An empirical evaluation of the effectiveness of financial ratio analysis in predicting corporate bankruptcy for technology firms in the United States.
Luu, Thi Thu Trang.
Tran, Thu Thao.
Tan, Hong Yi.
Date of Issue2010
College of Business (Nanyang Business School)
In the field of measuring and managing credit risk, structural models have gained wide recognition due to their ability to anticipate firm’s default risk very early. On the other hand, traditional methods of assessing credit risk such as ratings and financial ratios analysis have their appeal in its being unsophisticated and easy to understand. This paper aims to calibrate a model which is simplistic yet effective at warning firm’s default risk. Our analysis covers 64 listed technology firms in the United Stated whose stocks and options had been actively traded from 1998-2008. Study reveals that there is a weak positive correlation between the probabilities of default (PD) predicted by the Merton’s model and Standard & Poor’s average 1-year default rates for different rating scales. Consistent with studies done by KMV Corporation, it suggests that ratings may not be responsive to firm’s changing default risk. Distance-to-default (D2), in the (Merton, 1974) structural model, is found to be positively correlated with four out of five independent variables in the well-known Altman Credit- Scoring Model. D2 also has positive correlation with other financial ratios which were selected based on the criteria set by (Chen & Shimerda, 1981). Out of all these financial ratios, two, namely earnings before interest and taxes/total assets (EBIT/TA) and cash flow to sales (CF/S), appear to be strong predictors of D2. Finally, the research concludes with a simple and effective multivariate model of D2.
Final Year Project (FYP)
Nanyang Technological University