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Global loss diversification in the insurance sector

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  • Sheremet, Oleg
  • Lucas, André

Abstract

We study the possibility for international diversification of catastrophe risk by the insurance sector. Adopting the argument that large insurance losses may be a [`]globalizing factor' for the industry, we study the dependence of geographically distant insurance markets via equity returns. In particular, we employ conditional copula theory to model the bivariate dependence of the insurance industry. In contrast to earlier literature on this subject, we disentangle the causes of dependence stemming from the asset side from those from the liability side by conditioning on general market conditions. We find that for both Europe-America and Europe-Asia the dependence is significant. Moreover, we find asymmetric effects: the international dependence is particularly high for losses, even after conditioning for the asset side dependence. Finally, we investigate the time variation in copula parameters and find evidence that dependence in the insurance sector has increased over time, thus reducing the scope for international diversification of large losses in this sector.

Suggested Citation

  • Sheremet, Oleg & Lucas, André, 2009. "Global loss diversification in the insurance sector," Insurance: Mathematics and Economics, Elsevier, vol. 44(3), pages 415-425, June.
    • Handle: RePEc:eee:insuma:v:44:y:2009:i:3:p:415-425
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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. Laurent, Sebastien & Peters, Jean-Philippe, 2002. "G@RCH 2.2: An Ox Package for Estimating and Forecasting Various ARCH Models," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 447-485, July.
    3. Froot, Kenneth A. & O'Connell, Paul G.J., 2008. "On the pricing of intermediated risks: Theory and application to catastrophe reinsurance," Journal of Banking & Finance, Elsevier, vol. 32(1), pages 69-85, January.
    4. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    5. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    6. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    7. Cummins, J. David & Lewis, Christopher M. & Wei, Ran, 2006. "The market value impact of operational loss events for US banks and insurers," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2605-2634, October.
    8. Geluk, J.L. & De Vries, C.G., 2006. "Weighted sums of subexponential random variables and asymptotic dependence between returns on reinsurance equities," Insurance: Mathematics and Economics, Elsevier, vol. 38(1), pages 39-56, February.
    9. Jan Frederik Slijkerman, 2006. "Insurance Sector Risk," Tinbergen Institute Discussion Papers 06-062/2, Tinbergen Institute.
    10. Fields, Joseph A & Klein, Linda S & Myskowski, Edward G, 1998. "Lloyd's Financial Distress and Contagion within the US Property and Liability Insurance Industry," Journal of Risk and Uncertainty, Springer, vol. 16(2), pages 173-185, May-June.
    11. Elijah Brewer & William E. Jackson, 2002. "Inter-industry contagion and the competitive effects of financial distress announcements: evidence from commercial banks and life insurance companies," Working Paper Series WP-02-23, Federal Reserve Bank of Chicago.
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    Cited by:

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    2. Pai, Jeffrey & Li, Yunxian & Yang, Aijun & Li, Chenxu, 2022. "Earthquake parametric insurance with Bayesian spatial quantile regression," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 1-12.

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    More about this item

    Keywords

    Catastrophic insurance losses Copula Dependence Diversification;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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