Trading Brain is a framework example for implementing and testing trading strategies. It is composed of mainly three components communicating through APIs:

• Brain
• Memory
• Agent

This library can be used to test agents with the Trading-Gym.

Architecture

Installation

Install packages in requirements.txt file

Roll out your own Agent

To create your own agent, it must inherit from the Agent base class which can be found at 'tbrn/base/agent.py'. It consists of three basic methods that need to be overridden in order to implement your own logic:

• act: returns the action chosen by the agent.
• observe: returns a real value (can be the loss in the case of a KerasAgent for instance). This method is where the learning logic of the agent is located. Can be blank for dummy agents.
• end: any logic at the end of an episode.

Examples

One example can be found in examples/

• Simple keras agent (examples/keras_example.py)
• Dueling Double DQN tensorflow agent (examples/tf_example.py)

Read more about this example at our Trading Gym

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