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Non-Parametric Specification Tests For Conditional Duration Models

Author

Listed:
  • Marcelo Fernandes

    (European University Institute)

  • Joachim Grammig

    (University of Frankfurt)

Abstract

This paper deals with the estimation and testing of conditional duration models by looking at the density and hazard rate functions. More precisely, we focus on the distance between the parametric density (or hazard rate) function implied by the duration process and its non-parametric estimate. Asymptotic justification is derived using the functional delta method for fixed and gamma kernels, whereas finite sample properties are investigated through Monte Carlo simulations. Finally, we show the practical usefulness of such testing procedures by carrying out an empirical assessment of whether autoregressive conditional duration models are appropriate tools for modelling price durations of stocks traded at the New York Stock Exchange

Suggested Citation

  • Marcelo Fernandes & Joachim Grammig, 2000. "Non-Parametric Specification Tests For Conditional Duration Models," Computing in Economics and Finance 2000 40, Society for Computational Economics.
  • Handle: RePEc:sce:scecf0:40
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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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