Modeling Credit Risk for Smes: Evidence from the Us Market

48 Pages Posted: 27 Dec 2005

See all articles by Edward I. Altman

Edward I. Altman

New York University (NYU) - Salomon Center; New York University (NYU) - Department of Finance

Gabriele Sabato

Wiserfunding

Date Written: December 26, 2005

Abstract

Considering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries and the considerable attention placed on SMEs in the new Basel Capital Accord, we develop a distress prediction model specifically for the SME sector and to analyze its effectiveness compared to a generic corporate model. The behavior of financial measures for SMEs is analyzed and the most significant variables in predicting the entities' credit worthiness are selected in order to construct a default prediction model. Using a logit regression technique on a panel of over 2,000 US firms (with sales less than $65 million) over the period 1994-2002, we develop a one-year default prediction model. This model has an out of sample prediction power which is almost 30% higher than a generic corporate model. An associated objective is to observe our model's ability to lower bank capital requirements considering the new Basel Capital Accord's rules for SMEs.

Keywords: SME finance, Modeling credit risk, Basel II, Bank capital requirements

JEL Classification: G21, G28

Suggested Citation

Altman, Edward I. and Sabato, Gabriele, Modeling Credit Risk for Smes: Evidence from the Us Market (December 26, 2005). Available at SSRN: https://ssrn.com/abstract=872336 or http://dx.doi.org/10.2139/ssrn.872336

Edward I. Altman

New York University (NYU) - Salomon Center ( email )

44 West 4th Street
New York, NY 10012
United States
212-998-0709 (Phone)
212-995-4220 (Fax)

New York University (NYU) - Department of Finance ( email )

Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States

Gabriele Sabato (Contact Author)

Wiserfunding ( email )

Grand Union House
20 Kentish Town Road
London, NW1 9NX
United Kingdom

HOME PAGE: http://www.wiserfunding.com

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
3,609
Abstract Views
15,599
Rank
5,817
PlumX Metrics