Bank-Sourced Transition Matrices: Are Banks' Internal Credit Risk Estimates Markovian?
|Author(s):|| Ing. Mgr. Barbora Štěpánková (Máková) M.A., |
|Type:||IES Working Papers|
|ISSN / ISBN:|
|Published in:||IES Working Papers 3/2019|
|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.