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Estimating Markov Transition Matrices Using Proportions Data :, An Application to Credit Risk, Matthew Jones

Abstract
This paper outlines a way to estimate transition matrices for use in credit risk modeling with a decades-old methodology that uses aggregate proportions data. This methodology is ideal for credit-risk applications where there is a paucity of data on changes in credit quality, especially at an aggregate level. Using a generalized least squares variant of the methodology, this paper provides estimates of transition matrices for the United States using both nonperforming loan data and interest coverage data. The methodology can be employed to condition the matrices on economic fundamentals and provide separate transition matrices for expansions and contractions, for example. The transition matrices can also be used as an input into other credit-risk models that use transition matrices as a basic building block
Table Of Contents
""Contents""; ""I. INTRODUCTION""; ""II. CREDIT QUALITY DYNAMICS USING TRANSITION MATRICES""; ""III. APPLICATION TO U.S. DATA""; ""IV. ADDITIONAL APPLICATIONS""; ""V. CONCLUSIONS""; ""TECHNICAL APPENDIX""; ""REFERENCES""
Language
eng
Literary Form
non fiction
Note
Description based upon print version of record
Physical Description
1 online resource (27 p.)
Specific Material Designation
remote
Form Of Item
online
Isbn
9786613830241

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