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Autor
Popławska Małgorzata (Szkoła Główna Handlowa w Warszawie)
Tytuł
Credit Risk Analysis Using Failure Time Models
Źródło
Roczniki Kolegium Analiz Ekonomicznych / Szkoła Główna Handlowa, 2007, nr 17, s. 203-224, rys., tab., bibliogr 14 poz.
Tytuł własny numeru
Discovering patterns in economic data
Słowa kluczowe
Instytucje kredytowe, Ryzyko kredytowe, Zarządzanie kredytem, Uwarunkowania mikroekonomiczne
Credit institution, Credit risk, Credit management, Microeconomic conditions
Uwagi
summ.
Abstrakt
Credit granting institutions have to face the risk that some amount of money that has been lent will not be repaid. Therefore banks and other lending institutions are concerned with the issue of measuring the risk of each credit default, which is needed to accept or reject credit applications. The aim of this paper is to present an approach for classifying applicants, based on duration data - survival analysis. Including an extra dimension - time - in the analysis allows the lending institution to take into account the profitability of a loan. Moreover, failure models give an opportunity to include in the model time-varying covariates - regressors that change in time of the repayment. They make it possible to use in the estimation data about the credits that are still being repayed - censored durations. This method is also a useful tool to predict the influence of the particular characteristics on the probability and the expected time of exit to different kinds of states - complete repayment on time, default but also e.g. an early repayment. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
Biblioteka Główna Uniwersytetu Ekonomicznego we Wrocławiu
Bibliografia
Pokaż
  1. Banasik J., Crook J. N., Thomas L. C. [1999], Not if but when will borrowers default, The Journal of the Operational Research Society, Vol. 50, No. 12., pp. 1185-1190.
  2. Cameron A. C., Trivedi P. K. [2005], Microeconometrics. Methods and Applications, Cambridge University Press.
  3. Cox D. R. [1972], Partial likelihood, Biometrika, Vol. 62, No. 2., pp. 269-276.
  4. Cox D. R. [1972], Regression models and life-tables, Journal of the Royal Statistical Society, Series B, Vol. 34, No. 2, pp. 187-220.
  5. Gray R. [1996], Hazard rate regression using ordinary nonparametric regression smoothers, Journal of Computational and Graphical Statistics, Vol. 5, No. 2, pp. 190-207.
  6. Kalbfleisch J.D. and Prentice R.L. [1980], The Statistical Analysis of Failure Time Data, Wiley.
  7. Kiefer N. M. [1988], Economic duration data and hazardfunctions, Journal of Economic Literature, Vol. 26, No. 2., pp. 646-679.
  8. Klein J.P. Moeschberger M.L., [1997], Survival Analysis: Techniques for Censored and Truncated Data, Springer.
  9. Narain B. [1992], Survival analysis and the credit granting decision, In: Thomas LC, Crook JN and Edelman DB (eds). Credit Scoring and Credit Control, Oxford University Press, pp. 109-121.
  10. Rosenberg E., Gleit A. [1994], Quantitative Methods in Credit Management: A Survey, The Journal of the Operations Research, Vol. 42, No. 4., pp. 589-613.
  11. Stepanova M., Thomas L. C. [2001], PHAB scores:proportional hazards analysis behavioural scores, The Journal of the Operational Research Society, Vol. 52, No. 2., pp. 1007-1016.
  12. Stepanova M., Thomas L. C. [2002], Survival analysis methods for personal loan data, The Journal of the Operational Research Society, Vol. 50, No. 2.,pp. 277-289.
  13. http://ftp.ics.uci.edu/pub/machine-leaming-databases/statlog/german
  14. http://www.r-project.org
Cytowane przez
Pokaż
ISSN
1232-4671
Język
eng
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