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The Continuum-GMM Estimation: Theory and Application

Author

Listed:
  • Rachidi Kotchoni

    (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Marine Carrasco

Abstract

By avoiding discretization, the Generalized Method of Moment based on a Continuum of moment conditions (CGMM) permits to effciently use the information content of a continuum moment restrictions. When the moment restrictions are deduced from a characteristic function, the CGMM has the potential to achieve the maximum likelihood efficiency. This chapter reviews the theory underlying the CGMM procedure, discusses the properties of the CGMM estimator and presents numerical algorithms for its implementation. An empirical application is proposed where a Variance Gamma model is fitted to the monthly increments of the USD/GBP exchange rates. We find that the variance forecasts inferred from the Variance Gamma model are of poor quality. A model that specifies the variance as a dependent process should deliver better forecasts. JEL Classification: C00, C13, C15

Suggested Citation

  • Rachidi Kotchoni & Marine Carrasco, 2019. "The Continuum-GMM Estimation: Theory and Application," Post-Print hal-02435760, HAL.
  • Handle: RePEc:hal:journl:hal-02435760
    Note: View the original document on HAL open archive server: https://hal.science/hal-02435760
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    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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