37 Pages Posted: 26 May 2015 Last revised: 5 Aug 2015
Date Written: July 22, 2015
Revisiting the issue of return predictability, we show there is substantial predictive power in combining forecasting variables. We apply correlation screening to combine twenty variables that have been proposed in the return predictability literature, and demonstrate forecasting power at a six-month horizon. We illustrate the economic significance of return predictability through a walk-forward simulation, which takes positions in SPY proportional to the model forecast equity risk premium. The simulated strategy yields annual returns more than twice that of the buy-and-hold strategy, with a Sharpe ratio four times as large. To eliminate look-ahead bias, we perform additional simulations including variables only as they are discovered in the literature. Results show similar annual returns and Sharpe ratios. While a market-timing strategy outperforms the market, it is difficult to implement.
Keywords: equity premium, forecasting, predictability, correlation screening, market timing, asset returns, tactical asset allocation
Suggested Citation: Suggested Citation
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