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The Memory of Beta Factors

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

Hannover Economic Papers (HEP) from Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät

Abstract: Researchers and practitioners employ a variety of time-series processes to forecast betas, using either short-memory models or implicitly imposing infinite memory. We find that both approaches are inadequate: beta factors 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. Finally, we document the relation of firm characteristics with the forecast error differentials that result from inadequately imposing short-memory or random walk instead of long-memory processes.

Keywords: Long memory; beta; persistence; forecasting; predictability (search for similar items in EconPapers)
JEL-codes: C58 G15 G12 G11 (search for similar items in EconPapers)
Pages: 53 pages
Date: 2019-09
New Economics Papers: this item is included in nep-ecm, nep-fmk, nep-for and nep-ore
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