Fuzzy, Distributed, Instance Counting, and Default ARTMAP Neural Networks for Financial Diagnosis

This paper shows the potential of neural networks based on the Adaptive Resonance Theory as tools that generate warning signals when bankruptcy of a company is expected (bankruptcy prediction problem). Using that class of neural networks is still unexplored to date. We examined four of the most popular networks of the class — fuzzy, distributed, instance counting, and default ARTMAP. In order to illustrate their performance and to compare with other techniques, we used data, financial ratios, and experimental conditions identical to those published in previous studies. Our experiments show that two financial ratios provide highest discriminatory power of the model and ensure best prediction accuracy. We examined performance and validated results by exhaustive search of input variables, cross-validation, receiver operating characteristic analysis, and area under curve metric. We also did application-specific cost analysis. Our results show that distributed ARTMAP outperforms the other three models in general, but the fuzzy model is best performer for certain vigilance values and in the application-specific context. We also found that ARTMAP outperforms the most popular neural networks — multi-layer perceptrons and other statistical techniques applied to the same data.

[1]  Hsiao-Fan Wang,et al.  A Pruning Approach to Pattern Discovery , 2008, Int. J. Inf. Technol. Decis. Mak..

[2]  Zhengxin Chen,et al.  A Descriptive Framework for the Field of Data Mining and Knowledge Discovery , 2008, Int. J. Inf. Technol. Decis. Mak..

[3]  Ramesh Sharda,et al.  Performance comparison issues in neural network experiments for classification problems , 1993, [1993] Proceedings of the Twenty-sixth Hawaii International Conference on System Sciences.

[4]  Anatoli Nachev,et al.  Default ARTMAP Neural Networks for Financial Diagnosis , 2007, DMIN.

[5]  G. Kane.  Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol 1: Foundations, vol 2: Psychological and Biological Models , 1994 .

[6]  KEIJI TATSUMI,et al.  Improved Projection Hopfield Network for the Quadratic Assignment Problem , 2008, Int. J. Inf. Technol. Decis. Mak..

[7]  Stephen Grossberg,et al.  Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps , 1992, IEEE Trans. Neural Networks.

[8]  Pamela K. Coats,et al.  Recognizing Financial Distress Patterns Using a Neural Network Tool , 1993 .

[9]  Vadlamani Ravi,et al.  Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review , 2007, Eur. J. Oper. Res..

[10]  Stephen Grossberg,et al.  A massively parallel architecture for a self-organizing neural pattern recognition machine , 1988, Comput. Vis. Graph. Image Process..

[11]  Tom Fawcett,et al.  An introduction to ROC analysis , 2006, Pattern Recognit. Lett..

[12]  Stephen Grossberg,et al.  Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system , 1991, Neural Networks.

[13]  Gail A. Carpenter,et al.  Default ARTMAP 2 , 2007, 2007 International Joint Conference on Neural Networks.

[14]  Gail A. Carpenter,et al.  Distributed Learning, Recognition, and Prediction by ART and ARTMAP Neural Networks , 1997, Neural Networks.

[15]  Stephen Grossberg,et al.  Adaptive pattern classification and universal recoding: II. Feedback, expectation, olfaction, illusions , 1976, Biological Cybernetics.

[16]  Anna Hart,et al.  Using Neural Networks for Classification Tasks – Some Experiments on Datasets and Practical Advice , 1992 .

[17]  Carlos Serrano-Cinca,et al.  Self organizing neural networks for financial diagnosis , 1996, Decision Support Systems.

[18]  Stephen Grossberg,et al.  A What-and-Where fusion neural network for recognition and tracking of multiple radar emitters , 2001, Neural Networks.

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

[20]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[21]  Kyung-shik Shin,et al.  A genetic algorithm application in bankruptcy prediction modeling , 2002, Expert Syst. Appl..

[22]  Dong-Sik Jang,et al.  Fuzzy Art-Based Image Clustering Method for Content-Based Image Retrieval , 2007, Int. J. Inf. Technol. Decis. Mak..

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

[24]  JIANPING LI,et al.  Feature Selection via Least Squares Support Feature Machine , 2007, Int. J. Inf. Technol. Decis. Mak..

[25]  Kin Keung Lai,et al.  Neural Networks in Finance and Economics Forecasting , 2007, Int. J. Inf. Technol. Decis. Mak..

[26]  Andrew P. Bradley,et al.  The use of the area under the ROC curve in the evaluation of machine learning algorithms , 1997, Pattern Recognit..

[27]  James L. McClelland.  Explorations In Parallel Distributed Processing , 1988 .

[28]  John Mingers,et al.  Neural Networks, Decision Tree Induction and Discriminant Analysis: an Empirical Comparison , 1994 .

[29]  Koen Vanhoof,et al.  Bankruptcy prediction using a data envelopment analysis , 2004, Eur. J. Oper. Res..

[30]  Stephen Grossberg,et al.  ARTMAP: supervised real-time learning and classification of nonstationary data by a self-organizing neural network , 1991, [1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering.

[31]  Pamela K. Coats,et al.  A neural network for classifying the financial health of a firm , 1995 .

[32]  John J. Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities , 1999 .

[33]  Gail A. Carpenter,et al.  Distributed Activation, Search, and Learning by ART and ARTMAP Neural Networks , 1996 .

[34]  Ramesh Sharda,et al.  A neural network model for bankruptcy prediction , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[35]  Sancho Salcedo-Sanz,et al.  Genetic programming for the prediction of insolvency in non-life insurance companies , 2005, Comput. Oper. Res..

[36]  Anatoli Nachev,et al.  Forecasting with ARTMAP-IC Neural Networks - An Application Using Corporate Bankruptcy Data , 2008, ICEIS.

[37]  Gail A. Carpenter,et al.  ARTMAP-IC and medical diagnosis: Instance counting and inconsistent cases , 1998, Neural Networks.

[38]  Youngohc Yoon,et al.  A Comparison of Discriminant Analysis versus Artificial Neural Networks , 1993 .

[39]  Alfredo Vellido,et al.  Neural networks in business: a survey of applications (1992–1998) , 1999 .

[40]  E. F. Brigham,et al.  Financial Management: Theory and Practice , 1990 .