Modelos paramétricos y no paramétricos en problemas de "credit scoring"

  1. Puertas Medina, Rosa
  2. Bonilla Musoles, María
  3. Olmeda Martos, José Ignacio
Revista:
Revista española de financiación y contabilidad

ISSN: 0210-2412

Año de publicación: 2003

Número: 118

Páginas: 833-869

Tipo: Artículo

DOI: 10.1080/02102412.2003.10779502 DIALNET GOOGLE SCHOLAR

Otras publicaciones en: Revista española de financiación y contabilidad

Referencias bibliográficas

  • ALTMAN, E. [1998]: «The Importance and Subtlety of Credit Rating Migration», Journal of Banking and Finance, vol. 22: 1231-1247.
  • ALTMAN, E.; MARCO, G., y VARETTO, F. [1994]: «Corporate Distress Diagnosis: Comparisons Using Linear Discriminant Analysis and Neural Networks», Journal of Banking and Finance, vol. 18: 505-529.
  • BARDOS, M. [1998]: «Detecting the Risk of Company Failure at the Banque de France», Journal of Banking and Finance, vol. 22: 1405-1419.
  • BREIMAN, L.; FRIEDMAN, J.; OLSHEN, R., y STONE, C. [1984]: Classification and Regresion Trees, Wadsworth & Brooks.
  • CLEVELAND, W. S. [1979]: «Robust Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting», Journal of the American Statistical Association, vol. 83: pp. 596-610.
  • CRAVEN, P., y WAHBA, G. [1979]: «Smoothing Noisy Data with Spline Functions. Estimating the Correct Degree of Smoothing by the Method of Generalized Cross - Validation», Numerische Mathematik, vol. 31: 317-403.
  • EFRON, B. [1975]: «The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis», Journal of the American Statistical Association, vol. 70: 892-898.
  • FISHER, R. A. [1936]: «The Use of Multiple Measurements in Taxonomic Problems», Annals of Eugenics, vol. 7: 179-188.
  • FOGLIA, A.; LAVÍOLA, S., y MARULLO REEDTZ, P. [1998]: «Multiple Banking Relations and the Fragility of Corporate Borrowers», Journal of Banking and Finance, vol. 22: 1441-1456.
  • FRIEDMAN, J. H. [1977]: «A Recursive Partitioning Decisión Rule for Nonparametric Classification», IEEE Transactions on Computers: 404-509.
  • -[1991]: «Multivariate Adaptive Regression Splines (with discussion)», The Annals of Statistics, vol. 19: pp. 1-141.
  • FRYDMAN, H.; ALTMAN, E., y KAO, D. [1985]: «Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress», The Journal of Finance: 269-291.
  • GNANADESIKAN, R., y KETTENRING, J. R. [1989]: «Discriminant Analysis and Clustering», Statistical Science: 34-69.
  • GRACIA-DÍEZ, M., y SERRANO, G. [1992]: «Algunos aspectos sobre el análisis empírico de credit scoring», Estadística Española, vol. 34: 261-283.
  • HANSEN, J.; MCDONALD, J., y STICE, J. [1992]: «Artificial Intelligence and Generalized Qualitative-Response Models: An Empirical Test on Two Audit DecisionMaking Domains», Decision Sciences, vol. 23: 708-723.
  • KATTAN, M.; ADAMS, D., y PARKS, M. [1993]: «A Comparison of Machine Learning with Human Judgement», Journal of Management Information Systems, vol. 9: 37-57.
  • KUMAR, A., y OLMEDA, I. [1999]: «A Study of Composite or Hybrid Classifiers for Knowledge Discovery», INFORMS Journal of Computing, vol. 11: 267-277.
  • LIU, P.; SEYYED, F., y SMITH, S. [1999]: «The Independent Impact of Credit Rating Changes-The Case of Moody's Rating Refinement of Yield Premiums», Journal of Business Finance & Accounting, 337-465.
  • MACHAUER, A., y WEBER, M. [1998]: «Bank Behavior Based on Internal Credit Ratings of Borrowers», Journal of Banking and Finance, vol. 22: 1355-1383.
  • MARAIS, M.L; PATELL, J., y WOLFSON, M. [1984]: «The Experimental Design of Classification Models: An Application of Recursive Partitioning and Bootstrapping to Commercial Bank Loan Classifications», Journal of Accounting Research: 87-114.
  • MICHALSKI, R. [1983]: «A Theory and Methodology of Inductive Learning», en R. S. MICHALSKI, J. G. CARBONELL y T. M. MITCHELL (eds.), Machine Learning: An Artificial Intelligence Approach, Tioga Publishing Company, Palo Alto, CA.
  • OLMEDA, I., y BARBE-ROMERO, S. [1993]: Redes neuronales artificiales: Fundamentos y aplicaciones, Servicio de Publicaciones de la Universidad de Alcalá de Henares, Madrid.
  • OLMEDA, I., y FERNÁNDEZ, E. [1997]: «Hybrid Classifiers for Financial Multicriteria Decision Making: The Case of Bankruptcy Prediction», Computational Economics: 1-19.
  • PRESS, J., y WILSON, S. [1978]: «Choosing Between Logistic Regression and Discriminant Analysis», Journal of the American Statistical Association, vol. 73: 699-705.
  • QUINLAN, J. [1983]: «Learning Effiecient Classification Procedures and their Application to Chess End Games», en R. S. MICHALSKI, J. G. CARBONELL y T. M. MICHELL (eds.), Machine Learning: An Artificial Intelligence Approach, Tioga Publishing Company, Palo Alto, CA.
  • QUINLAN, J. [1987]: «Symplifying Decision Trees», International Journal of Machine Studies, vol. 27: pp. 221-234.
  • -[1993]: C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers, San Mateo, California.
  • ROBBINS, H., y MONRO, S. [1951]: «A Stochastic Approximation Method», The Annals of Mathematical Statistics, vol. 22: 400-407.
  • STONE, M. [1974]: «Cross-validatory Choice and Assessment of Statistical Predictions», Journal of the Royal Statistical Society, vol. 36: 11-144.
  • TAM, K., y KIANG, M. [1992]: «Managerial Applications of Neural Networks: The Case of Bank Failure Predictions», Management Science, vol. 38: 926-947.
  • VARETTO, F. [1998]: «Genetic Algorithms Applications in the Analysis of Insolvency Risk», Journal of Banking & Finance, vol. 22: 1421-1439.
  • WAGNER, G.; REICHERT, A., y CHO, C. [1983]: «Conceptual Issues in Credit Scoring Models», Credit World, vol. 71 (May/June) 22-25 (part 1) (July/August) 2228, 41(part 2).
  • YATCHEW, A. [1998]: «Nonparametric Regression Techniques in Economics», Journal of Economic Literature, vol. 16: 669-721.
  • ZMIEWSKI, M., y FOSTER, B. [1996]: «Credit-Scoring Speeds Small Business Loan Processing», The Journal of Lending & Credit Risk Management, 42-56.
Fuente de los datos: Dialnet