The use of financial ratios in predicting financial distress of listed entities in Sri Lanka - Akil, M.A.M.; Perera, W.T.N.M.; Wijekoon, W.M.H.N. (University of Jaffna, 2024)
Corporate failure represents the most severe circumstance an organization or a business entity may encounter. Consequently, forecasting impending financial distress is paramount in circumventing corporate failures and shakeouts. This study aims to construct a framework employing the formulated financial indicators to anticipate the financial distress of listed companies in Sri Lanka. The research encompasses many listed entities in the Colombo Stock Exchange, except for financial institutions. It relies on publicly accessible information from the corporate annual reports of a comprehensive sample of 50 firms. These firms are divided into two clusters, namely 25 distressed firms and 25 non-distressed firms, which possess comparable capacities. The investigation spans 6 years, commencing in 2016 and concluding in 2021. A set of ten devised financial ratios were utilized to ascertain the model and examined through logistic regression analysis. The findings from the statistical tests revealed that the model's ability to forecast accurately, in line with the financial ratios, stands at 77.86% one year before the onset of financial distress. Moreover, the model's predictive performance remains commendable, with an accuracy that surpasses 72% throughout the three years leading to financial distress. As a result, it can be concluded that the model's robustness in generating reliable outcomes extends up to three years before the manifestation of failure. Therefore, in relation to the requisite and the prevailing circumstances, the enterprises, shareholders, workers, providers, banking establishments, regulatory entities, and assessors will derive advantageous insights from the advanced framework in Anticipating the financial distress of listed entities in Sri Lanka.
Keywords: Financial Distress; Corporate Failure; Financial Ratios; Listed Entities; JEL Classification: G10