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Credit Risk Migration and Economic Cycles

Department of Economic and Social Sciences, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy
SDA Bocconi School of Management, 20136 Milan, Italy
Department of Industrial Engineering, University of Parma, 43100 Parma, Italy
Department of Law, Economics, Politics and Modern Languages, LUMSA University, 00193 Rome, Italy
Department of Management and Law, University of Siena, 53100 Siena, Italy
Author to whom correspondence should be addressed.
Risks 2019, 7(4), 109;
Received: 22 September 2019 / Revised: 13 October 2019 / Accepted: 19 October 2019 / Published: 29 October 2019
(This article belongs to the Special Issue Credit Risk Modeling and Management in Banking Business)
The misestimation of rating transition probabilities may lead banks to lend money incoherently with borrowers’ default trajectory, causing both a deterioration in asset quality and higher system distress. Applying a Mover-Stayer model to determine the migration risk of small and medium enterprises, we find that banks are over-estimating their credit risk resulting in excessive regulatory capital. This has important macroeconomic implications due to the fact that holding a large capital buffer is costly for banks and this in turn influences their ability to lend in the wider economy. This conclusion is particularly true during economic downturns with the consequence of exacerbating the cyclicality in risk capital that therefore acts to aggravate economic conditions further. We also explain part of the misevaluation of borrowers and the actual relevant weight of non-performing loans within banking portfolios: some of the prudential requirements, at least as regards EMS credit portfolios, cannot be considered effective as envisaged by the regulators who developed the “new” regulation in response to the most recent crisis. The Mover-Stayers approach helps to reduce calculation inaccuracy when analyzing the historical movements of borrowers’ ratings and consequently, improves the efficacy of the resource allocation process and banking industry stability. View Full-Text
Keywords: credit risk; Markov chains; absorbing state; rating migration credit risk; Markov chains; absorbing state; rating migration
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MDPI and ACS Style

Ferretti, C.; Gabbi, G.; Ganugi, P.; Sist, F.; Vozzella, P. Credit Risk Migration and Economic Cycles. Risks 2019, 7, 109.

AMA Style

Ferretti C, Gabbi G, Ganugi P, Sist F, Vozzella P. Credit Risk Migration and Economic Cycles. Risks. 2019; 7(4):109.

Chicago/Turabian Style

Ferretti, Camilla, Giampaolo Gabbi, Piero Ganugi, Federica Sist, and Pietro Vozzella. 2019. "Credit Risk Migration and Economic Cycles" Risks 7, no. 4: 109.

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