---
title: Portfolio Optimization with RL
url: https://www.ml-quant.com/papers/ssrn/5276183/
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 5276183
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5276183
featured: 2025-06-04
citations: unknown
topic: Portfolio & Allocation
---


# Portfolio Optimization with RL

The authors suggest a new approach to portfolio optimization that incorporates turnover cost and diversification into a convex optimization framework, using reinforcement learning-based control.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5276183
- Identifier: SSRN 5276183
- Released: 2025-05-30
- First featured: Quant Letter No. 100 (2025-06-04): https://www.ml-quant.com/issues/2025-06-04/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation

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