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Robust Bayesian estimation and prediction of reserves in exponential model with quadratic variance function

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  • Boratyńska, Agata
Abstract
The exponential families with quadratic variance function, conjugate families of priors and square loss function is applied to the prediction of claim reserves. The robustness with respect to the priors is considered. The uncertainty of the prior information is modeled by two different classes of priors. The posterior regret Γ-minimax estimators and predictors are constructed.

Suggested Citation

  • Boratyńska, Agata, 2017. "Robust Bayesian estimation and prediction of reserves in exponential model with quadratic variance function," Insurance: Mathematics and Economics, Elsevier, vol. 76(C), pages 135-140.
    • Handle: RePEc:eee:insuma:v:76:y:2017:i:c:p:135-140
    DOI: 10.1016/j.insmatheco.2017.07.007
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    6. Chan, Jennifer S.K. & Boris Choy, S.T. & Makov, Udi E., 2008. "Robust Bayesian Analysis of Loss Reserves Data Using the Generalized-t Distribution," ASTIN Bulletin, Cambridge University Press, vol. 38(1), pages 207-230, May.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Loss reserves; Exponential model with quadratic variance function; Classes of priors; ε-contamination; Posterior regret Γ-minimax estimation and prediction; Mean square error; Chain ladder factor;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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