Introduction

TradeMaster is a first-of-its kind, best-in-class open-source platform for quantitative trading (QT) empowered by reinforcement learning (RL), which covers the full pipeline for the design, implementation, evaluation and deployment of RL-based algorithms.

Architecture

TradeMaster is composed of 6 key modules: 1) multi-modality market data of different financial assets at multiple granularity; 2) whole data preprocessing pipeline; 3) a series of high-fidelity data-driven market simulators for mainstream QT tasks; 4) efficient implementations of over 13 novel RL-based trading algorithms; 5) systematic evaluation toolkits with 6 axes and 17 measures; 6) different interfaces for interdisciplinary users.

Model Zoo

DeepScalper based on Pytorch (Shuo Sun et al, CIKM 22)

OPD based on Pytorch (Fang et al, AAAI 21)

DeepTrader based on Pytorch (Wang et al, AAAI 21)

SARL based on Pytorch (Yunan Ye et al, AAAI 20)

ETTO based on Pytorch (Lin et al, 20)

Investor-Imitator based on Pytorch (Yi Ding et al, KDD 18)

EIIE based on Pytorch (Jiang et al, 17)

Classic RL based on Pytorch and Ray: PPO A2C Rainbow SAC DDPG DQN PG TD3