Predicting The Financial Failure Of Retail Companies In The United States

Abstract

Predicting the financial failure of companies using financial ratios is a topic that has been explored in various ways for many years, and the current economic climate suggests that these models may still be more useful than ever.  Various financial ratios and bankruptcy prediction methods have been used in order to try to find the most accurate prediction model possible.  With historically successful retailers, like Sears, Kmart and JCPenney, struggling in recent years, predicting the future of retailers has become even more important.

Therefore, this paper focuses specifically on the application of a failure prediction model to companies from the retail industry.  Logistic regressions are used in this study in order to attempt to predict which companies are likely to fail.  The sample for this study includes publicly traded United States companies from the retail industry, and data is collected from the COMPUSTAT database for the period from 2005-2012.  Based on prior studies, the author hypothesizes that companies are most likely to fail if they are unprofitable, highly leveraged, and having cash flow problems.  As expected, the results demonstrate that smaller retail companies with fewer employees are more likely to fail.  The results also provide strong evidence that firms with lower cash to current liability ratios, lower cash flow margins, and higher debt to equity ratios are more likely to file for bankruptcy.