Bankruptcy Prediction With Industry Effects

49 Pages Posted: 20 Oct 2001

See all articles by Sudheer Chava

Sudheer Chava

Georgia Institute of Technology - Scheller College of Business

Robert A. Jarrow

Cornell University - Samuel Curtis Johnson Graduate School of Management

Date Written: August 2004

Abstract

This paper investigates the forecasting accuracy of bankruptcy hazard rate models for U.S. companies over the time period 1962 - 1999 using both yearly and monthly observation intervals. The contribution of this paper is multiple-fold. One, using an expanded bankruptcy database we validate the superior forecasting performance of Shumway's (2001) model as opposed to Altman (1968) and Zmijewski (1984). Two, we demonstrate the importance of including industry effects in hazard rate estimation. Industry groupings are shown to significantly affect both the intercept and slope coefficients in the forecasting equations. Three, we extend the hazard rate model to apply to financial firms and monthly observation intervals. Due to data limitations, most of the existing literature employs only yearly observations. We show that bankruptcy prediction is markedly improved using monthly observation intervals. Fourth, consistent with the notion of market efficiency with respect to publicly available information, we demonstrate that accounting variables add little predictive power when market variables are already included in the bankruptcy model.

Keywords: Bankruptcy Prediction, Hazard Models, Industry Effects, Reduced Form Credit Risk Models

JEL Classification: G33, C41, G13

Suggested Citation

Chava, Sudheer and Jarrow, Robert A., Bankruptcy Prediction With Industry Effects (August 2004). Available at SSRN: https://ssrn.com/abstract=287474 or http://dx.doi.org/10.2139/ssrn.287474

Sudheer Chava (Contact Author)

Georgia Institute of Technology - Scheller College of Business ( email )

800 West Peachtree St.
Atlanta, GA 30308
United States

HOME PAGE: http://https://fintech.gatech.edu

Robert A. Jarrow

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Department of Finance
Ithaca, NY 14853
United States
607-255-4729 (Phone)
607-254-4590 (Fax)

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