This paper proposes a structural approach to long-horizon asset allocation. In particular, the investor draws inferences about asset returns from a vector autoregression (VAR) with economic restrictions on the intercept, slope, and covariance matrix implied by the long-run risk model of Bansal...

This paper shows that investments based on deep learning signals extract profitability from difficult-to-arbitrage stocks and during high limits-to-arbitrage market states. In particular, excluding microcaps, distressed stocks, or episodes of high market volatility considerably attenuates...

The distance between short- and long-run moving averages of prices (MAD) predicts future equity returns in the cross-section. Annualized value-weighted alphas from the accompanying hedge portfolios are around 9%, and the predictability goes beyond momentum, 52-week highs, profitability, and...