A proposed multidimensional model for predicting financial distress: an empirical study on Egyptian listed firms

Noha Adel Mohamed Abdelkader () and Hayam Hassan Wahba ()
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Noha Adel Mohamed Abdelkader: Ain Shams University
Hayam Hassan Wahba: Ain Shams University

Future Business Journal, 2024, vol. 10, issue 1, 1-16

Abstract: Abstract Although there has been a growing interest by researchers worldwide over the past decades to identify the factors pertaining to corporate financial distress and to develop financial distress prediction models that serve as early warning signs to the various firm stakeholders, notably to date, studies that were conducted were context specific and cannot be objectively generalized to other countries and rendered mixed inconclusive results. Therefore, the main objective of this study is to thoroughly investigate the factors that affect corporate financial distress in Egypt and to develop a multidimensional financial distress prediction model. Using comprehensive data of EGX100 listed firms, the researcher examines the role played by financial ratios, market-based indicators, macroeconomic factors, and corporate governance mechanisms in modeling corporate financial distress. Empirical results indicate that after controlling for the COVID-19 effects, the most significant financial ratios in predicting corporate financial distress are the working capital to total assets ratio, earnings before interest and taxes to total assets ratio, and the sales to total assets ratio. Such ratios are negatively related to the likelihood of corporate financial distress. However, the market value of equity to total liabilities ratio, and GDP growth rate have a positive impact on the likelihood of financial distress. However, the retained earnings to total assets ratio, the corporate governance mechanisms, the firm market capitalization, the interest rate, and the consumer price index are insignificant in predicting corporate financial distress in the Egyptian context. The resulting model demonstrates outstanding classification accuracy at around 96%.

Keywords: Egypt; Financial distress; Logistic regression; Financial ratios; Market indicators; Macroeconomic factors; Corporate governance (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1186/s43093-024-00328-2

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