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

B-Tier
Journal: Review of Asset Pricing Studies
Year: 2014
Volume: 4
Issue: 1
Pages: 78-117

Authors (4)

Thomas Gilbert (not in RePEc) Christopher Hrdlicka (not in RePEc) Jonathan Kalodimos (not in RePEc) Stephan Siegel (University of Washington)

Score contribution per author:

0.503 = (α=2.01 / 4 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:oup:rasset:v:4:y:2014:i:1:p:78-117.
Journal Field
Finance
Author Count
4
Added to Database
2026-01-29