RT Journal Article SR Electronic T1 The Cross Section of Commodity Returns: A Nonparametric Approach JF The Journal of Financial Data Science FD Institutional Investor Journals SP 86 OP 103 DO 10.3905/jfds.2020.1.034 VO 2 IS 3 A1 Clemens Struck A1 Enoch Cheng YR 2020 UL https://pm-research.com/content/2/3/86.abstract AB To what extent are financial market returns predictable? Standard approaches to asset pricing make strong parametric assumptions that undermine their return-predicting ability. The authors employ tree-based methods to overcome these limitations and attempt to approximate an upper bound for the predictability of returns in commodities futures markets. Out of sample, they find that up to 3.74% of 1-month returns are predictable—more than a 10-fold increase from standard approaches. The findings hint at the importance multiway interactions and nonlinearities acquire in the data; they imply that new factors should be tested on their ability to add explanatory power to an ensemble of existing factors.TOPICS: Futures and forward contracts, commoditiesKey Findings• Standard approaches to asset pricing make strong parametric assumptions that undermine their return-predicting ability.• The authors employ tree-based methods to overcome these limitations and estimate the predictability of returns in commodities futures markets.• Out of sample, they find that up to 3.74% of 1-month returns are predictable—more than a 10-fold increase from standard approaches.