Bivariate Semi-Markov Process for Counterparty Credit Risk

We consider the problem of constructing an appropriate multivariate model to study counterparty credit risk in the credit rating migration problem. For this financial problem different multivariate Markov chain models were proposed. However, the Markovian assumption may be inappropriate for the stud...

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Bibliographic Details
Published in:Communications in statistics. Theory and methods 2014-04, Vol.43 (7), p.1503-1522
Main Authors: D'amico, Guglielmo, Manca, Raimondo, Salvi, Giovanni
Format: Article
Language:English
Subjects:
Algorithm
Chains
Construction costs
Counterparty credit risk
Derivatives
Dynamic tests
Markov analysis
Markov processes
Mathematical analysis
Migration
Multivariate semi-Markov chains
Risk
Statistics
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Summary:We consider the problem of constructing an appropriate multivariate model to study counterparty credit risk in the credit rating migration problem. For this financial problem different multivariate Markov chain models were proposed. However, the Markovian assumption may be inappropriate for the study of the dynamics of credit ratings, which typically show non Markovian-like behavior. In this article, we develop a semi-Markov approach to study the counterparty credit risk by defining a new multivariate semi-Markov chain model. Methods are given for computing the transition probabilities, reliability functions and the price of a risky Credit Default Swap.
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2013.804563