---
title: Single-stage Portfolio Optimization with Automated Machine Learning for M6
url: https://www.ml-quant.com/papers/ssrn/4836123/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4836123
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4836123
featured: 2024-05-22
citations: 7
topic: Portfolio & Allocation
---


# 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.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4836123
- Identifier: SSRN 4836123
- Released: 2024-05-21
- First featured: Quant Letter No. 50 (2024-05-22): https://www.ml-quant.com/issues/2024-05-22/
- Citations (Semantic Scholar): 7
- Published in: not yet
- Topic: Portfolio & Allocation

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