The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas
Fabian Hollstein (),
Marcel Prokopczuk () and
Chardin Wese Simen ()
Additional contact information
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
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)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:66:y:2020:i:6:p:2474-2494
Access Statistics for this article
More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Matthew Walls ().