Business failure prediction using the UTADIS multicriteria analysis method

Business failure prediction is one of the most essential problems in the field of financial management. The research on developing quantitative business failure prediction models has been focused on building discriminant models to distinguish among failed and non-failed firms. Several researchers in this field have proposed multivariate statistical discrimination techniques. This paper explores the applicability of multicriteria analysis to predict business failure. Four preference disaggregation methods, namely the UTADIS method and three of its variants, are compared to three well-known multivariate statistical and econometric techniques, namely discriminant analysis, logit and probit analyses. A basic (learning) sample and a holdout (testing) sample are used to perform the comparison. Through this comparison, the relative performance of all the aforementioned methods is investigated regarding their discriminating and predicting ability.

[1]  Eric Jacquet-Lagrèze,et al.  An Application of the UTA Discriminant Model for the Evaluation of R & D Projects , 1995 .

[2]  Kevin Keasey,et al.  Multilogit approach to predicting corporate failure—Further analysis and the issue of signal consistency , 1990 .

[3]  Kenth Skogsvik,et al.  CURRENT COST ACCOUNTING RATIOS AS PREDICTORS OF BUSINESS FAILURE: THE SWEDISH CASE , 1990 .

[4]  Yash P. Gupta,et al.  LINEAR GOAL PROGRAMMING AS AN ALTERNATIVE TO MULTIVARIATE DISCRIMINANT ANALYSIS: A NOTE , 1990 .

[5]  Edward I. Altman,et al.  FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY , 1968 .

[6]  Constantin Zopounidis,et al.  A survey of business failures with an emphasis on prediction methods and industrial applications , 1996 .

[7]  C. Zopounidis,et al.  A Multicriteria Decision Aid Methodology for Sorting Decision Problems: The Case of Financial Distress , 1999 .

[8]  Gordon V. Karels,et al.  Multivariate Normality and Forecasting of Business Bankruptcy , 1987 .

[9]  James V. Hansen,et al.  Inducing rules for expert system development: an example using default and bankruptcy data , 1988 .

[10]  K. Keasey,et al.  Financial Distress Prediction Models: A Review of Their Usefulness1 , 1991 .

[11]  Constantin Zopounidis,et al.  Multicriteria decision aid in financial management , 1999, Eur. J. Oper. Res..

[12]  Edward I. Altman,et al.  Application of Classification Techniques in Business, Banking and Finance. , 1983 .

[13]  Constantin Zopounidis,et al.  Multicriteria Decision Aid Methods for the Prediction of Business Failure , 1998 .

[14]  Constantin Zopounidis,et al.  THE USE OF THE PREFERENCE DISAGGREGATION ANALYSIS IN THE ASSESSMENT OF FINANCIAL RISKS , 1998 .

[15]  J. Siskos.  Assessing a set of additive utility functions for multicriteria decision-making , 1982 .

[16]  Constantin Zopounidis,et al.  Application of the Rough Set Approach to Evaluation of Bankruptcy Risk , 1995 .

[17]  Daniel Martin,et al.  Early warning of bank failure: A logit regression approach , 1977 .

[18]  Ramesh Sharda,et al.  Bankruptcy prediction using neural networks , 1994, Decis. Support Syst..

[19]  J. Courtis.  MODELLING A FINANCIAL RATIOS CATEGORIC FRAMEWORK , 1978 .

[20]  Erkki K. Laitinen,et al.  Prediction of failure of a newly founded firm , 1992 .

[21]  Peter J. Elmer,et al.  An Expert System Approach to Financial Analysis: The Case of S&L Bankruptcy , 1988 .

[22]  Katherine Schipper,et al.  Application of Classification Techniques in Business, Banking and Finance. , 1983 .

[23]  C. Zopounidis,et al.  Developing a multicriteria decision support system for financial classification problems: the finclas system , 1998 .

[24]  Ignacio Olmeda,et al.  Hybrid Classifiers for Financial Multicriteria Decision Making: The Case of Bankruptcy Prediction , 1997 .

[25]  C. Zavgren.  ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS , 1985 .

[26]  J. Efrim Boritz,et al.  Effectiveness of neural network types for prediction of business failure , 1995 .