We propose a hybrid approach for estimating beta that shrinks rolling window estimates toward firm-specific priors motivated by economic theory. Our method yields superior forecasts of beta that have important practical implications. First, unlike standard rolling window betas, hybrid betas carry a significant price of risk in the cross-section even after controlling for characteristics. Second, the hybrid approach offers statistically and economically significant out-of-sample benefits for investors who use factor models to construct optimal portfolios. We show that the hybrid estimator outperforms existing estimators because shrinkage toward a fundamentals-based prior is effective in reducing measurement noise in extreme beta estimates.

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JEL Portfolio Choice; Investment Decisions (jel G11), Asset Pricing (jel G12), Information and Market Efficiency; Event Studies (jel G14), Financial Forecasting (jel G17)
Persistent URL dx.doi.org/10.1093/rfs/hhv131, hdl.handle.net/1765/93472
Journal The Review of Financial Studies
Note A previous draft of this paper circulated under the title “Efficient Estimation of Firm-Specific Betas and its Benefits for Asset Pricing Tests and Portfolio Choice.”
Cosemans, M.M.J.E, Frehen, R, Schotman, P.C, & Bauer, R. (2016). Estimating Security Betas Using Prior Information Based on Firm Fundamentals. In The Review of Financial Studies (Vol. 29, pp. 1072–1112). doi:10.1093/rfs/hhv131