Template-Type: ReDIF-Paper 1.0
Author-Name: Camilla Ferretti
Author-X-Name-First: Camilla
Author-X-Name-Last: Ferretti
Author-Email: camilla.ferretti@unicatt.it
Author-Workplace-Name: DISCE, Università Cattolica
Author-Name: Giampaolo Gabbi
Author-X-Name-First: Giampaolo
Author-X-Name-Last: Gabbi
Author-Email: giampaolo.gabbi@unisi.it
Author-Workplace-Name: DISAG, Università di Siena
Author-Name: Piero Ganugi
Author-X-Name-First: Piero
Author-X-Name-Last: Ganugi
Author-Email: piero.ganugi@unipr.it
Author-Workplace-Name: DIA, Università di Parma
Author-Name: Pietro Vozzella
Author-X-Name-First: Pietro
Author-X-Name-Last: Vozzella
Author-Email: vozzy71@gmail.com
Author-Workplace-Name: DISAG, Università di Siena
Title: Rating Trajectories and Credit Risk Migration: Evidence for SMEs
Abstract: 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 overestimating 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 nonperforming loans within banking portfolios: prudential prescriptions cannot be considered as effective as expected by regulators who have designed 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. 
Length: 27 pages
Creation-Date: 2016-07
Publication-Status:
File-URL: http://dipartimenti.unicatt.it/dises-dises_wp_16_115.pdf
File-Format: Application/pdf
File-Function: First version, 2016
Number: dises1615
Keywords: credit risk; Markov chains; absorbing state; rating migration 
Handle: RePEc:ctc:serie2:dises1615