@article {Lallemand70, author = {Justin Lallemand and Jack Strauss}, title = {Can We Count on Accounting Fundamentals for Industry Portfolio Allocation?}, volume = {42}, number = {4}, pages = {70--87}, year = {2016}, doi = {10.3905/jpm.2016.42.4.070}, publisher = {Institutional Investor Journals Umbrella}, 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\%.TOPICS: Portfolio theory, derivatives}, issn = {0095-4918}, URL = {https://jpm.pm-research.com/content/42/4/70}, eprint = {https://jpm.pm-research.com/content/42/4/70.full.pdf}, journal = {The Journal of Portfolio Management} }