Bank-Sourced Transition Matrices: Are Banks' Internal Credit Risk Estimates Markovian?
| Author(s): | Ing. Mgr. Barbora Štěpánková M.A., Ph.D., |
|---|---|
| Type: | IES Working Papers |
| Year: | 2019 |
| Number: | 3 |
| ISSN / ISBN: | |
| Published in: | IES Working Papers 3/2019 |
| Publishing place: | Prague |
| Keywords: | Risk management, credit risk, transition matrices |
| JEL codes: | C12, G12, G21, G32 |
| Suggested Citation: | Máková B. (2019): “Bank-Sourced Transition Matrices: Are Banks' Internal Credit Risk Estimates Markovian? ” IES Working Papers 3/2019. IES FSV. Charles University. |
| Grants: | GAUK No. 1278218 Credit Transition matrices based on bank-sourced data and the business cycle |
| Abstract: | This study provides new insights into banks' credit risk models by exploring features of their credit risk estimates and assessing practicalities of transition matrix estimation and related assumptions. Using a unique dataset of internal credit risk estimates from twelve global A-IRB banks, covering monthly observations on 20,000 North American and EU large corporates over the 2015-2018 time period, the study empirically tests the widely used assumptions of the Markovian property and time homogeneity at a larger scale than previously documented in the literature. The results show that internal credit risk estimates do not satisfy these assumptions as they show evidence of both path-dependency and time heterogeneity. In addition, contradicting previous findings on credit rating agency data, banks tend to revert their rating actions. |
| Downloadable: |
wp_2019_03_makova |
