A Markov chain model for contagion

Angelos Dassios and Hongbiao Zhao

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: We introduce a bivariate Markov chain counting process with contagion for modelling the clustering arrival of loss claims with delayed settlement for an insurance company. It is a general continuous-time model framework that also has the potential to be applicable to modelling the clustering arrival of events, such as jumps, bankruptcies, crises and catastrophes in finance, insurance and economics with both internal contagion risk and external common risk. Key distributional properties, such as the moments and probability generating functions, for this process are derived. Some special cases with explicit results and numerical examples and the motivation for further actuarial applications are also discussed. The model can be considered a generalisation of the dynamic contagion process introduced by Dassios and Zhao (2011).

Keywords: risk model; contagion risk; bivariate point process; Markov chain model; discretised dynamic contagion process; dynamic contagion process (search for similar items in EconPapers)
JEL-codes: F3 G3 (search for similar items in EconPapers)
Date: 2014-11-05
New Economics Papers: this item is included in nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in Risks, 5, November, 2014, 2(4), pp. 434-455. ISSN: 2227-9091

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