FlexTrader

A multi-task deep reinforcement learning model for trading futures contracts using the Interactive Brokers API and TensorFlow

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Install / Use

/learn @spawnaga/FlexTrader

About this skill

Quality Score

0/100

README

FlexTrader

Overview

This project is a multi-task trading algorithm that utilizes various reinforcement learning techniques such as DQN, DDQN, Actor-Critic, and Policy Gradient to trade on the futures market. The algorithm is implemented using the Interactive Brokers API and TensorFlow.

Requirements

Python 3.x TensorFlow IB API (ib_insync) pandas numpy matplotlib

Usage

Clone the repository to your local machine Install the required packages by running pip install -r requirements.txt Run the train.py file to train the algorithm on the specified task (DQN, DDQN, Actor-Critic, or Policy Gradient) Use the Trader class to execute trades on the market using the trained model

Note

This project is intended for educational and research purposes only. The results and performance of the algorithm may not be indicative of actual trading performance.

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