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Nonparametric estimation of jump diffusion models

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  • Park, Joon Y.
  • Wang, Bin

Abstract

This paper develops the asymptotics for nonparametric kernel estimators of local time, drift and volatilities, and Lévy measure in jump diffusion models. Our asymptotics are developed in a very general set-up, allowing the sample span to increase as the sampling interval decreases, and without assuming stationarity. For drift and volatilities, we analyze both local constant and local linear estimators. We consider not only estimators for instantaneous conditional second moment, but also threshold estimators to disentangle diffusive and jump volatilities. The optimal bandwidths are provided for all these estimators.

Suggested Citation

  • Park, Joon Y. & Wang, Bin, 2021. "Nonparametric estimation of jump diffusion models," Journal of Econometrics, Elsevier, vol. 222(1), pages 688-715.
    • Handle: RePEc:eee:econom:v:222:y:2021:i:1:p:688-715
    DOI: 10.1016/j.jeconom.2020.07.020
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    Cited by:

    1. Wang, Bin & Zheng, Xu, 2022. "Testing for the presence of jump components in jump diffusion models," Journal of Econometrics, Elsevier, vol. 230(2), pages 483-509.

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    More about this item

    Keywords

    Nonparametric estimation; Jump diffusion; Asymptotics; Local time; Drift; Diffusive and jump volatility; Lévy measure; Threshold estimation; Optimal bandwidth;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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