Repository for the Cambridge HEX 2021 event for the Optiver trading challenge.

python src/AlgoPassive.py

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.

1. Create new (empty) Python 3 environment on your local system, e.g. `python3 -m venv /path/to/new/virtual/environment`
2. Activate your environment: `source /bin/activate`
3. Navigate to path where you want to clone this repository
4. git clone to clone this repository to your system
5. Enter root folder of repository
6. Install all existing dependencies of the project into your venv: `pip install requirements.txt`
7. 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.
8. Commit changes and push/pull request to remote repository

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.

• Raquel Manzano
• Quincy van den Berg
• torus403
• kitfunso
• gg1998