TensorTrade is built around modular components that together make up a trading strategy. Trading strategies combine reinforcement learning agents with composable trading logic in the form of a gym environment. A trading environment is made up of a set of modular components that can be mixed and matched to create highly diverse trading and investment strategies.

Just like electrical components, the purpose of TensorTrade components is to be able to mix and match them as necessary.