A Markov Chain Model for Contagion

Risks

Angelos Dassios²  Hongbiao Zhao¹ 

[1] Department of Finance, School of Economics ＆ Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, Fujian 361005, China;Department of Statistics, London School of Economics, Houghton Street, London WC2A 2AE, UK

关键词: risk model;    contagion risk;    bivariate point process;    Markov chain model;    discretised dynamic contagion process;    dynamic contagion process;   

DOI  :  10.3390/risks2040434

来源: mdpi

【 摘 要 】

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).

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.