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Daily Data is Bad for Beta: Opacity and Frequency-Dependent Betas

Author

Listed:
  • Thomas Gilbert
  • Christopher Hrdlicka
  • Jonathan Kalodimos
  • Stephan Siegel

Abstract

A stock’s market exposure, beta, varies across return frequencies. Sorting stocks on the difference between low- and high-frequency betas (Δβ) yields large systematic mispricings relative to the CAPM at high frequencies, but significantly smaller mispricings at low frequencies. We provide a risk-based explanation for this frequency dependence by introducing uncertainty about the effect of systematic news on firm value (opacity) into a frictionless model. We document a robust relationship between the frequency dependence of betas and proxies for opacity. Our findings suggest that opacity poses significant challenges to using betas estimated from high-frequency returns. While the CAPM may be an appropriate asset pricing model at low frequencies, additional factors, e.g., based on opacity, are necessary at high frequencies.

Suggested Citation

  • Thomas Gilbert & Christopher Hrdlicka & Jonathan Kalodimos & Stephan Siegel, 2014. "Daily Data is Bad for Beta: Opacity and Frequency-Dependent Betas," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 4(1), pages 78-117.
    • Handle: RePEc:oup:rasset:v:4:y:2014:i:1:p:78-117.
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    File URL: http://hdl.handle.net/10.1093/rapstu/rau001
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    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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