Semiparametric diffusion estimation and application to a stock market index

Wolfgang Härdle, Torsten Kleinow, Alexander Korostelev, Camille Logeay, Eckhard Platen

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


The analysis of diffusion processes in financial models is crucially dependent on the form of the drift and diffusion coefficient functions. A new model for a stock market index process is proposed in which the index is decomposed into an average growth process and an ergodic diffusion. The ergodic diffusion part of the model is not directly observable. A methodology is developed for estimating and testing the coefficient functions of this unobserved diffusion process. The estimation is based on the observations of the index process and uses semiparametric and non-parametric techniques. The testing is performed via the wild bootstrap resampling technique. The method is illustrated on SP 500 index data.

Original languageEnglish
Pages (from-to)81-92
Number of pages12
JournalQuantitative Finance
Issue number1
Publication statusPublished - Feb 2008


  • Bootstrap
  • Continuous-time financial models
  • Diffusion
  • Identification
  • Kernel smoothing
  • Semiparametric methods


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