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

Barbora Máková ()
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Barbora Máková: Institute of Economic Studies, Faculty of Social Science, Charles University, Prague, Czech Republic

No 2019/3, Working Papers IES from Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies

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.

Keywords: Risk management; credit risk; transition matrices (search for similar items in EconPapers)
JEL-codes: C12 G12 G21 G32 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2019-03, Revised 2019-03
New Economics Papers: this item is included in nep-ban, nep-ore and nep-rmg
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