Linking global economic dynamics to a South African-specific credit risk correlation model

Show simple item record

dc.contributor.author Van Eyden, Renee
dc.contributor.author Gupta, Rangan
dc.contributor.author De Wet, Albertus Hendrik
dc.date.accessioned 2009-09-10T08:41:14Z
dc.date.available 2009-09-10T08:41:14Z
dc.date.issued 2009
dc.description.abstract In order to address practical questions in credit portfolio management it is necessary to link the cyclical or systematic components of firm credit risk with the firm's own idiosyncratic credit risk as well as the systematic credit risk component of every other exposure in the portfolio. This paper builds on the methodology proposed by Pesaran, Schuermann, and Weiner [Pesaran, M.H., Schuermann, T., and Weiner, S.M., (2004), Modeling regional interdependencies using a global error correcting macroeconometric model, Journal of Business and Economic Statistics, 22, 2, 129–169.] and supplemented by Pesaran, Schuermann, Treutler and Weiner [Pesaran, M.H., Schuermann, T., Treutler, B., and Weiner, S.M., (2006), Macroeconomic dynamics and credit risk: a global perspective, Journal of Money, Credit, and Banking, Volume 38, Number 5, August 2006, 1211–1261.] which has made a significant advance in credit risk modelling in that it avoids the use of proprietary balance sheet and distance-to-default data, focusing on credit ratings which are more freely available. In this paper a country-specific macroeconometric risk-driver engine which is compatible with and could feed into the GVAR model and framework of PSW (2004) is constructed, using vector error-correcting (VECM) techniques. This allows conditional loss estimation of a South African-specific credit portfolio but also opens the door for credit portfolio modelling on a global scale, as such a model can easily be linked to the GVAR model. The set of domestic factors is extended beyond those used in PSW (2004) in such a way that the risk-driver model is applicable for both retail and corporate credit risk. As such, the model can be applied to a total bank balance sheet, incorporating the correlation and diversification between both retail and corporate credit exposures. Assuming statistical over-identification restrictions, the results indicate that it is possible to construct a South African component for the GVAR model that can easily be integrated into the global component. From a practical application perspective the framework and model is particularly appealing since it can be used as a theoretically consistent correlation model within a South African-specific credit portfolio management tool. en_US
dc.identifier.citation De Wet, A.H., et al., Linking global economic dynamics to a South African-specific credit risk correlation model, Econ. Model. (2009), doi:10.1016/j.econmod.2009.02.015 en_US
dc.identifier.issn 0264-9993
dc.identifier.other 10.1016/j.econmod.2009.02.015
dc.identifier.uri http://hdl.handle.net/2263/11188
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.rights Elsevier en_US
dc.subject Credit portfolio management en_US
dc.subject Multifactor model en_US
dc.subject Vector error correction model (VECM) en_US
dc.subject Credit correlations en_US
dc.subject.lcsh Credit -- Management -- Econometric models en
dc.title Linking global economic dynamics to a South African-specific credit risk correlation model en_US
dc.type Postprint Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record