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The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas

Fabian Hollstein (), Marcel Prokopczuk () and Chardin Wese Simen ()
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Fabian Hollstein: School of Economics and Management, Leibniz University Hannover, 30167 Hannover, Germany
Chardin Wese Simen: International Capital Market Association Centre, Henley Business School, University of Reading, Reading RG6 6BA, United Kingdom

Management Science, 2020, vol. 66, issue 6, 2474-2494

Abstract: When using high-frequency data, the conditional capital asset pricing model (CAPM) can explain asset-pricing anomalies. Using conditional betas based on daily data, the model works reasonably well for a recent sample period. However, it fails to explain the size anomaly as well as three out of six of the anomaly component excess returns. Using high-frequency betas, the conditional CAPM is able to explain the size, value, and momentum anomalies. We further show that high-frequency betas provide more accurate predictions of future betas than those based on daily data. This result holds for both the time-series and the cross-sectional dimensions.

Keywords: beta estimation; conditional CAPM; high-frequency data (search for similar items in EconPapers)
Date: 2020
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Handle: RePEc:inm:ormnsc:v:66:y:2020:i:6:p:2474-2494