유전자 알고리즘을 활용한 부실예측모형의 구축

A GA-based Rule Extraction for Bankruptcy Prediction Modeling

  • 발행 : 2001.12.01

초록

기업부실예측은 과거로부터 많은 연구가 이루어진 분야로, 주로 통계기법에 의한 분류예측문제로 다루어져 왔다. 최근에는 인공신경망, 의사결정나무 등 비선형성을 반영할 수 있는 인공지능 기법을 적용한 연구가 많이 수행되고 있다. 본 연구에서는 최적화에 주로 활용하는 인공지능 기법인 유전자 알고리즘을 규칙추출을 통한 기업부실예측 모형의 개발에 적용하고, 활용가능성을 검증하였다.

Prediction of corporate failure using past financial data is well-documented topic. Early studies of bankruptcy prediction used statistical techniques such as multiple discriminant analysis, logit and probit. Recently, however, numerous studies have demonstrated that artificial intelligence such as neural networks (NNs) can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. Although numerous theoretical and experimental studies reported the usefulness or neural networks in classification studies, there exists a major drawback in building and using the model. That is, the user can not readily comprehend the final rules that the neural network models acquire. We propose a genetic algorithms (GAs) approach in this study and illustrate how GAs can be applied to corporate failure prediction modeling. An advantage of GAs approach offers is that it is capable of extracting rules that are easy to understand for users like expert systems. The preliminary results show that rule extraction approach using GAs for bankruptcy prediction modeling is promising.

키워드

참고문헌

  1. The Journal of Finance v.23 Financial ratios,discriminant analysis and the prediction of Corporate bankruptcy Altman,E.
  2. A complete guide to predicting avoiding and dealing with bankruptcy,John Wiley,New York Corporate financial distress
  3. Intelligent Systems in Accounting Finance and Management v.6 Predicting the outcome following bankruptcy filling : A three-state classification using neural networks Barniv,R.Agarwal,A.;Leach,R.
  4. Genetic Algorithms and Investment Strategies,John Wiley & sons Bauer,R.J.
  5. Intelligent Systems in Accounting Finance and Management v.6 Neural nets or the logit model? A Comparison of each model's ability to predict commercial bank failures Bell,T.,
  6. Expert Systems with Applications v.9 Effectiveness of neural networks types for prediction of business failure Boritz,;Kennedy,D,
  7. Intelligent Systems in Accounting Finance and Management v.2 A Comparative Analysis of Inductive Learning Algorithm Chung,H.;Tam,K.
  8. In Deboeck,G.J(Eds),Trading on the Edge John wiley,NewYork Genetic algorithms for financial modeling Colin,A.M,
  9. Handbook of Genetic Algorithms,Van Nostrand Reinhold,NewYork Davis,L.,
  10. Intelligent Systems in Accounting Finance and Management v.6 A comparison of the relative costs of financial distress models : Arificial neural networks ,logit and Multivariate discriminant analysis Etheride,H.;Sriram,R.
  11. Intelligent Systems in Accounting, Finance and Management v.6 A comparison of the relative costs of financial distress models : Artificial neural networks,logit and multivariate discriminant analysis Etheridge,H.;Sriram,R.
  12. Information and Management v.24 no.3 Forecasting with neural networks:An application using bankruptcy data Fletcher,D.;Goss,E.
  13. Genetic Algorithms in Search,Optimization and Machine Leaning Addison-Wesley Goldberg,D.E.,
  14. Journal of the Korean Operations Research and Management science Society v.22 no.3 The hybrid systems for credit rarting Han,I.JO,H.;Shin,K.S.
  15. Adaptation in Natural and Artificial Systems, Ann Arbor, Holland,J.H.
  16. Expert Systems With Applications, v.13 no.2 Bankruptcy prediction using case-based reasoning neural networks,and discriminant analysis Jo.H.,Han,I.And Lee,H.,
  17. In Medsker,L.R.(Eds),Hybrid Intelligent Systems,Kluwer Academic Publishers Adaptive control of an exothermic chemical reaction system using fuzzy logic and genetic algorithms Karr,C.,
  18. Genetic algorithms for bankruptcy prediction, Search Space Research Report no.01-95 Kingdom,J.;Feldman,K.
  19. Genetic Programming, The MIT Press Koza,J.
  20. Proceedings of the 3rd International Conference on Artificial Intelligence Applications on Wall Street Genetic algorithms for predicting individual stock performance Mahfoud,S.;Mani,G
  21. Proceedings of the IEEE International Conference on Neural Network v.2 A neural networks model for bankruptcy prediction Odom,M.;Sharda,R.
  22. Journal of Accounting Research, v.18 no.1 Financial ratios and the probabilistic prediction of bankruptcy Ohlson,J.
  23. Complex Systems v.4 A genetic learning algorithm for the analysis of complex data Packard,N.
  24. Proceedings of the 3rd International Conference on Artificial Intelligence Applications on Wall Steet Experiments with optimal stock screens Rutan,E,
  25. Decision Sciences v.23 Nerual networks:A new tool for predicting thrift failures Salchenberger,L.,Cinar,E;Lash,N.
  26. Proceedings of Korea Management Science Institute Conference Bankruptcy Prediction Modeling Using Multiple Neural Networks Models Shin,K.S.;Han,I.(a)
  27. Proceedings of Second Asia Pacific Decision Sciences Institute(DSI)Conference,Taipei Using Genetic Algorithm to Support Case-Based Reasoning : Application to Corporate Bond Rating Integration shin,k.s.;Han,I.(b)
  28. Proceedings of Ⅳ International Meeting on Artificial Intelligence and Emerging Technologies in Accounting Finance and Taxation,Spain Corporate Credit Rating System Using Bankruptcy Probability Matrix Skin,K.S.,Shin,T.S,;Han,I.
  29. In Schaffer,J.D(Eds).Proceedings of 3rd Int I conference of Genetic Algorithms,San Maeto,Morgan Kaufmann Uniform Crossover in genetic algorithms Syswerda,G.
  30. Management Science v.38 no.7 Managerial applications of neural networks : the case of bank failure predictions Tam,K.;Kiang,M.
  31. In Coonatilake,S.and Treleaven,P.(Eds).Intelligent Systems for FInance and Business John Wiley Credit evaluation using a genetic algorithm Walker,R.,Haasdijk,E.;Gerrets,M.
  32. Decision Support Systems v.11 no.5 Bankruptcy prediction using neural networks Wilson,R.;Sharda,R.