SSRNML & AI Methods
Memorisation or Alpha? Detecting Look-Ahead Contamination in Cross-Sectional Equity Signals
Testing whether a large language model ranks stocks by forecasting or memory, the study finds a significant information-coefficient gap of 0.185 inside versus outside its training window, suggesting substantial look-ahead contamination.
Featured in No. 132 on 25 Sep 2026 · 3 days after release
- Released
- 22 Sep 2026
- First featured
- No. 132 · 25 Sep 2026
- Published in
- Not yet, as far as Semantic Scholar knows
- Fanfare
- 3 of 5
- Identifier
- SSRN 7490302
- Authors
- Bach Nguyen
Citations and venue from Semantic Scholar (ODC-BY), refreshed weekly. Summary: Quant Letter (CC BY 4.0).