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Dependence structure of CAT bonds and portfolio diversification: a copula-GARCH approach

Author

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  • Adlane Haffar

    (University of Science and Technology Houari Boumediene)

  • Éric Le Fur

    (INSEEC Grande Ecole)

Abstract

This paper analyzes advantages of investing in catastrophe bonds (CATs) in terms of portfolio diversification. Indeed, the increase in environmental disasters and their economic and financial consequences are still poorly covered by insurance and reinsurance companies. As a result, there is a rapid growth in the use of catastrophe bonds on the financial markets, which can allow the transfer of risks to the capital market. We use copula-GARCH models to test the time-varying dependence of CATs, in a portfolio composed of six stock markets (CAC 40, DJIA, EUROSTOXX 50, FTSE 100, HANGSENG, and NIKKEI 225). Our results reveal that the CATs display the highest risk-adjusted performer. This security may be a good complement to a portfolio for investors seeking to optimize their risk-adjusted returns. In addition, the CATs are one of the best diversifiers. Finally, the CATs are the asset that increases the lowest the probability of extreme co-variations with its benchmark portfolio.

Suggested Citation

  • Adlane Haffar & Éric Le Fur, 2022. "Dependence structure of CAT bonds and portfolio diversification: a copula-GARCH approach," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 297-309, July.
  • Handle: RePEc:pal:assmgt:v:23:y:2022:i:4:d:10.1057_s41260-022-00271-3
    DOI: 10.1057/s41260-022-00271-3
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    1. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Shahbaz, Muhammad, 2017. "Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 258-279.
    2. Charles-Olivier Amédée-Manesme & Benoit Faye & Eric Le Fur, 2020. "Heterogeneity and fine wine prices: application of the quantile regression approach," Applied Economics, Taylor & Francis Journals, vol. 52(26), pages 2821-2840, May.
    3. Rafael Schmidt & Ulrich Stadtmüller, 2006. "Non‐parametric Estimation of Tail Dependence," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 307-335, June.
    4. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 130-168.
    5. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    6. Zhao, Yang & Yu, Min-Teh, 2019. "Measuring the liquidity impact on catastrophe bond spreads," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 197-210.
    7. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    8. Zhu, Huiming & Guo, Yawei & You, Wanhai & Xu, Yaqin, 2016. "The heterogeneity dependence between crude oil price changes and industry stock market returns in China: Evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 55(C), pages 30-41.
    9. Leo Michelis & Cathy Ning, 2010. "The dependence structure between the Canadian stock market and the USD/CAD exchange rate: a copula approach," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 43(3), pages 1016-1039, August.
    10. Shahzad, Syed Jawad Hussain & Hernandez, Jose Arreola & Al-Yahyaee, Khamis Hamed & Jammazi, Rania, 2018. "Asymmetric risk spillovers between oil and agricultural commodities," Energy Policy, Elsevier, vol. 118(C), pages 182-198.
    11. Ledoit, Oliver & Wolf, Michael, 2008. "Robust performance hypothesis testing with the Sharpe ratio," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 850-859, December.
    12. Baur, Dirk G., 2013. "The structure and degree of dependence: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 786-798.
    13. J. David Cummins & Philippe Trainar, 2009. "Securitization, Insurance, and Reinsurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 463-492, September.
    14. Laurent Barras & Olivier Scaillet & Russ Wermers, 2010. "False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas," Journal of Finance, American Finance Association, vol. 65(1), pages 179-216, February.
    15. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    16. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572.
    17. Marc Gürtler & Martin Hibbeln & Christine Winkelvos, 2016. "The Impact of the Financial Crisis and Natural Catastrophes on CAT Bonds," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(3), pages 579-612, September.
    18. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    19. Edward Frees & Emiliano Valdez, 1998. "Understanding Relationships Using Copulas," North American Actuarial Journal, Taylor & Francis Journals, vol. 2(1), pages 1-25.
    20. Ardia, David & Boudt, Kris, 2018. "The peer performance ratios of hedge funds," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 351-368.
    21. Dißmann, J. & Brechmann, E.C. & Czado, C. & Kurowicka, D., 2013. "Selecting and estimating regular vine copulae and application to financial returns," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 52-69.
    22. Shahzad, Syed Jawad Hussain & Mensi, Walid & Hammoudeh, Shawkat & Rehman, Mobeen Ur & Al-Yahyaee, Khamis H., 2018. "Extreme dependence and risk spillovers between oil and Islamic stock markets," Emerging Markets Review, Elsevier, vol. 34(C), pages 42-63.
    23. Garcia, René & Tsafack, Georges, 2011. "Dependence structure and extreme comovements in international equity and bond markets," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1954-1970, August.
    24. Peter Carayannopoulos & M Fabricio Perez, 2015. "Diversification through Catastrophe Bonds: Lessons from the Subprime Financial Crisis," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 40(1), pages 1-28, January.
    25. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    26. Ardia, David & Boudt, Kris, 2015. "Testing equality of modified Sharpe ratios," Finance Research Letters, Elsevier, vol. 13(C), pages 97-104.
    27. Alexander Braun, 2016. "Pricing in the Primary Market for Cat Bonds: New Empirical Evidence," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(4), pages 811-847, December.
    28. Massimo Mariani & Paola Amoruso, 2016. "The Effectiveness of Catastrophe Bonds in Portfolio Diversification," International Journal of Economics and Financial Issues, Econjournals, vol. 6(4), pages 1760-1767.
    29. Frahm, Gabriel & Junker, Markus & Schmidt, Rafael, 2005. "Estimating the tail-dependence coefficient: Properties and pitfalls," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 80-100, August.
    30. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    31. Ausin, M. Concepcion & Lopes, Hedibert F., 2010. "Time-varying joint distribution through copulas," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2383-2399, November.
    32. 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.
    33. Ning, Cathy, 2010. "Dependence structure between the equity market and the foreign exchange market-A copula approach," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 743-759, September.
    34. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
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    Cited by:

    1. Wulan Anggraeni & Sudradjat Supian & Sukono & Nurfadhlina Abdul Halim, 2023. "Catastrophe Bond Diversification Strategy Using Probabilistic–Possibilistic Bijective Transformation and Credibility Measures in Fuzzy Environment," Mathematics, MDPI, vol. 11(16), pages 1-30, August.

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    More about this item

    Keywords

    CAT bonds; Copula-GARCH model; Portfolio diversification; Portfolio risk; Robust MCD portfolio;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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