Abstract
The authors examine out-of-sample industry excess return predictability and portfolio allocation using forecasting combination methods of industry-level and aggregate accruals, book-to-market, earnings, investments, and gross profits. Out-of-sample combination forecasts generate significant industry return predictability. Substantial increases in Sharpe ratios and utility gains demonstrate that predictability is not driven primarily by higher risk. Real-time portfolio allocation strategies rotate into long positions in industries with high expected returns and short industries with low expected returns. Over the past thirty years, outof-sample combination forecasts of accounting variables have generated value-weighted industry portfolio payoffs five times greater than a buy-and-hold benchmark. The constructed portfolios consistently beat a buy-and-hold benchmark portfolio two-to-one while generating alphas that exceed 10%.
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