Modeling dependent credit rating transitions: a comparison of coupling schemes and empirical evidence

Dmitri Boreiko (), Y. M. Kaniovski () and G. Ch. Pflug ()
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Y. M. Kaniovski: Free University of Bozen-Bolzano
G. Ch. Pflug: University of Vienna

Central European Journal of Operations Research, 2016, vol. 24, issue 4, No 11, 989-1007

Abstract: Abstract Three coupling schemes for generating dependent credit rating transitions are compared and empirically tested. Their distributions, the corresponding variances and default correlations are characterized. Using Standard and Poor’s data for OECD countries, parameters of the models are estimated by the maximum likelihood method and MATLAB optimization software. Two pools of debtors are considered: with 5 and with 12 industry sectors. They are classified into two non-default credit classes. First portfolio mimics the Dow Jones iTraxx EUR market index. The default correlations evaluated for 12 industry sectors are confronted with their counterparts known for the US economy.

Keywords: Hidden variable; Coupled Markov chain; Idiosyncratic component; Common component; Maximum likelihood; Correlation; 90C30; 90C90 (search for similar items in EconPapers)
JEL-codes: C61 D44 G12 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10100-015-0415-6

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