Issue |
ITM Web Conf.
Volume 24, 2019
AMCSE 2018 - International Conference on Applied Mathematics, Computational Science and Systems Engineering
|
|
---|---|---|
Article Number | 02001 | |
Number of page(s) | 6 | |
Section | Computers | |
DOI | https://doi.org/10.1051/itmconf/20192402001 | |
Published online | 01 February 2019 |
Modelling of Insured Losses of Natural Catastrophes Using Block Maxima Model
University of Pardubice, Faculty of Economics and Administration, Institute of Mathematics and Quantitative Methods, Studentská 95, 532 10 Pardubice, Czech Republic
* Corresponding author: Pavla.Jindrova@upce.cz
Catastrophic events have a huge impact on society as a whole. Insurance, or reinsurance is one way of reducing the economic consequences of catastrophic events. By Sigma Swiss Re criteria the event can be noted as a catastrophe when the economic losses, insured claims or casualties associated with an event exceed just one of the thresholds. These thresholds are updated every year. We can observe a growing trend in both the number of catastrophic events as well as in total economic losses and insured losses too. Risk management of insurance and reinsurance companies have to have available relevant information for estimation and adjusting premium to cover these risks. The aim of this article is to present one of the useful method – block maxima method. This method uses information from historical events about insured losses of natural catastrophes and estimates future insured losses. These estimates are very important for actuaries and for risk managers as it is one of the bases for calculating and adjusting premiums of products covering these types of risks.
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.