The memory of beta

Janis Becker, Fabian Hollstein, Marcel Prokopczuk () and Philipp Sibbertsen

Journal of Banking & Finance, 2021, vol. 124, issue C

Abstract: 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.

Keywords: Long memory; Beta; Persistence; Forecasting; Predictability (search for similar items in EconPapers)
JEL-codes: C58 G11 G12 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:124:y:2021:i:c:s0378426620302879

DOI: 10.1016/j.jbankfin.2020.106026

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