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

WPIEA2005219 Image
Price:  $15.00

Author/Editor: Matthew T. Jones
Release Date: © November, 2005
ISBN : 978-1-45186-238-6
Stock #: WPIEA2005219
English
Stock Status: Available

Languages and formats available

EnglishFrenchSpanishArabicRussianChinesePortuguese
PaperbackYes
PDFYes

Description

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.

Taxonomy

Banks and banking , Financial institutions and markets , Loans




More publications in this series: Working Papers


More publications by: Matthew T. Jones