Single-stage Portfolio Optimization with Automated Machine Learning for M6
The M6 forecasting competition paper introduces a data-driven approach that directly optimizes portfolio weights, achieving a 9.5 global rate of return and an information ratio of 5.045.
Featured in No. 50 on 22 May 2024 · 1 day after release · 7 citations today
- Released
- 21 May 2024
- First featured
- No. 50 · 22 May 2024
- Citations (Semantic Scholar)
- 7
- Influential citations
- 0
- Published in
- Not yet, as far as Semantic Scholar knows
- Shares when featured
- 3
- Identifier
- SSRN 4836123
Citations and venue from Semantic Scholar (ODC-BY), refreshed weekly. Summary: Quant Letter (CC BY 4.0).