Before revision:  Analysing the agents' performances on the test data, we argue that the agents are able to create a dynamic representation of the underlying environment highlighting the occasional regularities present in the data and exploiting them to create long-term profitable trading strategies  .
After revision:  Analysing the agents' performances on the test data, we argue that the agents are able to create a dynamic representation of the underlying environment highlighting the occasional regularities present in the data and exploiting them to create long-term profitable trading strategies . Indeed, agents learn trading strategies able to produce stable positive returns in spite of the highly stochastic and non-stationary environment .