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A Synchronous Bootstrap to Account for Dependencies Between Lines of Business in the Estimation of Loss Reserve Prediction Error

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  • Greg Taylor
  • Gráinne McGuire

Abstract

In this article we consider the situation in which an insurer requires a loss reserve, together with the estimated prediction error, in respect of a number of stochastically dependent lines of business, individually and in aggregate. We suppose that generalized linear models are used to estimate each of the individual loss reserves, and that bootstrapping is used to estimate prediction errors. Specialized forms of the bootstrap, referred to as synchronous bootstraps, are constructed to capture the dependencies. Numerical examples are given in which loss reserve forecasts and their prediction errors are obtained for individual lines of business and in aggregate.

Suggested Citation

  • Greg Taylor & Gráinne McGuire, 2007. "A Synchronous Bootstrap to Account for Dependencies Between Lines of Business in the Estimation of Loss Reserve Prediction Error," North American Actuarial Journal, Taylor & Francis Journals, vol. 11(3), pages 70-88.
    • Handle: RePEc:taf:uaajxx:v:11:y:2007:i:3:p:70-88
    DOI: 10.1080/10920277.2007.10597467
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    Cited by:

    1. Klaus Schmidt, 2012. "Loss prediction based on run-off triangles," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(2), pages 265-310, June.
    2. Ioannis Badounas & Georgios Pitselis, 2020. "Loss Reserving Estimation With Correlated Run-Off Triangles in a Quantile Longitudinal Model," Risks, MDPI, vol. 8(1), pages 1-26, February.
    3. Gareth W. Peters & Mario V. Wuthrich & Pavel V. Shevchenko, 2010. "Chain ladder method: Bayesian bootstrap versus classical bootstrap," Papers 1004.2548, arXiv.org.
    4. Heo, Wookjae & Lee, Jae Min & Park, Narang & Grable, John E., 2020. "Using Artificial Neural Network techniques to improve the description and prediction of household financial ratios," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    5. Yannick Appert-Raullin & Laurent Devineau & Hinarii Pichevin & Philippe Tann, 2013. "One-Year Volatility of Reserve Risk in a Multivariate Framework," Working Papers hal-00848492, HAL.
    6. Peters, Gareth W. & Wüthrich, Mario V. & Shevchenko, Pavel V., 2010. "Chain ladder method: Bayesian bootstrap versus classical bootstrap," Insurance: Mathematics and Economics, Elsevier, vol. 47(1), pages 36-51, August.

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