Estimating Markov Transition Matrices Using Proportions Data: An Application to Credit Risk
AbstractThis 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.
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Bibliographic InfoPaper provided by International Monetary Fund in its series IMF Working Papers with number 05/219.
Date of creation: 01 Nov 2005
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-03-05 (All new papers)
- NEP-BEC-2006-03-05 (Business Economics)
- NEP-FMK-2006-03-05 (Financial Markets)
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