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SSRNML & AI Methods

Deep Learning from Commodity Futures Term-Structure Surfaces: Empirical Evidence and a Convolutional Theory of Carry

Encoding commodity futures curves as time-maturity surfaces and applying convolutional networks extracts carry information that predicts returns beyond standard factors and improves the mean-variance frontier.

Featured in No. 135 on 16 Oct 2026 · 4 days after release

Released
12 Oct 2026
First featured
No. 135 · 16 Oct 2026
Published in
Not yet, as far as Semantic Scholar knows
Fanfare
3 of 5
Identifier
SSRN 7600983
Authors
Yuecheng Jia et al.

Citations and venue from Semantic Scholar (ODC-BY), refreshed weekly. Summary: Quant Letter (CC BY 4.0).

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