This project was done in the context of the Applied Algorithm Trading Course (FINM 35910) at the University of Chicago.

Build an algorithm trading strategy with multiple constraints dictated by the teacher in terms of market impact, liquidity, frequency of trades...

The majority of the code that are with respect to analysis can be found in "analysis.py". The "data.py" code is there to generate and clean the data from source files, and "backtester.py" is the functions we used to backtest our strategy. The presentation to see the relevant results is under "trading_presentation.ipynb".

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

Laurent Lanteigne

MIT © lanteignel93