Publication detail

Bank-Sourced Transition Matrices: Are Banks' Internal Credit Risk Estimates Markovian?

Author(s): Ing. Mgr. Barbora Štěpánková (Máková) M.A.,
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

Partners

Deloitte

Sponsors

CRIF
McKinsey
Patria Finance