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

November 1, 2005

Preview Citation

Format: Chicago

Matthew T Jones. Estimating Markov Transition Matrices Using Proportions Data: An Application to Credit Risk, (USA: International Monetary Fund, 2005) accessed November 24, 2024

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

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.

Subject: Credit, Credit ratings, Credit risk, Loans, Nonperforming loans

Keywords: Real gross domestic product, WP

Publication Details

Pages:

27
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2005/219
Stock No:

WPIEA2005219
ISBN:

9781451862386
ISSN:

1018-5941

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