Nonparametric Estimators for the Probability of Default

  • Jürgen FrankeEmail author
  • Wolfgang Karl Härdle
  • Christian Matthias Hafner
Part of the Universitext book series (UTX)


The estimation of the probability of default based on information on the individual customer or the company is an important part of credit screening, i.e., judging the credit standing. It is essential for the establishment of a rating or for measuring credit risk to estimate the probability that a company will end in financial difficulties within a given period, for example, one year. Also, here nonparametric applications prove to be flexible tools in estimating the desired default probability without arbitrary assumptions. In this chapter we will give a brief overview of the various approaches for non- and semiparametric estimates of conditional probabilities.


Credit Rating Default Probability Nonparametric Estimator Consumer Credit Maximum Likelihood Estima 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jürgen Franke
    • 1
    Email author
  • Wolfgang Karl Härdle
    • 2
    • 3
  • Christian Matthias Hafner
    • 4
  1. 1.FB MathematikTU KaiserslauternKaiserslauternGermany
  2. 2.Ladislaus von Bortkiewicz Chair of Statistics C.A.S.E. Centre for Applied Statistics and Economics School of Business and EconomicsHumboldt-Universität zu BerlinBerlinGermany
  3. 3.Graduate Institute of StatisticsNational Central UniversityJhongliTaiwan
  4. 4.Inst. StatistiqueUniversité Catholique de LouvainLeuven-la-NeuveBelgium

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