mbt_gym is a module which provides a suite of gym environments for training reinforcement learning (RL) agents to solve model-based high-frequency trading problems such as market-making and optimal execution. The module is set up in an extensible way to allow the combination of different aspects of different models. It supports highly efficient implementations of vectorized environments to allow faster training of RL agents.

It includes gym environments for popular analytically tractable market making models, as well as more complex models that prove difficult to solve analytically.

The associated paper can be found at https://arxiv.org/abs/2209.07823.