Studies from University of Economics in Katowice Add New Findings in the Area of Statistics (On Bootstrap Estimators of Some Prediction Accuracy Measures of Loss Reserves In a Non-life Insurance Company): Mathematics – Statistics

2022 SEP 08 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Current study results on Mathematics - Statistics have been published. According to news reporting originating in Katowice, Poland, by NewsRx journalists, research stated, “This article considers the hierarchical generalized linear model (HGLM) for loss reserving in a non-life insurance. In the current insurance practice, insurance companies use generalized linear models (GLM) for prediction of the total loss reserve.”

The news reporters obtained a quote from the research from the University of Economics in Katowice, “This model, however, requires the assumption of independence of random variables occurring in the loss triangle, which may not always be fulfilled. The remedy to this problem is to introduce random effects to the GLM allowing modeling dependence inside the loss triangle. A limitation in the use of HGLM to predict the total loss reserve is the fact that the error of prediction is expressed by a complex analytical formula. An alternative to the analytical approach is to use the bootstrap technique. The main purpose of this article is to propose the full residual and parametric bootstrap procedures for the estimation of three types of prediction accuracy measures. The first is a classic root mean squared error of prediction (RMSE). The second is a quantile of the absolute prediction error (QAPE). The third one, we propose, is a quantile of a mixture of absolute prediction errors. Stochastic properties of the estimators of the accuracy measures are studied in two Monte Carlo simulation experiments.”

According to the news reporters, the research concluded: “Bootstrap procedures and Monte Carlo simulation are implemented in R program.”

This research has been peer-reviewed.

For more information on this research see: On Bootstrap Estimators of Some Prediction Accuracy Measures of Loss Reserves In a Non-life Insurance Company. Communications in Statistics - Simulation and Computation, 2022;51(8):4225-4240. Communications in Statistics - Simulation and Computation can be contacted at: Taylor & Francis Inc, 530 Walnut Street, Ste 850, Philadelphia, PA 19106, USA.

Our news correspondents report that additional information may be obtained by contacting Alicja Wolny-Dominiak, University of Economics in Katowice, Dept Stat & Math Methods Econ, Katowice, Poland.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1080/03610918.2020.1740263. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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