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Consistent estimation of drift parameter in diffusion model with misspecified volatility function

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  • Jeong, Minsoo

Abstract

The drift parameter of a diffusion model can be consistently estimated by the MLE based on the Euler approximation even when the volatility function is misspecified. Contrastingly, all other commonly used estimators such as the exact MLE, the MLE by Aït-Sahalia, the MLE by Kessler and the MLE based on the Milstein approximation generally yield inconsistent drift estimates if the volatility function is misspecified.

Suggested Citation

  • Jeong, Minsoo, 2022. "Consistent estimation of drift parameter in diffusion model with misspecified volatility function," Economics Letters, Elsevier, vol. 211(C).
  • Handle: RePEc:eee:ecolet:v:211:y:2022:i:c:s0165176521004742
    DOI: 10.1016/j.econlet.2021.110237
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    References listed on IDEAS

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    1. Papanicolaou, Alex & Giesecke, Kay, 2016. "Variation-based tests for volatility misspecification," Journal of Econometrics, Elsevier, vol. 191(1), pages 217-230.
    2. Choi, Hwan-sik & Jeong, Minsoo & Park, Joon Y., 2014. "An asymptotic analysis of likelihood-based diffusion model selection using high frequency data," Journal of Econometrics, Elsevier, vol. 178(P3), pages 539-557.
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    More about this item

    Keywords

    Diffusion model; Drift and diffusion functions; Misspecification; Consistency; Maximum likelihood estimation;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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