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Calibrating CAT bonds for Mexican earthquakes

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  • Haerdle, Wolfgang
  • Cabrera, Brenda Lopez

Abstract

The study of natural catastrophe models plays an important role in the prevention and mitigation of disasters. After the occurrence of a natural disaster, the reconstruction can be financed with catastrophe bonds (CAT bonds) or reinsurance. This paper examines the calibration of a real parametric CAT bond for earthquakes that was sponsored by the Mexican government. The calibration of the CAT bond is based on the estimation of the intensity rate that describes the earthquake process from the two sides of the contract, the reinsurance and the capital markets, and from the historical data. The results demonstrate that, under specific conditions, the financial strategy of the government, a mix of reinsurance and CAT bond, is optimal in the sense that it provides coverage of USD 450 million for a lower cost than the reinsurance itself. Since other variables can affect the value of the losses caused by earthquakes, e.g. magnitude, depth, city impact, etc., we also derive the price of a hypothetical modeled-index loss (zero) coupon CAT bond for earthquakes, which is based on the compound doubly stochastic Poisson pricing methodology from BARYSHNIKOV, MAYO and TAYLOR (2001) and BURNECKI and KUKLA (2003). In essence, this hybrid trigger combines modeled loss and index trigger types, trying to reduce basis risk borne by the sponsor while still preserving a nonindemnity trigger mechanism. Our results indicate that the (zero) coupon CAT bond price increases as the threshold level increases, but decreases as the expiration time increases. Due to the quality of the data, the results show that the expected loss is considerably more important for the valuation of the CAT bond than the entire distribution of losses. The study of natural catastrophe models plays an important role in the prevention and mitigation of disasters. After the occurrence of a natural disaster, the reconstruction can be financed with catastrophe bonds (CAT bonds) or reinsurance. This paper examines the calibration of a real parametric CAT bond for earthquakes that was sponsored by the Mexican government. The calibration of the CAT bond is based on the estimation of the intensity rate that describes the earthquake process from the two sides of the contract, the reinsurance and the capital markets, and from the historical data. The results demonstrate that, under specific conditions, the financial strategy of the government, a mix of reinsurance and CAT bond, is optimal in the sense that it provides coverage of USD 450 million for a lower cost than the reinsurance itself. Since other variables can affect the value of the losses caused by earthquakes, e.g. magnitude, depth, city impact, etc., we also derive the price of a hypothetical modeled-index loss (zero) coupon CAT bond for earthquakes, which is based on the compound doubly stochastic Poisson pricing methodology from BARYSHNIKOV, MAYO and TAYLOR (2001) and BURNECKI and KUKLA (2003). In essence, this hybrid trigger combines modeled loss and index trigger types, trying to reduce basis risk borne by the sponsor while still preserving a nonindemnity trigger mechanism. Our results indicate that the (zero) coupon CAT bond price increases as the threshold level increases, but decreases as the expiration time increases. Due to the quality of the data, the results show that the expected loss is considerably more important for the valuation of the CAT bond than the entire distribution of losses.

Suggested Citation

  • Haerdle, Wolfgang & Cabrera, Brenda Lopez, 2007. "Calibrating CAT bonds for Mexican earthquakes," 101st Seminar, July 5-6, 2007, Berlin Germany 9265, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaa101:9265
    DOI: 10.22004/ag.econ.9265
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    References listed on IDEAS

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    1. Froot, Kenneth A., 2001. "The market for catastrophe risk: a clinical examination," Journal of Financial Economics, Elsevier, vol. 60(2-3), pages 529-571, May.
    2. Härdle, Wolfgang Karl & Burnecki, Krzysztof & Weron, Rafał, 2004. "Simulation of risk processes," Papers 2004,01, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    3. J. David Cummins & Mary A. Weiss, 2009. "Convergence of Insurance and Financial Markets: Hybrid and Securitized Risk‐Transfer Solutions," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 493-545, September.
    4. Silke Finken & Christian Laux, 2009. "Catastrophe Bonds and Reinsurance: The Competitive Effect of Information‐Insensitive Triggers," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 579-605, September.
    5. Burnecki, Krzysztof & Kukla, Grzegorz & Weron, Rafał, 2000. "Property insurance loss distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(1), pages 269-278.
    6. Lee, Jin-Ping & Yu, Min-Teh, 2007. "Valuation of catastrophe reinsurance with catastrophe bonds," Insurance: Mathematics and Economics, Elsevier, vol. 41(2), pages 264-278, September.
    7. Robert W. Klein & Shaun Wang, 2009. "Catastrophe Risk Financing in the United States and the European Union: A Comparative Analysis of Alternative Regulatory Approaches," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 607-637, September.
    8. 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.
    9. Cummins, J. David & Lalonde, David & Phillips, Richard D., 2004. "The basis risk of catastrophic-loss index securities," Journal of Financial Economics, Elsevier, vol. 71(1), pages 77-111, January.
    10. Burnecki, Krzysztof & Misiorek, Adam & Weron, Rafal, 2010. "Loss Distributions," MPRA Paper 22163, University Library of Munich, Germany.
    11. Victor Vaugirard, 2003. "Valuing catastrophe bonds by Monte Carlo simulations," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(1), pages 75-90.
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    Cited by:

