7 citations · 10 across the 3 of their papers we have counts for
3 papers
Stock market microstructure inference via multi-agent reinforcement learning
J. Lussange, I. Lazarevich, S. Bourgeois-Gironde +2
Quantitative finance has had a long tradition of a bottom-up approach to complex systems inference via multi-agent systems (MAS). These statistical tools are based on modelling age…
Mesoscale impact of trader psychology on stock markets: a multi-agent AI approach
J. Lussange, S. Palminteri, S. Bourgeois-Gironde +1
Recent advances in the fields of machine learning and neurofinance have yielded new exciting research perspectives in practical inference of behavioural economy in financial market…
Stock price formation: useful insights from a multi-agent reinforcement learning model
J. Lussange, S. Bourgeois-Gironde, S. Palminteri +1
In the past, financial stock markets have been studied with previous generations of multi-agent systems (MAS) that relied on zero-intelligence agents, and often the necessity to im…