Generalized Pareto Fit to the Society of Actuaries’ Large Claims Database
Authors:
- 1 July 2003
- journal article
- research article
- Published by Taylor & Francis in North American Actuarial Journal
- Vol. 7 (3) , 18-36
Abstract
This paper discusses a statistical modeling strategy based on extreme value theory to describe the behavior of an insurance portfolio, with particular emphasis on large claims. The strategy is illustrated using the 1991–92 group medical claims database maintained by the Society of Actuaries. Using extreme value theory, the modeling strategy focuses on the “excesses over threshold” approach to fit generalized Pareto distributions. The proposed strategy is compared to standard parametric modeling based on gamma, lognormal, and log-gamma distributions. Extreme value theory outperforms classical parametric fits and allows the actuary to easily estimate high quantiles and the probable maximum loss from the data.Keywords
This publication has 8 references indexed in Scilit:
- Extreme Value Theory as a Risk Management ToolNorth American Actuarial Journal, 1999
- Estimating the Tails of Loss Severity Distributions Using Extreme Value TheoryASTIN Bulletin, 1997
- Modelling Extremal Events1997
- Parameter and Quantile Estimation for the Generalized Pareto DistributionTechnometrics, 1987
- Extremes and Related Properties of Random Sequences and Processes1983
- Estimates for the probability of ruin with special emphasis on the possibility of large claimsInsurance: Mathematics and Economics, 1982
- Statistical Inference Using Extreme Order StatisticsThe Annals of Statistics, 1975
- Residual Life Time at Great AgeThe Annals of Probability, 1974