Publication

Deep Reinforcement Learning for Quantitative Trading: Challenges and Opportunities (IEEE Intelligent Systems 2022)

DeepScalper: A Risk-Aware Reinforcement Learning Framework to Capture Fleeting Intraday Trading Opportunities (CIKM 2022)

Commission Fee is not Enough: A Hierarchical Reinforced Framework for Portfolio Management (AAAI 21)

Reinforcement Learning for Quantitative Trading (Survey)

PRUDEX-Compass: Towards Systematic Evaluation of Reinforcement Learning in Financial Markets

File Structure

Here is the structure of the TradeMaster project.

| TradeMaster
| ├── configs
| │   ├── base
| │   ├── algorithmic_trading
| │   ├── order_excution
| │   └── porfolio_management
| ├── data
| │   ├── algorithmic_trading          
| │   ├── order_excution          
| │   └──  porfolio_management
| ├── deploy
| │   ├── backend_client_test.py         
| │   ├── backend_client.py
| │   ├── backend_service_test.py  
| │   └── backend_service.py  
| ├── tools
| │   ├── algorithmic_trading          
| │   ├── MarketRegimeLabeling   
| │   ├── order_excution  
| │   ├── porfolio_management  
| │   ├── __init__.py 
| │   └── tmp.py      
| ├── tradmaster
| │   ├── __pycache         
| │   ├── agents   
| │   ├── datasets 
| │   ├── enviornments 
| │   ├── losses
| │   ├── nets
| │   ├── optimizers
| │   ├── pretrained
| │   ├── trainers
| │   ├── utils
| │   └── __init__.py     
| ├── unit_testing
| │   ├── test_agents\algorithmic_trading        
| │   ├── test_datasets
| │   ├── test_enviornments 
| │   ├── test_losses
| │   ├── test_nets
| │   ├── test_optimizers
| │   ├── test_trainers
| │   ├── __init__.py   
| │   └── test_score.py  
| ├── LICENSE
| ├── python3.9.yaml
| └── README.md

In the folder structure above:

• configs contains configuration files directory for agents trainng.

• data contains the data for training and testing.

• deploy contains the backend deploying scripts.

• tools contains training scripts.

• trademaster contains the files defining agents,enviornments, training losses, nets, optimizers and helper functions.

• unit_testing contains the components for testing.

External Sources

Users may download data from the following data source with personal account:

Data Source	Type	Range and Frequency	Request Limits	Raw Data
Alpaca	US Stocks, ETFs	2015-now, 1min	Account-specific	OHLCV
Baostock	CN Securities	1990-12-19-now, 5min	Account-specific	OHLCV
Binance	Cryptocurrency	API-specific, 1s, 1min	API-specific	Tick-level daily data
CCXT	Cryptocurrency	API-specific, 1min	API-specific	OHLCV
IEXCloud	NMS US securities	1970-now, 1 day	100 per second per IP	OHLCV
JoinQuant	CN Securities	2005-now, 1min	3 requests each time	OHLCV
QuantConnect	US Securities	1998-now, 1s	NA	OHLCV
RiceQuant	CN Securities	2005-now, 1ms	Account-specific	OHLCV
Tushare	CN Securities, A share	-now, 1 min	Account-specific	OHLCV
WRDS	US Securities	2003-now, 1ms	5 requests each time	Intraday Trades
YahooFinance	US Securities	Frequency-specific, 1min	2,000/hour	OHLCV

Change Log

New Contributors

Frequently Asked Questions