Estimating Beta

Full text not archived in this repository.

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Hollstein, F. and Prokopczuk, M. (2016) Estimating Beta. Journal of Financial and Quantitative Analysis, 51 (4). pp. 1437-1466. ISSN 1756-6916 doi: 10.1017/S0022109016000508

Abstract/Summary

We conduct a comprehensive comparison of market beta estimation techniques. We study the performance of several historical, time-series model, and option-implied estimators for estimating realized market beta. Thereby, we find the hybrid methodology of Buss and Vilkov to consistently outperform all other approaches. In addition, all other approaches, including fully implied and dynamic conditional beta, based on generalized autoregressive conditional heteroskedasticity (GARCH) models, are dominated by a simple beta estimate based on historical (co-)variances and an approach based on the Kalman filter. Our conclusions remain unchanged after performing several robustness checks.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/39066
Identification Number/DOI 10.1017/S0022109016000508
Refereed Yes
Divisions Henley Business School > Finance and Accounting
Publisher Cambridge University Press
Download/View statistics View download statistics for this item

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar