Forecasting Stock Returns Under Economic Constraints
Brandeis University - Department of Economics
Allan G. Timmermann
University of California, San Diego (UCSD) - Department of Economics; Centre for Economic Policy Research (CEPR)
Rossen I. Valkanov
University of California, San Diego (UCSD) - Rady School of Management
December 7, 2012
We propose a new approach to imposing economic constraints on 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 and improve both statistical and economic measures of out-of-sample forecast performance. The Sharpe ratio constraint, in particular, results in considerable economic gains.
Number of Pages in PDF File: 57
Keywords: Economic constraints, Sharpe ratio, Equity premium predictions, Bayesian analysis
JEL Classification: C11, C22, G11, G12
Date posted: December 9, 2012
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