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Variation and efficiency of high-frequency betas

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Listed:
  • Zhang, Congshan
  • Li, Jia
  • Todorov, Viktor
  • Tauchen, George

Abstract

This paper studies the efficient estimation of betas from high-frequency return data on a fixed time interval. Under an assumption of equal diffusive and jump betas, we derive the semiparametric efficiency bound for estimating the common beta and develop an adaptive estimator that attains the efficiency bound. We further propose a Hausman type test for deciding whether the common beta assumption is true from the high-frequency data. In our empirical analysis we provide examples of stocks and time periods for which a common market beta assumption appears true and ones for which this is not the case. We further quantify empirically the gains from the efficient common beta estimation developed in the paper.

Suggested Citation

  • Zhang, Congshan & Li, Jia & Todorov, Viktor & Tauchen, George, 2022. "Variation and efficiency of high-frequency betas," Journal of Econometrics, Elsevier, vol. 228(1), pages 156-175.
    • Handle: RePEc:eee:econom:v:228:y:2022:i:1:p:156-175
    DOI: 10.1016/j.jeconom.2020.05.022
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    References listed on IDEAS

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    More about this item

    Keywords

    Adaptive estimation; Beta; High frequency data; Jump; Semiparametric efficiency; Volatility;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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