JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Adjusted ROC and CAP Curves
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Adjusted ROC and CAP Curves
Hong, Chong-Sun; Kim, Ji-Hun; Choi, Jin-Soo;
  PDF(new window)
 Abstract
Among others, ROC and CAP curves are used to explore the discriminatory power between the defaults and non-defaults, based on the distribution of the probability of default in credit rating works. ROC and CAP curves are plotted in terms of various ratios of the probability of default. Each point on ROC and CAP curves is calculated according to cutting points (scores) for classifying between defaults and non-defaults. In this paper, adjusted ROC and CAP curves are proposed by using functions of ratios of the probability of default. It is possible to recognize the score corresponding to a point oil these adjusted curves, and we can identify the best score to show the optimal discriminatory power. Moreover, we discuss the relationships between the best score obtained from the adjusted ROC and CAP curves and the score corresponding to Kolmogorov - Smirnov statistic to test the homogeneous distribution functions of the defaults and non-defaults.
 Keywords
Credit rating;cross-product ratio;cutting point;discriminatory power;odds ratio;probability of default;score;
 Language
Korean
 Cited by
1.
AROC 곡선과 최적분류점,홍종선;이희정;

응용통계연구, 2011. vol.24. 1, pp.185-191 crossref(new window)
1.
AROC Curve and Optimal Threshold, Korean Journal of Applied Statistics, 2011, 24, 1, 185  crossref(new windwow)
2.
Test for Theory of Portfolio Diversification, Korean Journal of Applied Statistics, 2011, 24, 1, 1  crossref(new windwow)
 References
1.
송문섭, 박창순, 이정진 (2003). , 자유아카데미, 경기

2.
이군희 (2006). 바젤 II 협약 기반 신용평점의 계량전 점검에 대한 고찰, 예금보험공사 <금융리스크리뷰>, 3, 70-95

3.
임종건 (2005). 신용평가시스템에 대한 적합성 검증, 금융감독원, <리스크리뷰>, 2005

4.
홍종선, 이창혁, 김지훈 (2008). Validation comparison of credit rating models for categorized financial data, <한국통계학회논문집>, 15, 615-631

5.
Fawcett, T. (2004). ROC Graphs: Notes and Practical Considerations for Researchers, Kluwer Academic Publishers, Netherlands

6.
Fawcett, T. (2005). An introduction to ROC analysis, Pattern Recognition Letters, 27, 861-874 crossref(new window)

7.
Hosmer, D. W. and Lemeshow, S. (2000). Applied Logistic Regression, 2nd ed, John Wiely & Sons, New York

8.
Joseph, M. P. (2005). A PD validation framework for basel II internal ratings based systems, Credit Scoring and Credit Control IV

9.
Sonego, P., Kocsor, A. and Pongor, S. (2008). ROC analysis: Applications to the classification ofbiological sequences and 3D structures, Briefings in Bioinformatics, 9, 198-209 crossref(new window)

10.
Tasche, D. (2006). Validation of internal rating systems and PD estimates, arXiv:physics/0606071, 1