IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v16y2016icp103-111.html

A DCC-GARCH multi-population mortality model and its applications to pricing catastrophic mortality bonds

Author

Listed:
  • Wang, Zihe
  • Li, Johnny Siu-Hang

Abstract

This paper considers the pricing problem of catastrophic mortality bonds, which have been traded among financial institutions since about 10 years ago. We first use a DCC-GARCH model to capture the evolution of the aggregate mortality rates for five developed countries jointly. We then utilize the estimated model to price an illustrative catastrophic mortality bond, which, similar to most of the existing catastrophic mortality bonds, is linked to the mortality of multiple populations. We also study the impact of various features of the DCC-GARCH model on the pricing results.

Suggested Citation

  • Wang, Zihe & Li, Johnny Siu-Hang, 2016. "A DCC-GARCH multi-population mortality model and its applications to pricing catastrophic mortality bonds," Finance Research Letters, Elsevier, vol. 16(C), pages 103-111.
    • Handle: RePEc:eee:finlet:v:16:y:2016:i:c:p:103-111
    DOI: 10.1016/j.frl.2015.10.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612315000999
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2015.10.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Alemany, Aida & Ballester, Laura & González-Urteaga, Ana, 2015. "Volatility spillovers in the European bank CDS market," Finance Research Letters, Elsevier, vol. 13(C), pages 137-147.
    2. Siu-Hang Li & Wai-Sum Chan, 2007. "The Lee-Carter Model for Forecasting Mortality, Revisited," North American Actuarial Journal, Taylor & Francis Journals, vol. 11(1), pages 68-89.
    3. Chen, Hua & MacMinn, Richard & Sun, Tao, 2015. "Multi-population mortality models: A factor copula approach," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 135-146.
    4. Liu, Yanxin & Li, Johnny Siu-Hang, 2015. "The age pattern of transitory mortality jumps and its impact on the pricing of catastrophic mortality bonds," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 135-150.
    5. Noureldin, Diaa & Shephard, Neil & Sheppard, Kevin, 2014. "Multivariate rotated ARCH models," Journal of Econometrics, Elsevier, vol. 179(1), pages 16-30.
    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. Gian Piero Aielli, 2013. "Dynamic Conditional Correlation: On Properties and Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 282-299, July.
    8. Hua Chen & Samuel H. Cox, 2009. "Modeling Mortality With Jumps: Applications to Mortality Securitization," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 727-751, September.
    9. Cox, Samuel H. & Lin, Yijia & Pedersen, Hal, 2010. "Mortality risk modeling: Applications to insurance securitization," Insurance: Mathematics and Economics, Elsevier, vol. 46(1), pages 242-253, February.
    10. Yijia Lin & Sheen Liu & Jifeng Yu, 2013. "Pricing Mortality Securities With Correlated Mortality Indexes," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(4), pages 921-948, December.
    11. Carmichael, Benoıˆt & Coën, Alain, 2013. "Asset pricing with skewed-normal return," Finance Research Letters, Elsevier, vol. 10(2), pages 50-57.
    12. 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.
    13. Lane, Morton N., 2000. "Pricing Risk Transfer Transactions1," ASTIN Bulletin, Cambridge University Press, vol. 30(2), pages 259-293, November.
    14. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    15. Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2014. "Constructing a financial fragility index for emerging countries," Finance Research Letters, Elsevier, vol. 11(4), pages 410-419.
    16. Wang, Chou-Wen & Yang, Sharon S. & Huang, Hong-Chih, 2015. "Modeling multi-country mortality dependence and its application in pricing survivor index swaps—A dynamic copula approach," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 30-39.
    17. Yinglu Deng & Patrick L. Brockett & Richard D. MacMinn, 2012. "Longevity/Mortality Risk Modeling and Securities Pricing," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 79(3), pages 697-721, September.
    18. Wills, Samuel & Sherris, Michael, 2010. "Securitization, structuring and pricing of longevity risk," Insurance: Mathematics and Economics, Elsevier, vol. 46(1), pages 173-185, February.
    19. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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. Li, Johnny Siu-Hang & Liu, Yanxin & Chan, Wai-Sum, 2023. "Hedging longevity risk under non-Gaussian state-space stochastic mortality models: A mean-variance-skewness-kurtosis approach," Insurance: Mathematics and Economics, Elsevier, vol. 113(C), pages 96-121.
    3. Liu, Zhenhua & Tseng, Hui-Kuan & Wu, Jy S. & Ding, Zhihua, 2020. "Implied volatility relationships between crude oil and the U.S. stock markets: Dynamic correlation and spillover effects," Resources Policy, Elsevier, vol. 66(C).
    4. Kim, Joseph H.T. & Li, Johnny S.H., 2017. "Risk-neutral valuation of the non-recourse protection in reverse mortgages: A case study for Korea," Emerging Markets Review, Elsevier, vol. 30(C), pages 133-154.
    5. Zhou, Rui & Ji, Min, 2021. "Modelling mortality dependence: An application of dynamic vine copula," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 241-255.
    6. Hung-Tsung Hsiao & Chou-Wen Wang & I.-Chien Liu & Ko-Lun Kung, 2024. "Mortality improvement neural-network models with autoregressive effects," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(2), pages 363-383, April.
    7. Tsai, Cary Chi-Liang & Wu, Adelaide Di, 2020. "Incorporating hierarchical credibility theory into modelling of multi-country mortality rates," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 37-54.

