Financial ratios, discriminant analysis and the prediction of corporate bankruptcy.pdf

The Journal of FINANCE VOL. XXIII SEPTEMBER 1968 FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY EDWARD I. ALTMAN* ACADEMICIANS SEEM to be moving toward the elimination of ratio analysis as an analytical technique in assessing the performance of the business enterprise. Theorists downgrade arbitrary rules of thumb, such pany pari- sons, widely used by practitioners. Since attacks on the relevance of ratio analysis emanate from many esteemed members of the scholarly world, does this mean that ratio analysis is limited to the world of "nuts and bolts"? Or, has the significance of such an approach been unattractively garbed and there- fore unfairly handicapped? Can we bridge the gap, rather than sever the link, between traditional ratio "analysis" and the more rigorous statistical tech- niques which have e popular among academicians in recent years? The purpose of this paper is to attempt an assessment of this issue-the quality of ratio analysis as an analytical technique. The prediction of corporate bankruptcy is used as an illustrative case.' Specifically, a set of financial and economicratios will be investigated in a bankruptcy prediction context wherein a multiple discriminant statistical methodology is employed. The data used in the study are limited to manufacturing corporations. Abrief review of the development of traditional ratio analysis as a technique for investigating corporate performance is presented in section section II the ings of this approach are discussed and multiple discriminant anal- ysis is introduced with the emphasis centering on patibility with ratio analysis in a bankruptcy prediction context. The discriminant model is devel- oped in section III, where an initial sample of sixty-six firms is utilized to establish a function which best discriminates panies in two mutu- ally exclusive groups: bankrupt and non-bankrupt firms. Section IV reviews empirical results obtained from the initial sample and