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

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
Table Of Contents
""Contents""; ""I. INTRODUCTION""; ""II. PORTFOLIO CREDIT RISK""; ""III. PROPOSAL TO IMPROVE PORTFOLIO CREDIT RISK MEASUREMENT""; ""IV. PROPOSED PROCEDURE FOR STRESS TESTING""; ""V. STRESS TESTING: EMPIRICAL IMPLEMENTATION IN DENMARK""; ""VI. ANALYSIS OF STRESS TESTING RESULTS""; ""VII. CONCLUSIONS""; ""Appendix 1: Entropy in a Nutshell""; ""References""
Language
eng
Literary Form
non fiction
Note
"December 2006."
Physical Description
1 online resource (52 p.)
Specific Material Designation
remote
Form Of Item
online
Isbn
9781462330621

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