Direct and Hierarchical Models for Aggregating Spatially Dependent Catastrophe Risks

Autor:	Rafał Wójcik, Charlie Wusuo Liu, Jayanta Guin
Jazyk:	angličtina
Rok vydání:	2019
Předmět:	risk aggregation numerical convolution copula trees Monte-Carlo simulation spatial correlation Insurance HG8011-9999
Zdroj:	Risks, Vol 7, Iss 2, p 54 (2019)
Druh dokumentu:	article
ISSN:	2227-9091
DOI:	10.3390/risks7020054
Popis:	We present several fast algorithms for computing the distribution of a sum of spatially dependent, discrete random variables to aggregate catastrophe risk. The algorithms are based on direct and hierarchical copula trees. Computing speed comes from the fact that loss aggregation at branching nodes is based on combination of fast approximation to brute-force convolution, arithmetization (regriding) and linear complexity of the method for computing the distribution of comonotonic sum of risks. We discuss the impact of tree topology on the second-order moments and tail statistics of the resulting distribution of the total risk. We test the performance of the presented models by accumulating ground-up loss for 29,000 risks affected by hurricane peril.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/c200bfec48d9458692b18268f27e25a0 Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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