Affiliation:
1. Institute of Mathematics and Quantitative Methods Faculty of Economics and Administration University of Pardubice Studentská 95, 532 10 Pardubice 2 CZECH REPUBLIC
Abstract
This article aims to present the application of probability modelling and simulations based on quantile function of extreme insured losses in the world natural catastrophes based on data in time period 1970-2014, published in Swiss Re Sigma No2/2015. Quantile function provides an appropriate and flexible approach to the probability modelling needed to obtain well-fitted tails. We are specifically interested in modelling and simulations the tails of loss distributions. In a number of applications of quantile functions in insurance and reinsurance risk management interest focuses particularly on the extreme observations in the upper tail of probability distribution. Fortunately it is possible to simulate the observations in one tail of distribution without simulating the central values. This advantage will be used for estimate a few extreme high insured losses in the world’s natural catastrophes in future.
Publisher
World Scientific and Engineering Academy and Society (WSEAS)
Subject
Law,Philosophy,General Medicine,Sociology and Political Science,Law,Plant Science,Soil Science,Agronomy and Crop Science,Philosophy,Law,Political Science and International Relations,Tourism, Leisure and Hospitality Management,Sociology and Political Science,Environmental Science (miscellaneous),Tourism, Leisure and Hospitality Management,Geography, Planning and Development,Tourism, Leisure and Hospitality Management,Geography, Planning and Development
Reference13 articles.
1. W. G. Gilchrist, Statistical Modelling with Quantile Functions, Chapman & Hall/CRC, London 2000.
2. R. J. Gray, S. M. Pitts, Risk Modelling in General Insurance. Cambridge University Press, 2012, ch. 2.
3. P. Jindrová, Ľ. Sipková, Statistical Tools for Modeling Claim Severity. In: European Financial Systems 2014. Proceedings of the 11th International Scientific Conference. Lednice, June 12-13, 2014. Brno: Masaryk University, 2014, pp. 288-294.
4. A. J. McNeil, A., Estimating the Tails of Loss Severity Distributions using Extreme Value Theory. ETH Zentrum, Zürich 1996. [online]. Available on: https://www.casact.org/library/astin/vol27no1/1 17.pdf
5. V. Pacáková, B. Linda, Simulations of Extreme Losses in Non-Life Insurance. E+M Economics and Management, Volume XII, 4/2009.