This paper intends to identify empirically the common characteristics of bankrupting firms from accounting and financial data. It provides not only ways of predicting firms headed for bankruptcy, but also identifying the pattern of failing firms over time. The Adaptive Learning Network (ALN), an...

We consider generalized monotone functions f: X -- {0,1} defined for an arbitrary binary relation = on X by the property x = y implies f(x) = f(y). These include the standard monotone (or positive) Boolean functions, regular Boolean functions and other interesting functions as special cases. It...

We consider generalized monotone functions f: X -- {0,1} defined for an arbitrary binary relation = on X by the property x = y implies f(x) = f(y). These include the standard monotone (or positive) Boolean functions, regular Boolean functions and other interesting functions as special cases. It...

Access to three years of annual reports and bank credit managers' assessments for 63 small businesses in New Zealand provides a strong basis to evaluate and to predict whether small businesses are likely to fail. Indicators of company failure are important, even crucial, to those who provide...

This paper analyses whether Z-score, as examined by Altman and other researchers, can predict correctly company failures. The empirical analysis concentrates on the construction companies listed in Athens Exchange, for the period 1995-2006, which coincides with significant construction activity...

This paper proposes a genetic-based hybrid approach to predict the possibility of corporate failure. We use Genetic Algorithm (GA) to select the critical variables set and optimise the weight of each classifier for integrating the best features of several classification approaches (such as...