SSRNML & AI Methods
Does It Actually Run? An Execution-Based Reproducibility Study of Published Machine-Learning Finance Research
Testing 459 quantitative-finance machine-learning papers' released code, the study finds that execution success rates fall steeply due to environment and dependency issues, not link rot alone.
Featured in No. 138 on 6 Nov 2026 · 2 days after release
- Released
- 4 Nov 2026
- First featured
- No. 138 · 6 Nov 2026
- Published in
- Not yet, as far as Semantic Scholar knows
- Fanfare
- 4 of 5
- Identifier
- SSRN 7677538
- Authors
- Akram Khan
Citations and venue from Semantic Scholar (ODC-BY), refreshed weekly. Summary: Quant Letter (CC BY 4.0).