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Bayesian modelling of financial guarantee insurance

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  • Puustelli, Anne
  • Koskinen, Lasse
  • Luoma, Arto

Abstract

In this paper we model the claim process of financial guarantee insurance, and predict the pure premium and the required amount of risk capital. The data used are from the financial guarantee system of the Finnish statutory pension scheme. The losses in financial guarantee insurance may be devastating during an economic depression (i.e., deep recession). This indicates that the economic business cycle, and in particular depressions, must be taken into account in modelling the claim amounts in financial guarantee insurance. A Markov regime-switching model is used to predict the frequency and severity of future depression periods. The claim amounts are predicted using a transfer function model where the predicted growth rate of the real GNP is an explanatory variable. The pure premium and initial risk reserve are evaluated on the basis of the predictive distribution of claim amounts. Bayesian methods are applied throughout the modelling process. For example, estimation is based on posterior simulation with the Gibbs sampler, and model adequacy is assessed by posterior predictive checking. Simulation results show that the required amount of risk capital is high, even though depressions are an infrequent phenomenon.

Suggested Citation

  • Puustelli, Anne & Koskinen, Lasse & Luoma, Arto, 2008. "Bayesian modelling of financial guarantee insurance," Insurance: Mathematics and Economics, Elsevier, vol. 43(2), pages 245-254, October.
    • Handle: RePEc:eee:insuma:v:43:y:2008:i:2:p:245-254
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    References listed on IDEAS

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    1. Coe, Patrick J, 2002. "Financial Crisis and the Great Depression: A Regime Switching Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 76-93, February.
    2. Rantala, Jukka & Hietikko, Harri, 1988. "An application of time series methods to financial guarantee insurance," European Journal of Operational Research, Elsevier, vol. 37(3), pages 398-408, December.
    3. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    4. N. G. Best & D. J. Spiegelhalter & A. Thomas & C. E. G. Brayne, 1996. "Bayesian Analysis of Realistically Complex Models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(2), pages 323-342, March.
    5. Carol Alexander, 2005. "The Present and Future of Financial Risk Management," Journal of Financial Econometrics, Oxford University Press, vol. 3(1), pages 3-25.
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    Cited by:

    1. Tanskanen, Antti J. & Niininen, Petri & Vatanen, Kari, 2010. "Risk-based classification of financial instruments in the Finnish statutory pension scheme TyEL," Research Discussion Papers 9/2010, Bank of Finland.
    2. Tanskanen, Antti J. & Niininen, Petri & Vatanen, Kari, 2010. "Risk-based classification of financial instruments in the Finnish statutory pension scheme TyEL," Bank of Finland Research Discussion Papers 9/2010, Bank of Finland.
    3. repec:zbw:bofrdp:2010_009 is not listed on IDEAS
    4. Jacques, Sébastien & Lai, Van Son & Soumaré, Issouf, 2011. "Synthetizing a debt guarantee: Super-replication versus utility approach," International Review of Financial Analysis, Elsevier, vol. 20(1), pages 27-40, January.

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