    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. Hua Chen & Richard D. MacMinn & Tao Sun, 2017. "Mortality Dependence and Longevity Bond Pricing: A Dynamic Factor Copula Mortality Model With the GAS Structure," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 393-415, April.
    4. Liu, Yanxin & Li, Johnny Siu-Hang, 2015. "The age pattern of transitory mortality jumps and its impact on the pricing of catastrophic mortality bonds," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 135-150.
    5. Chen, Fen-Ying & Yang, Sharon S. & Huang, Hong-Chih, 2022. "Modeling pandemic mortality risk and its application to mortality-linked security pricing," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 341-363.
    6. Bahl, Raj Kumari & Sabanis, Sotirios, 2021. "Model-independent price bounds for Catastrophic Mortality Bonds," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 276-291.
    7. Raj Kumari Bahl & Sotirios Sabanis, 2016. "Model-Independent Price Bounds for Catastrophic Mortality Bonds," Papers 1607.07108, arXiv.org, revised Dec 2020.
    8. Guo, Yiping & Li, Johnny Siu-Hang, 2025. "Robust parameter estimation for the Lee-Carter family: A probabilistic principal component approach," Insurance: Mathematics and Economics, Elsevier, vol. 125(C).
    9. Nguyen, Duc Khuong & Sensoy, Ahmet & Sousa, Ricardo M. & Salah Uddin, Gazi, 2020. "U.S. equity and commodity futures markets: Hedging or financialization?," Energy Economics, Elsevier, vol. 86(C).
    10. Andreas Milidonis & Maria Efthymiou, 2017. "Mortality Leads and Lags," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 495-514, April.
    11. Wenjun Zhu & Ken Seng Tan & Chou‐Wen Wang, 2017. "Modeling Multicountry Longevity Risk With Mortality Dependence: A Lévy Subordinated Hierarchical Archimedean Copulas Approach," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 477-493, April.
    12. Lorenzo Fratoni & Susanna Levantesi & Massimiliano Menzietti, 2022. "Measuring Financial Sustainability and Social Adequacy of the Italian NDC Pension System under the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(23), pages 1-23, December.
    13. Chia-Lin Chang & Yiying Li & Michael McAleer, 2018. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Energies, MDPI, vol. 11(6), pages 1-19, June.
    14. Francq, Christian & Zakoian, Jean-Michel, 2014. "Estimating multivariate GARCH and stochastic correlation models equation by equation," MPRA Paper 54250, University Library of Munich, Germany.
    15. Caporin, Massimiliano & Chang, Chia-Lin & McAleer, Michael, 2019. "Are the S&P 500 index and crude oil, natural gas and ethanol futures related for intra-day data?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 50-70.
    16. Jackie Li & Jia Liu, 2020. "A modified extreme value perspective on best-performance life expectancy," Journal of Population Research, Springer, vol. 37(4), pages 345-375, December.
    17. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling and Estimation," Papers 2206.14275, arXiv.org, revised Jan 2025.
    18. Morana, Claudio, 2019. "Regularized semiparametric estimation of high dimensional dynamic conditional covariance matrices," Econometrics and Statistics, Elsevier, vol. 12(C), pages 42-65.
    19. 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.
    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

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

    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:eee:finlet:v:16:y:2016:i:c:p:103-111. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.