Impact of using industry benchmark financial ratios on performance of bankruptcy prediction logistic regression model

Mateusz Heba () and Marcin Chlebus ()
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Mateusz Heba: Faculty of Economic Sciences, University of Warsaw

No 2020-30, Working Papers from Faculty of Economic Sciences, University of Warsaw

Abstract: The phenomenon of companies bankruptcy is crucial for business partners and financial institutions due to the fact that business failure might be the cause of huge losses. Researchers has continually been aimed for improving models performance in the prediction of companies bankruptcy. Some authors of scientific papers claim that the process of evaluation of the companies situation requires comparison of its characteristics defined as financial ratio with situation of whole sector in order to obtain reliable conclusions. In this paper, a hypothesis that usage of the industry benchmarks (transformation of raw financial ratios values into sectoral deciles groups numbers) improves results of bankruptcy prediction logistic regression model is verified. Based on empirical results for Polish market, it turns out that although models estimated on different types of data have similar discriminatory power, logistic regression using raw financial ratios obtained a bit better results than its industry equivalents defined as sectoral deciles groups numbers. It is worth emphasizing that empirical part of paper uses information about 109K companies what is the rarity in bankruptcy prediction papers – researchers usually use small datasets that include less than several hundred records.

Keywords: bankruptcy prediction; financial ratios; industry financial ratios; sectoral financial ratios; logistic regression; financial econometrics (search for similar items in EconPapers)
JEL-codes: C52 C53 C58 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2020
New Economics Papers: this item is included in nep-cfn
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