Backtesthub is a simple and efficient backtest framework, built upon numpy and pandas to enable fast calculations, providing handy resources for quantitative researchers:
- Run backtests on signal based (systematic) strategies;
- Manage position/sizing [stocks and futures];
- Manage orders w/ commission & slippage schemes;
- Output backtest metrics for evaluation.
This project attempts to merge ideas from the two best python backtest frameworks imo [backtrader and backtesting], and introduces some ideas I think could've been implemented on both (e.g. broadcasting, base/asset separation, etc.)
Note: The project is still going under several improvements. Do not use it without reading the comments on code!! - Important simplyfing assumptions and inner workings are explained in detail there.
Conda
# Create a new environment
conda create -name backtest
source activate backtest
# Install libraries
pip install -r requirements.txt
# Install setup.py and enjoy!
python setup.py install