CamHEX2021
Repository for the Cambridge HEX 2021 event for the Optiver trading challenge.
Run instructions
python src/AlgoPassive.py
Collaboration instructions
This code runs in a virtual environment (venv or conda) that is described by the requirements.txt file. See https://docs.python.org/3/library/venv.html for details. Below instructions are for using pip on a Linux/OS X system. Use the link for a Windows system with conda.
- Create new (empty) Python 3 environment on your local system, e.g. `python3 -m venv /path/to/new/virtual/environment`
- Activate your environment: `source /bin/activate`
- Navigate to path where you want to clone this repository
- git clone to clone this repository to your system
- Enter root folder of repository
- Install all existing dependencies of the project into your venv: `pip install requirements.txt`
- If you add new packages/dependencies, install them the regular way while you are in your venv. Then to add them to the `requirements.txt` file, use a command like `pip freeze > requirements.txt` so that new packages are added.
- Commit changes and push/pull request to remote repository
Useful articles about technical indicators
Articles about implementing trading algorithms based on simple technical indicators.
- https://medium.com/swlh/4-technical-indicators-i-use-in-technical-analysis-b065c8737823
- https://medium.com/swlh/creating-a-contrarian-indicator-using-moving-averages-in-python-de898d9f29c2
- https://kvbprime.medium.com/how-to-use-moving-averages-when-trading-61f2df9ed14f
- https://towardsdatascience.com/how-to-create-a-fully-automated-ai-based-trading-system-with-python-708503c1a907
A possible 5th: Inbalance in the order book. I couldn't find an easy-to-read article so quickly, but generally the buy vs sell order volume says something about near-future price movements too.
Group members
- Raquel Manzano
- Quincy van den Berg
- torus403
- kitfunso
- gg1998