsevier, vol. 46(1), pages 162-172, February.
    16. Olivieri, Annamaria & Pitacco, Ermanno, 2009. "Stochastic Mortality: The Impact on Target Capital," ASTIN Bulletin, Cambridge University Press, vol. 39(2), pages 541-563, November.
    17. Dowd, Kevin & Cairns, Andrew J.G. & Blake, David & Coughlan, Guy D. & Epstein, David & Khalaf-Allah, Marwa, 2010. "Evaluating the goodness of fit of stochastic mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 47(3), pages 255-265, December.
    18. Guy Coughlan & Marwa Khalaf-Allah & Yijing Ye & Sumit Kumar & Andrew Cairns & David Blake & Kevin Dowd, 2011. "Longevity Hedging 101," North American Actuarial Journal, Taylor & Francis Journals, vol. 15(2), pages 150-176.
    19. Carter, Lawrence R. & Lee, Ronald D., 1992. "Modeling and forecasting US sex differentials in mortality," International Journal of Forecasting, Elsevier, vol. 8(3), pages 393-411, November.
    20. Wills, Samuel & Sherris, Michael, 2010. "Securitization, structuring and pricing of longevity risk," Insurance: Mathematics and Economics, Elsevier, vol. 46(1), pages 173-185, February.
    21. Brouhns, Natacha & Denuit, Michel & Vermunt, Jeroen K., 2002. "A Poisson log-bilinear regression approach to the construction of projected lifetables," Insurance: Mathematics and Economics, Elsevier, vol. 31(3), pages 373-393, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    2. Blake, David & El Karoui, Nicole & Loisel, Stéphane & MacMinn, Richard, 2018. "Longevity risk and capital markets: The 2015–16 update," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 157-173.
    3. Cairns, Andrew J.G., 2011. "Modelling and management of longevity risk: Approximations to survivor functions and dynamic hedging," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 438-453.
    4. Katrien Antonio & Anastasios Bardoutsos & Wilbert Ouburg, 2015. "Bayesian Poisson log-bilinear models for mortality projections with multiple populations," BAFFI CAREFIN Working Papers 1505, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    5. David Blake & Christophe Courbage & Richard MacMinn & Michael Sherris, 2011. "Longevity Risk and Capital Markets: The 2010–2011 Update," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 36(4), pages 489-500, October.
    6. David Blake & Andrew Cairns & Guy Coughlan & Kevin Dowd & Richard MacMinn, 2013. "The New Life Market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(3), pages 501-558, September.
    7. David Blake & Marco Morales & Enrico Biffis & Yijia Lin & Andreas Milidonis, 2017. "Special Edition: Longevity 10 – The Tenth International Longevity Risk and Capital Markets Solutions Conference," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 515-532, April.
    8. Li, Hong & De Waegenaere, Anja & Melenberg, Bertrand, 2015. "The choice of sample size for mortality forecasting: A Bayesian learning approach," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 153-168.
    9. Liu, Yanxin & Li, Johnny Siu-Hang, 2016. "It’s all in the hidden states: A longevity hedging strategy with an explicit measure of population basis risk," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 301-319.
    10. James Risk & Michael Ludkovski, 2015. "Statistical Emulators for Pricing and Hedging Longevity Risk Products," Papers 1508.00310, arXiv.org, revised Sep 2015.
    11. Tan, Chong It & Li, Jackie & Li, Johnny Siu-Hang & Balasooriya, Uditha, 2014. "Parametric mortality indexes: From index construction to hedging strategies," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 285-299.
    12. Li, Johnny Siu-Hang & Zhou, Rui & Hardy, Mary, 2015. "A step-by-step guide to building two-population stochastic mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 121-134.
    13. Hunt, Andrew & Blake, David, 2018. "Identifiability, cointegration and the gravity model," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 360-368.
    14. Andrew J.G. Cairns & Malene Kallestrup-Lamb & Carsten P.T. Rosenskjold & David Blake & Kevin Dowd, 2016. "Modelling Socio-Economic Differences in the Mortality of Danish Males Using a New Affluence Index," CREATES Research Papers 2016-14, Department of Economics and Business Economics, Aarhus University.
    15. Wan, Cheng & Bertschi, Ljudmila, 2015. "Swiss coherent mortality model as a basis for developing longevity de-risking solutions for Swiss pension funds: A practical approach," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 66-75.
    16. Risk, J. & Ludkovski, M., 2016. "Statistical emulators for pricing and hedging longevity risk products," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 45-60.
    17. Ahmadi, Seyed Saeed & Li, Johnny Siu-Hang, 2014. "Coherent mortality forecasting with generalized linear models: A modified time-transformation approach," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 194-221.
    18. Man Chung Fung & Gareth W. Peters & Pavel V. Shevchenko, 2016. "A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting," Papers 1605.09484, arXiv.org.
    19. Danesi, Ivan Luciano & Haberman, Steven & Millossovich, Pietro, 2015. "Forecasting mortality in subpopulations using Lee–Carter type models: A comparison," Insurance: Mathematics and Economics, Elsevier, vol. 62(C), pages 151-161.
    20. Rui Zhou & Johnny Siu-Hang Li & Ken Seng Tan, 2013. "Pricing Standardized Mortality Securitizations: A Two-Population Model With Transitory Jump Effects," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(3), pages 733-774, September.

    More about this item

    Keywords

    Hedge Effectiveness; Correlation; Mark-to-Model; Valuation Model; Simulation; Value Hedging; Longevity Risk; Stochastic Mortality; Population Basis Risk; Recalibration Risk;
    All these keywords.

    JEL classification:

    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:34236. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.