---
title: The Expected Returns on Machine-Learning Strategies
url: https://www.ml-quant.com/papers/ssrn/4702406/
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 4702406
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4702406
featured: 2024-01-23
citations: 2
topic: Asset Pricing & Factors
---


# The Expected Returns on Machine-Learning Strategies

Despite high turnover rates and the selection of hard-to-arbitrage stocks, machine learning strategies can predict profitable returns that common risk factors cannot explain, according to a study.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4702406
- Identifier: SSRN 4702406
- Released: 2023-11-18
- First featured: Quant Letter No. 34 (2024-01-23): https://www.ml-quant.com/issues/2024-01-23/
- Citations (Semantic Scholar): 2
- Published in: not yet
- Topic: Asset Pricing & Factors

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