Open AccessDiscriminant Methods for Bankruptcy Prediction - Theory and Applications
Author(s) -
Józef Pociecha
Publication year - 2005
Publication title -
ekonomika
Language(s) - English
Resource type - Journals
eISSN - 2424-6166
pISSN - 1392-1258
DOI - 10.15388/ekon.2005.17534
Subject(s) - linear discriminant analysis , bankruptcy , discriminant function analysis , discriminant , multiple discriminant analysis , optimal discriminant analysis , econometrics , stability (learning theory) , function (biology) , sample (material) , interpretation (philosophy) , mathematics , statistics , economics , artificial intelligence , computer science , machine learning , finance , biology , chemistry , chromatography , evolutionary biology , programming language
Discriminant analysis consists of assigning an individual to two (or more) distinct populations, on the basis of observations of several characters of the individuals and a sample of observations of these characters from the populations. R. A. Fisher suggested a linear function of variables representing different characters, called linear discriminant function, for classifying an individual into one of the two populations. E. I. Altman adapted this approach to identify bankruptcy risk of corporations. Altman’s model of bankruptcy was estimated for various countries, thereby for Polish economy. Some results of estimation and interpretation of Altman’s model for Polish economy are presented in the paper. Methodological problems of discriminant analysis, especially fulfilling the basic assumptions, the analytical form of the discriminant function, the stability of the model and the estimation problems are also discussed.