The memory of beta

[thumbnail of BetaLM_complete.pdf]
Preview
Text - Accepted Version
· Available under License Creative Commons Attribution Non-commercial No Derivatives.
· Please see our End User Agreement before downloading.
| Preview

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

Becker, J., Hollstein, F., Prokopczuk, M. and Sibbertsen, P. (2021) The memory of beta. Journal of Banking & Finance, 124. 106026. ISSN 0378-4266 doi: 10.1016/j.jbankfin.2020.106026

Abstract/Summary

Researchers and practitioners employ a variety of time-series processes to forecast betas, either using short-memory models or implicitly imposing infinite memory. We find that both approaches are inadequate: betas show consistent long-memory properties. For the vast majority of stocks, we reject both the short-memory and difference-stationary (random walk) alternatives. A pure long-memory model reliably provides superior beta forecasts compared to all alternatives. Accounting for long memory in beta also pays off economically for portfolio formation. We widely document the robustness of these results.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/95508
Identification Number/DOI 10.1016/j.jbankfin.2020.106026
Refereed Yes
Divisions Henley Business School > Finance and Accounting
Publisher Elsevier
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

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

Search Google Scholar