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).