---
title: Deep reinforcement learning for arbitrage in decentralized exchanges
url: https://www.ml-quant.com/papers/ssrn/4666504/
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 4666504
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4666504
featured: 2023-12-20
citations: 1
topic: Trading, Microstructure & Execution
---


# Deep reinforcement learning for arbitrage in decentralized exchanges

The study explores trading performances under arbitrage conditions in decentralized exchanges, using a simulation model and deep reinforcement learning to determine optimal arbitrage strategies for eight cryptocurrency pairs.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4666504
- Identifier: SSRN 4666504
- Released: 2023-04-30
- First featured: Quant Letter No. 30 (2023-12-20): https://www.ml-quant.com/issues/2023-12-20/
- Citations (Semantic Scholar): 1
- Published in: not yet
- Topic: Trading, Microstructure & Execution

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