The Conditional CAPM Revisited: Evidence from High-Frequency Betas

Management Science, Forthcoming

52 Pages Posted: 25 Mar 2019 Last revised: 29 Jul 2019

See all articles by Fabian Hollstein

Fabian Hollstein

Leibniz Universität Hannover - Faculty of Economics and Management

Marcel Prokopczuk

Leibniz Universität Hannover - Faculty of Economics and Management; University of Reading - ICMA Centre

Chardin Wese Simen

University of Reading - ICMA Centre

Date Written: February 14, 2019

Abstract

When using high-frequency data, the conditional 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 3 out of 6 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

JEL Classification: G11, G12, C58

Suggested Citation

Hollstein, Fabian and Prokopczuk, Marcel and Wese Simen, Chardin, The Conditional CAPM Revisited: Evidence from High-Frequency Betas (February 14, 2019). Management Science, Forthcoming. Available at SSRN: https://ssrn.com/abstract=3334524

Fabian Hollstein (Contact Author)

Leibniz Universität Hannover - Faculty of Economics and Management ( email )

Koenigsworther Platz 1
Hannover, 30167
Germany

Marcel Prokopczuk

Leibniz Universität Hannover - Faculty of Economics and Management ( email )

Koenigsworther Platz 1
Hannover, 30167
Germany

University of Reading - ICMA Centre ( email )

Whiteknights Park
P.O. Box 242
Reading RG6 6BA
United Kingdom

Chardin Wese Simen

University of Reading - ICMA Centre ( email )

Henley Business School
University of Reading
Reading, RG6 6BA
United Kingdom

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