7 citations · 16 across the 9 of their papers we have counts for
3 papers · 1 filter
Order book regulatory impact on stock market quality: a multi-agent reinforcement learning perspective
Johann Lussange, Boris Gutkin
Recent technological developments have changed the fundamental ways stock markets function, bringing regulatory instances to assess the benefits of these developments. In parallel,…
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…
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…