Credit risk evaluation in power market with random forest

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

Volumn , Issue , 2007, Pages 3737-3742

  Mori, Hiroyuki ^a,b   Umezawa, Yasushi ^a,b  

^a IEEE

^b MEIJI UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPETITIVE INTELLIGENCE; DATA MINING; OPTIMIZATION; PROFITABILITY; RANDOM PROCESSES; RISK MANAGEMENT;

CREDIT RISK EVALUATION; POWER MARKET; RANDOM FOREST; RISK INDEX;

RISK ASSESSMENT;

EID: 40949121374     PISSN: 1062922X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSMC.2007.4413777     Document Type: Conference Paper

References (24)

1. E. I. Altman, "Financial Ratio, Discriminant Analysis and the Prediction of Corporate Bankruptcy," Journal of Finance, Vol. 23, No. 4, Sep. 1968, pp. 589-609.
2. W. Beaver, "Financial Ratios as Predictors of Failure," Journal of Accounting Research, Vol. 4, 1966, pp. 71-111.
3. D. Martin, "Early Warning of Bank Failure: A Logit Regression Approach," Journal of Banking and Finance, Vol. 1, No. 3, Nov. 1977, pp. 249-276.
4. R. Kaplan and G. Urwitz, "Statistical Models of Bond Ratings," Journal of Business, Vol. 52, No. 2, 1979, pp. 231-261.
5. J. Ohlson, "Financial Ratio and the Probabilistic Prediction of Bankruptcy," Journal of Accounting Research, Vol. 18, No. 1, 1980, pp. 109-131.
6. A. F. Atiya, "Bankruptcy Prediction for Credit Risk Using Neural Networks: A Survey and New Results," IEEE Trans. on Neural Networks, Vol. 12, No. 4, Jul. 2001, pp. 929-935.
7. th International Conference on Machine Learning and Cybernetics, Guangzhou, Vol. 7, Aug. 2005, pp. 4038-4043.
8. th International Conference on Machine Learning and Cybernetics, Dalian, Aug. 2006, pp. 3110-3114.
9. S. L. Pang, Y. M. Wang and Y. H. Bai, "Credit Scoring Model Based on Neural Network," Proc. of the First International Conference on Machine Learning and Cybernetics, Beijing, Vol. 4, Nov. 2002, pp. 1742-1746.
10. T. K. Sung, M. Chang and G. Lee, "Dynamics of Modeling in Data Mining," Journal of Management Information Systems, Vol. 16, No. 1, 1999, pp. 63-85.
11. Y. Shirata, "Financial Ratios as Predictors of Bankruptcy in Japan: An Empirical Research," Proc. of The Second Asian Pacific Interdisciplinary Research in Accounting Conference, Aug. 1998, pp. 437-445.
12. R. A. Jarrow, D. Land and S. M. Turnbull, "A Markov Model for the Term Structure of Credit Risk Spread," Review of Financial Studies, Vol. 10, No. 2, 1997, pp. 481-523.
13. D. Duffie and K. Singleton, "Modeling Term Structures of Defaultable Bonds," Review of Financial Studies, Vol. 12, No. 4, 1999, pp. 687-720.
14. R. Bender and A. Benner, "Calculating Ordinal Regression Models in SAS and Splus," Biometrical Journal, Vol. 42, No. 6, Jun. 2000, pp. 677-699.
15. L. Breiman, "Random Forests," Machine Learning, Springer Netherlands, Vol. 45, No. 1, Oct. 2001, pp. 5-32.
16. P. O. Gislason, J. A. Benediktsson and J. R. Sveinsson, "Random Forests for land cover classification," Partern Recognition Letters, Vol. 27, No. 4, Mar. 2006, pp. 294-300.
17. C. Chen, A. Liaw and L. Breiman, "Using Random Forest to Learn Imbalanced Data," Technical Report 666, Statistics Department, UC Berkeley, 2004.
18. L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone, "Classification and Regression Trees," Wadsworth International Group, Belmont, California, USA 1984.
19. H. Mori and N. Kosemura, "Optimal regression tree based rule discovery for short-term load forecasting," Proc. of 2001 IEEE PES Winter Meeting Columbus, OH, USA, Vol. 2, Feb. 2001, pp. 421-426.
20. H. Mori, N. Kosemura, K. Ishiguro, and T. Kondo, "Data Mining for Short-term Load Forecasting," Proc. of 2002 IEEE PES Winter Meeting, Vol. 1, New York, NY, USA, Jan. 2002, pp. 623-624.
21. EDINET (http://info.edinet.go.jp/EdiHtml/main.htm).
22. Rating and Investment Information.Inc (http://www.r-i.co.jp/jpn/).
23. C. Bluhm, L. Overbeck and C. Wagner, "An Introduction to Credit Risk Modeling," Chapman & Hall, 2002.
24. JEPX (http://www.jepx.org/English/index_e.html).