How to Estimate Beta?

Fabian Hollstein, Marcel Prokopczuk () and Chardin Wese Simen

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

Abstract: Researchers and practitioners face many choices when estimating an asset's sensitivities toward risk factors, i.e., betas. We study the effect of different data sampling frequencies, forecast adjustments, and model combinations for beta estimation. Using the entire U.S. stock universe and a sample period of more than 50 years, we find that a historical estimator based on daily return data with an exponential weighting scheme as well as a shrinkage toward the industry average yield the best predictions for future beta. Adjustments for asynchronous trading, macroeconomic conditions, or regression-based combinations, on the other hand, typically yield very high prediction errors.

Keywords: beta estimation; forecast combinations; forecast adjustments (search for similar items in EconPapers)
JEL-codes: G11 G12 G17 (search for similar items in EconPapers)
Pages: 46 pages
Date: 2017-11
New Economics Papers: this item is included in nep-ecm and nep-fmk
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