Article2002

Grammatical Evolution And Corporate Failure Prediction

Anthony Brabazon · Michael O’Neill · Robin Matthews · Conor Ryan

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Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Evolutionary Algorithms and Applications

Abstract

This study examines the potential of Grammatical Evolution to uncover a series of useful rules which can assist in predicting corporate failure using information drawn from financial statements. A sample of 178 publically quoted, failed and non-failed US firms, drawn from the period 1991 to 2000 are used to train and test the model. The preliminary findings indicate that the methodology has much potential. 1

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2003The Theory of Economic Development 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 1966Financial Ratios As Predictors of Failure 1984Methodological Issues Related to the Estimation of Financial Distress Prediction Models 1977ZETATM analysis A new model to identify bankruptcy risk of corporations 1990Financial distress, reorganization, and organizational efficiency 2013Predicting financial distress of companies: revisiting the Z-Score and ZETA® models

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2004Diagnosing corporate stability using grammatical evolution 2009Determinants of Financial Distress of ST and PT Companies: A Panel Analysis of Chinese Listed Companies 2015Corporate Failure Prediction of Public Listed Companies in Malaysia 2003Anticipating Bankruptcy Reorganisation from Raw Financial Data Using Grammatical Evolution

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