응용통계연구 (The Korean Journal of Applied Statistics)

  • 제25권5호
  • /
  • Pages.803-811
  • /
  • 2012
  • /
  • 1225-066X(pISSN)
  • /
  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
권호 표지
DOI QR코드

DOI QR Code

Estimating Discriminatory Power with Non-normality and a Small Number of Defaults

  • Hong, C.S. (Department of Statistics, Sungkyunkwan University) ;
  • Kim, H.J. (Research Institute of Applied Statistics, Sungkyunkwan University) ;
  • Lee, J.L. (Department of Statistics, Sungkyunkwan University)
  • 투고 : 2012.09.04
  • 심사 : 2012.10.08
  • 발행 : 2012.10.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

For credit evaluation models, we extend the study of discriminatory power based on AUC obtained from a ROC curve when the number of defaults is small and distribution functions of the defaults and non-defaults are normal distributions. Since distribution functions do not satisfy normality in real world, the distribution functions of the defaults and non-defaults are assumed as normal mixture distributions based on results that the normal mixture could be better fitted than other distribution estimation methods for non-normal data. By using several AUC statistics, the discriminatory power under such a circumstance is explored and compared with those of normal distributions.

키워드

참고문헌

  1. Berry, M. J. A. and Linoff, G. (2009). Data Mining Techniques: For Marketing sales, and Customer Support, Morgan Kaufmann Publishers.
  2. Hanley, A. and McNeil, B. (1982). The meaning and use of the area under a receiver operating characteristics curve, Diagnostic Radiology, 143, 29-36.
  3. Hong, C. S. and Choi, J. S. (2009). Optimal threshold from ROC and CAP curves, The Korean Journal of Applied Statistics, 11, 911-921.
  4. Hong, C. S., Joo, J. S. and Choi, J. S. (2010). Optimal thresholds from mixture distributions, The Korean Journal of Applied Statistics, 16, 13-28.
  5. Hong, C. S. and Lee, W. Y. (2011). ROC curve fitting with normal mixtures, The Korean Journal of Applied Statistics, 10, 269-278.
  6. Hong, C. S., Lin, M. H. and Hong, S. W. (2011). ROC function estimation, The Korean Journal of Applied Statistics, 8, 987-994.
  7. Koh, H. C. (1992). The Sensitivity of Optimal cutoff to misclassification costs of type I and type II errors in the going concern prediction context, Journal of Business Finance and Accounting, 19, 187-197. https://doi.org/10.1111/j.1468-5957.1992.tb00618.x
  8. Sobehart, J. R. and Keenan, S. C. (2001). Measuring default accurately, Credit Risk Special Report, 14, 31-33.
  9. Stein, R. M. (2005). The relationship between default prediction and lending profits: Integrating ROC analysis and loan pricing, Journal of Banking and Finance, 29, 1213-1236. https://doi.org/10.1016/j.jbankfin.2004.04.008
  10. Tasche, D. (2006). Validation of internal rating systems and PD estimates, The Analytics of Risk Model Validation, 28, 169-196.
  11. Tasche, D. (2009). Estimating discriminatory power and PD curves when the number of defaults is small, Working Paper, Lloyds Banking Group.