Researcher ORCID Identifier
Date of Submission
Campus Only Senior Thesis
Bachelor of Arts
Carson J Bridges
This study seeks to examine which financial ratios are most relevant when attempting to predict bankruptcy in the high-tech industry. There are two different regression models that are looked at in this study. Both of the models utilize the same 687 non-bankrupt observations between the years 1978-2011. Model 1 compares this group to 33 observations of companies that went bankrupt the following year. These 33 companies all filed for Chapter 11 between 1979-2012. Model 2 compares the non-bankrupt group to 40 observations of companies that went bankrupt two years later. The two ratios that stood out as the most relevant for predicting bankruptcy in both of these models were the current ratio, and current financial leverage. Additionally, model 1 found the return on assets ratio to also be a solid predictor variable. Model 2 found that the sales to total assets ratio to be a solid predictor variable for companies going bankrupt two years in the future. Both models had high correct prediction rates for the total sample, with model 1 predicting 96.53% correctly and model 2 predicting 94.64% correctly. With that being said, model 1 only predicted 39.39% of the bankrupt group correctly and model 2 only predicted 10% of its bankrupt group correctly. A larger sample for these groups could have reduced this high rate of type II errors, but nonetheless it is a good start to predicting bankruptcy in an industry that has few known previous such studies.
Bridges, Carson J., "Predicting Bankruptcy in the High-Tech Industry Using a Binary Logistic Regression Model" (2021). CMC Senior Theses. 2736.
This thesis is restricted to the Claremont Colleges current faculty, students, and staff.