Python quantitative trading and investment platform
EliteQuant is an open source forever free unified quant trading platform built by quant traders, for quant traders. It is dual listed on both github and gitee.
The word unified carries two features.
- First it’s unified across backtesting and live trading.
Just switch the data source to play with real money.
- Second it’s consistent across platforms written in their native langugages.
It becomes easy to communicate with peer traders on strategies, ideas, and replicate performances, sparing language details.
Related projects include
EliteQuant_Python is Python3 based multi-threading, concurrent high-frequency trading platform that provides consistent backtest and live trading solutions.
It follows modern design patterns such as event-driven, server/client architect, and loosely-coupled robust distributed system. It follows the same structure and performance metrix as other EliteQuant product line, which makes it easier to share with traders using other languages.
Please feel free to report issues, fork the branch, and create pull requests.
Any kind of contributions are welcomed and appreciated.
Watch Me Build a Trading Bot
Through shared code architecture, it also helps traders using other languges.
No installation is needed, it's ready for use out of box.
Just download the code and enjoy.
On python side, it depends some python packages.
Here are the instructions after a clean installation of Anaconda Python 3.6 on Windows 10 system.
- Add the unzipped folder for example d:\workspace\EliteQuant_Python to PYTHONPATH environment variable
- pip install the following under command prompt cmd
Configure config_backtest.yaml in the source directory
- datasource: historical data source
- hist_dir: local history data directory
- output_dir: output test results directory
Currently it supports data source from
stay in command prompt, execute
Live trading needs one more python package, nanomsg.
Here is how to install it on Windows
- In command prompt, execute
go to folder createed by last step, C:\Anaconda3\Lib\site-packages\nanomsg-1.0-py3.6-win-amd64.egg\nanomsg-1.0-py3.6-win-amd64.egg, cut+paste move everything one level up, and delete the extra folder nanomsg-1.0-py3.6-win-amd64.egg.
copy resource\nanomsg.dll to C:\Anaconda3\Lib\site-packages\nanomsg-1.0-py3.6-win-amd64.egg\
After that, configure source/config.yaml
- If you want to use interactive broker, open IB trader workstation (TWS), go to its menu File/Global Configuration/API/Settings, check "Enable ActiveX and Socket Client", uncheck "Read-Only API"
- In the config file, change the account id to yours; IB account id usually can be found on the top right of the TWS window.
- If you use CTP, change your brokerage account information and ctp addresses accordingly.
- create folder for log_dir and data_dir respectively.
The former records runtime logs, while the later saves tick data.
run python live_engine.py
Interactive Brokers is the most popular broker among retail traders.
A lot of retail trading platform such as quantopian, quantconnect are built to support IB. If you don't have IB account but want to try it out, they provide demo account edemo with password demouser. Just download TWS trader workstation and log in with this demo account.
Note that accound id changes everytime you log on to TWS with demo account so you have to change EliteQuant config file accordingly.
CTP is the de-facto brokerage for Chinese futures market, including commodity futures and financial futures. They also offer free demo account SimNow.
After registration, you will get account, password, brokerid, along with market data and trading broker address. Replace them in EliteQuant config file accordingly.
Below is the environment we are using
- Anaconda Python 3.6
- PyCharm Community version 2017.2.4