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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).

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