We study the out-of-sample predictability of the returns of pan-European harmonized mutual funds that apply hedge fund-like investment strategies (“Alternative UCITS”). Given these funds’ higher liquidity, investors could exploit relevant information much easier than for hedge funds, and use it for asset allocation and risk management. We use a set of 13 variables, fundamental as well as technical, and apply single predictor models, combination forecasts, and multivariate regression models. Our results show that in terms of out-of-sample R 2 , predictive models do not lead to more accurate forecasts than historic average returns. Nonetheless, forming portfolios based on predicted returns can yield substantial economic gains to investors, especially during times of market crises. Combination approaches and multivariate models can reduce estimation uncertainty stemming from time-varying predictive performance of single predictor models, leading to economic gains across different market environments.