Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations

no code implementations • 13 Oct 2022 • Nelson Vadori, Leo Ardon, Sumitra Ganesh, Thomas Spooner, Selim Amrouni, Jared Vann, Mengda Xu, Zeyu Zheng, Tucker Balch, Manuela Veloso

We study a game between liquidity provider and liquidity taker agents interacting in an over-the-counter market, for which the typical example is foreign exchange.

Multi-agent Reinforcement Learning reinforcement-learning +1

CTMSTOU driven markets: simulated environment for regime-awareness in trading policies

no code implementations • 2 Feb 2022 • Selim Amrouni, Aymeric Moulin, Tucker Balch

Market regimes is a popular topic in quantitative finance even though there is little consensus on the details of how they should be defined.

ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial Markets

1 code implementation • 27 Oct 2021 • Selim Amrouni, Aymeric Moulin, Jared Vann, Svitlana Vyetrenko, Tucker Balch, Manuela Veloso

We introduce a general technique to wrap a DEMAS simulator into the Gym framework.

OpenAI Gym Reinforcement Learning (RL)

DocuBot : Generating financial reports using natural language interactions

no code implementations • 2 Oct 2020 • Vineeth Ravi, Selim Amrouni, Andrea Stefanucci, Armineh Nourbakhsh, Prashant Reddy, Manuela Veloso

Digital reports are often created based on tedious manual analysis as well as visualization of the underlying trends and characteristics of data.