Daily Data is Bad for Beta: Opacity and Frequency-Dependent Betas
研究发现股票的市场风险（贝塔）随收益频率变化，高低频贝塔差异可导致定价错误，不透明性解释了这一现象，表明高频贝塔估计面临挑战。
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.