Modeling of Dependent Credit Rating Transitions Governed by Industry-Specific Markovian Matrices

Dmitri Boreiko (), Yuri (Yuriy) Kaniovski (Kaniovskyi) () and Georg Ch. Pflug
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Georg Ch. Pflug: University of Vienna

A chapter in Operations Research Proceedings 2015, 2017, pp 525-531 from Springer

Abstract: Abstract Two coupling schemes where probabilities of credit rating migrations vary across industry sectors are introduced. Favorable and adverse macroeconomic factors, encoded as values 1 and 0, of credit class- and industry-specific unobserved tendency variables, modify the transition probabilities rendering individual evolutions dependent. Unlike in the known coupling schemes, expansion in some industry sectors and credit classes coexists with shrinkage in the rest. The schemes are tested on Standard and Poor’s data. Maximum likelihood estimators and MATLAB optimization software were used.

Keywords: Credit Rating; Common Component; Industry Sector; Markov Chain Model; Coupling Scheme (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-319-42902-1_71

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DOI: 10.1007/978-3-319-42902-1_71

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