TradingMachine
TradingMachine is intend to bring optimization and machine techniques into finance algorithmic trading.
Discussion and Help
TODO
Features
- Optimization on strategy parameters.
- PyBrain Integration (Reinforcement Learning, Neural Network ...).
- TA-Lib Integration (Most common technical analysis available.)
- Pandas (High speed time series data analysis)
Installation
# You will first need to install TALib. ta-lib is a python wrapper for that. Please refer [TA-Lib](http://ta-lib.org/hdr_doc.html)
TradingMachine can be installed via pip
` pip install numpy pip install matplotlib pip install pandas pip install ta-lib pip install tradingmachine `
If there are problems installing the dependencies, please consider install scipy stack. For Windows, the [Enthought Python Distribution](http://www.enthought.com/products/epd.php) includes most of the necessary dependencies. On OSX, the [Scipy Superpack](http://fonnesbeck.github.com/ScipySuperpack/) works very well. Other platforms, the [Scipy Stack](http://www.lfd.uci.edu/~gohlke/pythonlibs/) has binary available to install.
After installation, you will need to create a configuration file in home directory named ".tmconfig.ini".
1 [DEFAULT] 2 HistoricalDataPath = /Users/chen/Repository/historicaldata
Configuration file is intended to point to the historical data folder. A copy of historical data can be downloaded from: [historicalata](https://github.com/chinux23/historicaldata)
Dependencies
- Python (>= 3.3.1)
- numpy (>= 1.7.1)
- pandas (>= 0.11.0)
- pytz
- ta-lib
Contact
For other questions, please contact Chen Huang <chinux@gmail.com>.