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dc.contributor.authorBoreiko D
dc.contributor.authorKaniovski Y
dc.contributor.authorPflug G
dc.contributor.editorDoerner K
dc.contributor.editorLjubic I
dc.contributor.editorPflug G
dc.contributor.editorTragler G
dc.contributor.other
dc.date.accessioned2017-11-07T13:31:39Z
dc.date.available2017-11-07T13:31:39Z
dc.date.issued2017
dc.identifier.isbn978-3-319-42901-4
dc.identifier.issn0721-5924
dc.identifier.urihttp://dx.doi.org/10.1007/978-3-319-42902-1_71
dc.identifier.urihttp://link.springer.com/chapter/10.1007/978-3-319-42902-1_71
dc.identifier.urihttp://hdl.handle.net/10863/3555
dc.description.abstractTwo 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.en_US
dc.language.isoenen_US
dc.publisherSpringer International Publishingen_US
dc.relation.ispartofseriesOperations Research Proceedings;
dc.rights
dc.titleModeling of dependent credit rating transitions governed by industry-specific Markovian matricesen_US
dc.typeBook chapteren_US
dc.date.updated2017-05-05T08:27:24Z
dc.publication.titleOperations Research Proceedings 2015: Selected Papers of the International Conference of the German, Austrian and Swiss Operations Research Societies (GOR, ÖGOR, SVOR/ASRO), University of Vienna, Austria, September 1-4, 2015
dc.language.isiEN-GB
dc.description.fulltextreserveden_US


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