A Preformance Analysis of Parametric and Nonparametric Discriminant Approaches to Business Decision Making

This paper empirically investigation the performance of four relatively new nonparametric techniques against four different parameteric versions of discriminant analysis. The models were constructed and analyzed using financial data drawn from 232 bankrupt and nonbankrupt companies. Generally, the nonparametric approaches, with the exception of linear programming, performed as well as or better than the more traditional discriminant analysis.