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Sampling interval and estimated betas: Implications for the presence of transitory components in stock prices

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  • Perron, Pierre
  • Chun, Sungju
  • Vodounou, Cosme

Abstract

We provide a theoretical framework to explain the empirical finding that the estimated betas are sensitive to the sampling interval even when using continuously compounded returns. We suppose that stock prices have both permanent and transitory components. The discrete time representation of the beta depends on the sampling interval and two components labeled “permanent and transitory betas”. We show that if no transitory component is present in stock prices then no sampling interval effect occurs. However, the presence of a transitory component implies that the beta is an increasing (decreasing) function of the sampling interval for more (less) risky assets. In our framework, assets are labeled risky if their “permanent beta” is greater than their “transitory beta” and vice versa for less risky assets. Simulations show that our theoretical results provide good approximations for the estimated betas in small samples. We provide empirical evidence about the presence of negative serial correlation and mean reversion in the returns of the portfolios considered. We discuss why our model is better able to provide an explanation for this sampling interval effect than other models in the literature.

Suggested Citation

  • Perron, Pierre & Chun, Sungju & Vodounou, Cosme, 2013. "Sampling interval and estimated betas: Implications for the presence of transitory components in stock prices," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 42-62.
    • Handle: RePEc:eee:empfin:v:20:y:2013:i:c:p:42-62
    DOI: 10.1016/j.jempfin.2012.10.002
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    3. Conlon, Thomas & Cotter, John & Gençay, Ramazan, 2018. "Long-run wavelet-based correlation for financial time series," European Journal of Operational Research, Elsevier, vol. 271(2), pages 676-696.

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    More about this item

    Keywords

    Mean reversion; CAPM; Stock returns; Transitory components; Firm size; Continuous time models;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: 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
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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