    1. Nowak, Piotr & Romaniuk, Maciej, 2013. "Pricing and simulations of catastrophe bonds," Insurance: Mathematics and Economics, Elsevier, vol. 52(1), pages 18-28.
    2. Borensztein, Eduardo & Cavallo, Eduardo & Jeanne, Olivier, 2017. "The welfare gains from macro-insurance against natural disasters," Journal of Development Economics, Elsevier, vol. 124(C), pages 142-156.
    3. Denis-Alexandre Trottier & Van Son Lai, 2017. "Reinsurance or CAT Bond? How to Optimally Combine Both," Working Papers 2017-003, Department of Research, Ipag Business School.
    4. Braun, Alexander, 2011. "Pricing catastrophe swaps: A contingent claims approach," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 520-536.
    5. Chang Carolyn W. & Feng Yalan, 2021. "Hurricane Bond Price Dependency on Underlying Hurricane Parameters," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 15(1), pages 1-21, January.
    6. Shao, Jia & Papaioannou, Apostolos D. & Pantelous, Athanasios A., 2017. "Pricing and simulating catastrophe risk bonds in a Markov-dependent environment," Applied Mathematics and Computation, Elsevier, vol. 309(C), pages 68-84.
    7. Têtu Alexandre & Lai Van Son & Soumaré Issouf & Gendron Michel, 2015. "Hedging Flood Losses Using Cat Bonds," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 9(2), pages 149-184, July.
    8. Truong, Chi & Trück, Stefan, 2016. "It’s not now or never: Implications of investment timing and risk aversion on climate adaptation to extreme events," European Journal of Operational Research, Elsevier, vol. 253(3), pages 856-868.
    9. Martin Eling, 2013. "Recent Research Developments Affecting Nonlife Insurance—The CAS Risk Premium Project 2011 Update," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 16(1), pages 35-46, March.
    10. Giuricich, Mario Nicoló & Burnecki, Krzysztof, 2019. "Modelling of left-truncated heavy-tailed data with application to catastrophe bond pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 498-513.
    11. Alexis Louaas & Pierre Picard, 2014. "Optimal Insurance For Catastrophic Risk: Theory And Application To Nuclear Corporate Liability," Working Papers hal-01097897, HAL.
    12. Volodymyr Perederiy, 2007. "Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs," SFB 649 Discussion Papers SFB649DP2007-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Lo, Chien-Ling & Lee, Jin-Ping & Yu, Min-Teh, 2013. "Valuation of insurers’ contingent capital with counterparty risk and price endogeneity," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5025-5035.
    14. Krzysztof Burnecki & Mario Nicoló Giuricich, 2017. "Stable Weak Approximation at Work in Index-Linked Catastrophe Bond Pricing," Risks, MDPI, Open Access Journal, vol. 5(4), pages 1-19, December.
    15. Ben Ammar, Semir & Braun, Alexander & Eling, Martin, 2015. "Alternative Risk Transfer and Insurance-Linked Securities: Trends, Challenges and New Market Opportunities," I.VW HSG Schriftenreihe, University of St.Gallen, Institute of Insurance Economics (I.VW-HSG), volume 56, number 56.
    16. Ma, Zong-Gang & Ma, Chao-Qun, 2013. "Pricing catastrophe risk bonds: A mixed approximation method," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 243-254.
    17. Joanne Ho & Martin Odening, 2009. "Weather-based estimation of wildfire risk," SFB 649 Discussion Papers SFB649DP2009-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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    More about this item

    Keywords

    Risk and Uncertainty;

    JEL classification:

    • G19 - Financial Economics - - General Financial Markets - - - Other
    • G29 - Financial Economics - - Financial Institutions and Services - - - Other
    • N26 - Economic History - - Financial Markets and Institutions - - - Latin America; Caribbean
    • N56 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries - - - Latin America; Caribbean
    • Q29 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Other
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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