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Predicting corporate financial distress: A new neural networks approach

Abstract

This paper examines and models the financial distress prediction using neural network approach. Nine different neural network models, considering various predicting time horizons and information structures, are constructed. In order to test models' predictive capability we used a set of 15 financial ratios. Based on financial statements (balancesheets, result accounts and cash flow statements) for 87 Tunisian firms from 1993 to 1996, results prove that more the predictability horizon is short and the input information structure recent, more and better is the predictive capability of the neural model. Short debt, capital structure and sales growth and liquidity ratios contribute ...

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