Portfolio Credit Risk and Macroeconomic Shocks : Applications to Stress Testing Under Data-Restricted Environments /

Portfolio credit risk measurement is greatly affected by data constraints, especially when focusing on loans given to unlisted firms. Standard methodologies adopt convenient, but not necessarily properly specified parametric distributions or simply ignore the effects of macroeconomic shocks on credi...

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Detalles Bibliográficos
Autor principal: Segoviano, Miguel
Formato: Revista
Lenguaje:English
Publicado: Washington, D.C. : International Monetary Fund, 2006.
Colección:IMF Working Papers; Working Paper ; No. 2006/283
Acceso en línea:Full text available on IMF
Descripción
Sumario:Portfolio credit risk measurement is greatly affected by data constraints, especially when focusing on loans given to unlisted firms. Standard methodologies adopt convenient, but not necessarily properly specified parametric distributions or simply ignore the effects of macroeconomic shocks on credit risk. Aiming to improve the measurement of portfolio credit risk, we propose the joint implementation of two new methodologies, namely the conditional probability of default (CoPoD) methodology and the consistent information multivariate density optimizing (CIMDO) methodology. CoPoD incorporates the effects of macroeconomic shocks into credit risk, recovering robust estimators when only short time series of loans exist. CIMDO recovers portfolio multivariate distributions (on which portfolio credit risk measurement relies) with improved specifications, when only partial information about borrowers is available. Implementation is straightforward and can be very useful in stress testing exercises (STEs), as illustrated by the STE carried out within the Danish Financial Sector Assessment Program.
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Descripción Física:1 online resource (50 pages)
Formato:Mode of access: Internet
ISSN:1018-5941
Acceso:Electronic access restricted to authorized BRAC University faculty, staff and students