Detection of financial distress via multivariate statistical analysis

Describes the ability of modern computer-driven multivariate statistical analysis to deal with
complex data and the development of statistical models for predicting financial distress.
Applies multivariate techniques to 1986-1991 financial ratio data for Australian failed (29)
and nonfailed (42) companies; and explains the techniques used (principal components
analysis, factor analysis, discriminant analysis and cluster analysis) and the different types of
information they can provide to help identify the distress levels of companies. Predicts that
multivariate methods will change the way researchers think about problems and design their
research. An unusually clear exposition of the application of multivariate methods.