Bankruptcy Prediction for Restaurant Firms: A Comparative Analysis of Multiple Discriminant Analysis and Logistic Regression

Yang Huo, Leo H. Chan () and Doug Miller
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Leo H. Chan: Department of Finance and Economics, Utah Valley University, Orem, UT 84058, USA
Doug Miller: Department of Strategy Management and Operations, Utah Valley University, Orem, UT 84058, USA

JRFM, 2024, vol. 17, issue 9, 1-15

Abstract: In this paper, we used data from publicly traded restaurant firms between 2000 and 2019 to test the effectiveness of multiple discriminant analysis (MDA) and logistic regression (logit) in predicting the probability of bankruptcy in the restaurant industry. We constructed various financial ratios extracted from the financial information and analyzed them to determine the optimal models. Our results show that liquid ratios (particularly the quick ratio), operating cash flow, and working capital emerge as the most crucial indicators of potential bankruptcy filings for restaurant firms. The results also show that the logit model performs better within the sample. However, both models exhibit similar predictive capacities with out-of-sample data.

Keywords: bankruptcy prediction model; financial ratios; business failure; logistic regression; multidiscriminant analysis (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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