Forecasting stock returns under economic constraints

Davide Pettenuzzo (), Allan Timmermann and Rossen Valkanov

Journal of Financial Economics, 2014, vol. 114, issue 3, 517-553

Abstract: We propose a new approach to imposing economic constraints on time series forecasts of the equity premium. Economic constraints are used to modify the posterior distribution of the parameters of the predictive return regression in a way that better allows the model to learn from the data. We consider two types of constraints: non-negative equity premia and bounds on the conditional Sharpe ratio, the latter of which incorporates time-varying volatility in the predictive regression framework. Empirically, we find that economic constraints systematically reduce uncertainty about model parameters, reduce the risk of selecting a poor forecasting model, and improve both statistical and economic measures of out-of-sample forecast performance.

Keywords: Economic constraints; Sharpe ratio; Equity premium predictions (search for similar items in EconPapers)
JEL-codes: C11 C22 G11 G12 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (160)

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Related works:
Working Paper: Forecasting Stock Returns under Economic Constraints (2013)
Working Paper: Forecasting Stock Returns under Economic Constraints (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jfinec:v:114:y:2014:i:3:p:517-553

DOI: 10.1016/j.jfineco.2014.07.015

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