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Estimating beta: Forecast adjustments and the impact of stock characteristics for a broad cross-section

Fabian Hollstein, Marcel Prokopczuk () and Chardin Wese Simen

Journal of Financial Markets, 2019, vol. 44, issue C, 91-118

Abstract: Researchers and practitioners face many choices when estimating an asset's sensitivities toward risk factors, i.e., betas. 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 simple shrinkage adjustments 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 and fail to create market-neutral anomaly portfolios. Finally, we document a robust link between stock characteristics and beta predictability.

Keywords: Beta estimation; Forecast combinations; Forecast adjustments (search for similar items in EconPapers)
JEL-codes: G11 G12 G17 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1016/j.finmar.2019.03.001

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