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Catastrophe risk with global climate change determines the price of catastrophe equity puts

Author

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  • Chuang, Ming-Che
  • Huang, Hong-Chih
  • Huang, Shih-Feng
  • Lin, Shih-Kuei

Abstract

A growing frequency of natural catastrophes due to global climate change has confronted insurance companies with massive compensation claims and substantial stock price risk. The catastrophe equity put options provide a means to manage such risks. As stock markets usually exhibit volatility clustering, volatility may increase significantly. This article establishes a GARCH model for global climate change to characterize the dynamic process of insurance companies’ stock prices. The incomplete market requires an Esscher transform, a specific risk-neutral probability measure that serves to price the CatEPut. The empirical analysis identifies that the inverse-Gaussian distribution for each catastrophe loss and the random walk with positive drift for the arrival rate of catastrophes perform the best in terms of goodness-of-fit. The sensitivity analysis results illustrate that global climate change, the catastrophe intensity, and the systematic/unsystematic catastrophe risk constitute important factors for determining the CatEPut price.

Suggested Citation

  • Chuang, Ming-Che & Huang, Hong-Chih & Huang, Shih-Feng & Lin, Shih-Kuei, 2025. "Catastrophe risk with global climate change determines the price of catastrophe equity puts," The North American Journal of Economics and Finance, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:ecofin:v:80:y:2025:i:c:s1062940825001135
    DOI: 10.1016/j.najef.2025.102473
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    1. Cox, Samuel H. & Fairchild, Joseph R. & Pedersen, Hal W., 2004. "Valuation of structured risk management products," Insurance: Mathematics and Economics, Elsevier, vol. 34(2), pages 259-272, April.
    2. Ornthanalai, Chayawat, 2014. "Lévy jump risk: Evidence from options and returns," Journal of Financial Economics, Elsevier, vol. 112(1), pages 69-90.
    3. Jin‐Chuan Duan & Peter Ritchken & Zhiqiang Sun, 2006. "Approximating Garch‐Jump Models, Jump‐Diffusion Processes, And Option Pricing," Mathematical Finance, Wiley Blackwell, vol. 16(1), pages 21-52, January.
    4. Amin, Kaushik I, 1993. "Jump Diffusion Option Valuation in Discrete Time," Journal of Finance, American Finance Association, vol. 48(5), pages 1833-1863, December.
    5. Chia‐Chien Chang & Shih‐Kuei Lin & Min‐Teh Yu, 2011. "Valuation of Catastrophe Equity Puts With Markov‐Modulated Poisson Processes," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 78(2), pages 447-473, June.
    6. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
    7. Jaimungal, Sebastian & Wang, Tao, 2006. "Catastrophe options with stochastic interest rates and compound Poisson losses," Insurance: Mathematics and Economics, Elsevier, vol. 38(3), pages 469-483, June.
    8. Søren Asmussen & Jens Ledet Jensen & Leonardo Rojas-Nandayapa, 2016. "On the Laplace Transform of the Lognormal Distribution," Methodology and Computing in Applied Probability, Springer, vol. 18(2), pages 441-458, June.
    9. Heston, Steven L & Nandi, Saikat, 2000. "A Closed-Form GARCH Option Valuation Model," The Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 585-625.
    10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    11. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    12. Jin‐Chuan Duan, 1995. "The Garch Option Pricing Model," Mathematical Finance, Wiley Blackwell, vol. 5(1), pages 13-32, January.
    13. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    14. J. David Cummins, 2008. "CAT Bonds and Other Risk‐Linked Securities: State of the Market and Recent Developments," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 11(1), pages 23-47, March.
    15. Tak Kuen Siu & Howell Tong & Hailiang Yang, 2004. "On Pricing Derivatives Under GARCH Models: A Dynamic Gerber-Shiu Approach," North American Actuarial Journal, Taylor & Francis Journals, vol. 8(3), pages 17-31, July.
    16. Jin-Chuan Duan & Jean-Guy Simonato, 1998. "Empirical Martingale Simulation for Asset Prices," Management Science, INFORMS, vol. 44(9), pages 1218-1233, September.
    17. Lin, Shih-Kuei & Chang, Chia-Chien & Powers, Michael R., 2009. "The valuation of contingent capital with catastrophe risks," Insurance: Mathematics and Economics, Elsevier, vol. 45(1), pages 65-73, August.
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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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