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Stock price formation: useful insights from a multi-agent reinforcement learning model
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 implement so-called noise traders to sub-optimally emulate price formation processes.
Trading and Market Microstructure Pricing of Securities
Stock market microstructure inference via multi-agent reinforcement learning
Quantitative finance has had a long tradition of a bottom-up approach to complex systems inference via multi-agent systems (MAS).
Multi-agent Reinforcement Learning
reinforcement-learning
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