Predicting multilateral trade credit risks: comparisons of Logit and Fuzzy Logic models using ROC curve analysis

Employing pooled data of 3344 listed firms from seven Asia-Pacific countries, this is the first empirical study to classify and predict trade credit risks in the international trade context. In addition, this paper extends previous work by applying receiver operating characteristic (ROC) curve analysis to compare the model performance of Logit to that of Fuzzy Logic (FL). We are unaware of any other paper that has discussed the application of ROC curve analysis in the business and finance literature. The results show that FL exceeds Logit in terms of overall classification accuracy and prediction accuracy. However, by incorporating measurement in the form of ROC curves, Logit is proven to outperform FL in classifying non-default firms. This suggests that though FL is superior in overall accuracy and in classifying default firms, Logit is preferable in situations where higher accuracy in classifying non-default firms is preferred. The stability of the models is also demonstrated.

[1]  J Levy,et al.  A fuzzy logic evaluation system for commercial loan analysis , 1991 .

[2]  Chris Lloyd,et al.  Using Smoothed Receiver Operating Characteristic Curves to Summarize and Compare Diagnostic Systems , 1998 .

[3]  Krishna G. Palepu,et al.  Predicting takeover targets: A methodological and empirical analysis , 1986 .

[4]  Hussein Dourra,et al.  Investment using technical analysis and fuzzy logic , 2002, Fuzzy Sets Syst..

[5]  Caren Marzban,et al.  Bayesian Probability and Scalar Performance Measures in Gaussian Models , 1998 .

[6]  Liang Wang,et al.  Complex systems modeling via fuzzy logic , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[7]  Mu-Chun Su,et al.  Neural-network-based fuzzy model and its application to transient stability prediction in power systems , 1999, IEEE Trans. Syst. Man Cybern. Part C.

[8]  H. Carter Fuzzy Sets and Systems — Theory and Applications , 1982 .

[9]  D. Bamber The area above the ordinal dominance graph and the area below the receiver operating characteristic graph , 1975 .

[10]  Anurag Agarwal,et al.  Predicting Bankruptcy Resolution , 2002 .

[11]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[12]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[13]  M. Pepe An Interpretation for the ROC Curve and Inference Using GLM Procedures , 2000, Biometrics.

[14]  H. Frydman,et al.  Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress , 1985 .

[15]  W. Beaver Financial Ratios As Predictors Of Failure , 1966 .

[16]  Jonathan N. Crook,et al.  Credit Scoring and Its Applications , 2002, SIAM monographs on mathematical modeling and computation.

[17]  James A. Ohlson FINANCIAL RATIOS AND THE PROBABILISTIC PREDICTION OF BANKRUPTCY , 1980 .

[18]  Lawrence O. Hall,et al.  Decision making on creditworthiness, using a fuzzy connectionist model , 1992 .

[19]  W. Briggs Statistical Methods in the Atmospheric Sciences , 2007 .

[20]  E. Deakin Discriminant Analysis Of Predictors Of Business Failure , 1972 .

[21]  Masao Mukaidono,et al.  A fuzzy neural network for pattern classification and feature selection , 2002, Fuzzy Sets Syst..

[22]  David West,et al.  Neural network credit scoring models , 2000, Comput. Oper. Res..

[23]  E. H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Man Mach. Stud..

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

[25]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[26]  Michael Firth,et al.  A multivariate analysis of the determinants of Moody's bank financial strength ratings , 1999 .

[27]  Li-Chiu Chi,et al.  Credit Risk Prediction in Export Credit Sales: A Logistic Model Approach , 2002 .