PT  - JOURNAL ARTICLE
AU  - Clemens Struck
AU  - Enoch Cheng
TI  - The Cross Section of Commodity Returns: <em>A Nonparametric Approach</em>
AID  - 10.3905/jfds.2020.1.034
DP  - 2020 Jul 31
TA  - The Journal of Financial Data Science
PG  - 86--103
VI  - 2
IP  - 3
4099  - https://pm-research.com/content/2/3/86.short
4100  - https://pm-research.com/content/2/3/86.full
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.