The Detection and Dynamics of Financial Distress


  • *Earlier drafts of this paper were presented at the 2005 Financial Management Association meeting and the 2007 Southwest Finance Association meeting. The authors wish to thank Jingzhi (Jay) Huang, Kenneth Kim, Philip Perry, Samuel Tiras, Susan Lewis, Naohisa Goto, and especially an anonymous IRF referee and Editor Sudipto Dasgupta for helpful comments.

Joseph P. Ogden
School of Management 349 Jacobs Hall University at Buffalo – SUNY Buffalo, NY 14260, USA


Using samples of US firms, we examine the efficacy of six risk-proxy variables to forecast 5-year failure: year-end t-values of stock return volatility, firm size, recent profitability, market leverage (LEV), book-to-market equity ratio (BM), and recent stock return. Logistic regression results indicate that firm size is most powerful, while LEV and BM are weakest. We then identify distressed firms and analyze the effect of year t+1 operating and financing cash flows on 5-year failure rates for these firms using a new methodology, failure risk surprise. Results explain why LEV and BM are weak forecasters of 5-year failure rates: Low-LEV and low-BM (high-LEV and high-BM) distressed firms are less (more) likely to have a profit in year t+1, and are also more likely to issue equity (retire debt) in year t+1, interactions which tend to moderate failure risk. We also find that failure risk sensitivity to year t+1 operating result increases with both LEV and BM, while failure risk sensitivity to future macroeconomic conditions is significant only for high-LEV firms. Many results are consistent with the tradeoff theory of capital structure, while other results indicate that managers make financing decisions to take advantage of mispricing.