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Variation-based tests for volatility misspecification

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  • Papanicolaou, Alex
  • Giesecke, Kay

Abstract

We provide a simple and easy to use goodness-of-fit test for the misspecification of the volatility function in diffusion models. The test uses power variations constructed as functionals of discretely observed diffusion processes. We introduce an orthogonality condition which stabilizes the limit law in the presence of parameter estimation and avoids the necessity for a bootstrap procedure that reduces performance and leads to complications associated with the structure of the diffusion process. The test has good finite sample performance as we demonstrate in numerical simulations.

Suggested Citation

  • Papanicolaou, Alex & Giesecke, Kay, 2016. "Variation-based tests for volatility misspecification," Journal of Econometrics, Elsevier, vol. 191(1), pages 217-230.
    • Handle: RePEc:eee:econom:v:191:y:2016:i:1:p:217-230
    DOI: 10.1016/j.jeconom.2015.10.008
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    References listed on IDEAS

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    Cited by:

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    2. Jeong, Minsoo, 2022. "Consistent estimation of drift parameter in diffusion model with misspecified volatility function," Economics Letters, Elsevier, vol. 211(C).
    3. Guangying Liu & Meiyao Liu & Jinguan Lin, 2022. "Testing the volatility jumps based on the high frequency data," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 669-694, September.

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    More about this item

    Keywords

    Volatility testing; Diffusion processes; Goodness-of-fit tests;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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