A case-based approach using inductive indexing for corporate bond rating

Abstract Case-based reasoning (CBR) is a problem solving technique by re-using past cases and experiences to find a solution to problems. The central tasks involved in CBR methods are to identify the current problem situation, find a past case similar to the new one, use that case to suggest a solution to the current problem, evaluate the proposed solution, and update the system by learning from this experience. In doing tasks, one of the critical issues in building a useful CBR system lies in the application of general domain knowledge to the indexing of cases, which may support the retrieval of relevant cases to the problem. This paper investigates the effectiveness of inductive learning approach to case indexing process for business classification tasks. We suggest this approach as a unifying framework to combine general domain knowledge and case-specific knowledge. Our particular interest involves optimal or near optimal decision trees that represent an optimal combination level between the two knowledge types. The proposed approach is demonstrated by applications to corporate bond rating.

[1]  John Moody,et al.  Architecture Selection Strategies for Neural Networks: Application to Corporate Bond Rating Predicti , 1995, NIPS 1995.

[2]  Christopher K. Riesbeck,et al.  Inside Case-Based Reasoning , 1989 .

[3]  Alvin J. Surkan,et al.  Neural networks for bond rating improved by multiple hidden layers , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[4]  A. Refenes.  Neural Networks in the Capital Markets , 1994 .

[5]  J. Horrigan.  DETERMINATION OF LONG-TERM CREDIT STANDING WITH FINANCIAL RATIOS , 1966 .

[6]  I. Kononenko,et al.  INDUCTION OF DECISION TREES USING RELIEFF , 1995 .

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

[8]  James V. Hansen,et al.  Case-Based Reasoning: Application Techniques for Decision Support , 1995 .

[9]  Ingoo Han,et al.  Integrating statistical and inductive learning methods for knowledge acquisition , 1990 .

[10]  Yuh Foong David Law,et al.  An integrated case-based reasoning approach for intelligent help desk fault management , 1997 .

[11]  Ingoo Han,et al.  Ordinal Pairwise Partitioning (OPP) Approach to Neural Networks Training in Bond rating , 1997, Intell. Syst. Account. Finance Manag..

[12]  Tarun K. Sen,et al.  Predicting Bond Ratings Using Neural Networks: A Comparison with Logistic Regression , 1997, Intell. Syst. Account. Finance Manag..

[13]  Stephanie M. Bryant,et al.  A case-based reasoning approach to bankruptcy prediction modeling , 1996 .

[14]  Ingoo Han,et al.  Ordinal Pairwise Partitioning (OPP) Approach to Neural Networks Training in Bond rating , 1997, Intell. Syst. Account. Finance Manag..

[15]  Janet L. Kolodner,et al.  Improving Human Decision Making through Case-Based Decision Aiding , 1991, AI Mag..

[16]  Ingoo Han,et al.  Case-based reasoning supported by genetic algorithms for corporate bond rating , 1999 .

[17]  G. E. Pinches,et al.  A MULTIVARIATE ANALYSIS OF INDUSTRIAL BOND RATINGS , 1973 .

[18]  E. Mine Cinar,et al.  Neural Networks: A New Tool for Predicting Thrift Failures , 1992 .

[19]  Stephen Slade,et al.  Case-Based Reasoning: A Research Paradigm , 1991, AI Mag..

[20]  Michael J. Shaw,et al.  Inductive learning for risk classification , 1990, IEEE Expert.

[21]  Bonnie W. Morris.  SCAN: A Case-Based Reasoning Model for Generating Information System Control Recommendations , 1994 .

[22]  Efraim Turban,et al.  Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real-World Performance , 1992 .

[23]  Uma G. Gupta,et al.  Applying Case-Based Reasoning to the Accounting Domain , 1994 .

[24]  David Patterson,et al.  A case-based reasoning approach to the selection of comparable evidence for retail rent determination , 1997 .

[25]  Louis H. Ederington.  CLASSIFICATION MODELS AND BOND RATINGS , 1985 .

[26]  David L. Olson,et al.  Knowledge acquisition tool for case-based reasoning s ystems , 1995 .

[27]  Soumitra Dutta,et al.  Bond rating: A non-conservative application of neural networks , 1988 .

[28]  Janet L. Kolodner,et al.  Case-Based Reasoning , 1989, IJCAI 1989.

[29]  Melody Y. Kiang,et al.  Generalized case-based reasoning system for portfolio management , 1993 .

[30]  Richard T. Redmond,et al.  Expert systems for bond rating: a comparative analysis of statistical, rule‐based and neural network systems , 1993 .

[31]  Ingoo Han,et al.  Using Induction Techniques to Support Case-Based Reasoning , 1997 .