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Taurus

A cryptocurrency trading platform using deep reinforcement learning.

Structure

Taurus is based on several microservices in a monorepo:

• The deep learning model that turns price data into trade decisions (/navigator)
• The trading system that executes and tracks trades (/trader)
• The data collection service that feeds data into the ML model (/collector)
• The web application for user control and monitoring (/web)

The microservices communicate via gRPC (https://grpc.io). The current version only supports being run on a single server, so no key exchange occurs between APIs.

Prerequisites

This application requires Python 3.7+, protoc/protobuf, gRPC, Docker and Docker Compose to build.

Usage

TBD

Under Development

• RPC/messaging interfaces
• Data collection logic
• Trading logic
• Machine learning model & training
• Web interface
• Logging

Credits

The reinforcement learning model for this project is based on a graduate paper from Zhengyao Jiang, Dixing Xu, and Jinjun Liang of Xi'an Jiaotong-Liverpool University in Suzhou, China. https://arxiv.org/abs/1706.10059

This project uses the CCXT library (https://github.com/ccxt/ccxt) to interact with exchanges for data collection and trading.