A Fresh Look at Return Predictability Using a More Efficient Estimator

Review of Asset Pricing Studies, Forthcoming

59 Pages Posted: 7 Feb 2015 Last revised: 11 Oct 2018

Date Written: September 21, 2018

Abstract

I assess time-series return predictability using a weighted least squares estimator that is around 25% more efficient than ordinary least squares (OLS) because it incorporates time-varying volatility into its point estimates. Traditional predictors, such as the dividend yield, perform better in- and out-of-sample when using my estimator, indicating the insignificant OLS estimates may be false negatives driven by a lack of power. Some newer predictors, such as the variance risk premium and the president's political party, are insignificant when using my estimator, indicating the significant OLS estimates may be false positives driven by a few periods with high expected volatility.

Keywords: Return predictability, weighted least squares, volatility, out-of-sample predictability, variance risk premium, presidential puzzle

JEL Classification: G10, G11, G12

Suggested Citation

Johnson, Travis L., A Fresh Look at Return Predictability Using a More Efficient Estimator (September 21, 2018). Review of Asset Pricing Studies, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2561112 or http://dx.doi.org/10.2139/ssrn.2561112

Travis L. Johnson (Contact Author)

The University of Texas at Austin ( email )

2110 Speedway Stop B6600
Austin, TX Texas 78712
United States
6178995325 (Phone)

HOME PAGE: http://travislakejohnson.com

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