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Portfolio credit risk and macroeconomic shocks : applications to stress testing under data-restricted environments

Author: Miguel A Segoviano; Pablo Padilla; International Monetary Fund. Monetary and Capital Markets Department.
Publisher: [Washington, D.C.] : International Monetary Fund, 2006.
Series: IMF working paper, WP/06/283.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Segoviano, Miguel A.
Portfolio credit risk and macroeconomic shocks.
[Washington, D.C.] : International Monetary Fund, 2006
(OCoLC)144528930
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Miguel A Segoviano; Pablo Padilla; International Monetary Fund. Monetary and Capital Markets Department.
OCLC Number: 535146946
Reproduction Notes: Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2010. MiAaHDL
Description: 1 online resource (50 pages) : illustrations.
Details: Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
Series Title: IMF working paper, WP/06/283.
Responsibility: prepared by Miguel A. Segoviano Basurto and Pablo Padilla.

Abstract:

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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