Modelling crypto markets by multi-agent reinforcement learning

By Johann Lussange, Stefano Vrizzi, Stefano Palminteri, Boris Gutkin

Published 2024-02-16

Everscope rating

1530.2

Relevance to quantitative trading

8 / 10

Implementation complexity

7 / 10

Reproducibility

4 / 5

About this paper

Methodology: Multi-agent reinforcement learning. Problem types: Time Series Forecasting, Market Making, Reinforcement Learning.

arXiv:2402.10803 · Code · Paper rankings

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