Random Forest Cat: An ML Trading Factory

Random Forest Cat: An ML Trading Factory

I open-sourced a multi-model, machine-learning based factory for trading strategies on GitHub. It's written in Python and is highly customizable, as it exposes a framework for configuring the pipeline via a DSL.

Currently, it comes with two pipeline configurations: one that focuses on predicting wether the price of Bitcoin in 5 minutes will be higher or lower than now (Polymarket style), and a more generic strategy that shorts or longs Bitcoin at its own discretion.

This project also represents an experiment on enabling AI agents to discover trading strategies that will be profitable with real world, live price data. Clone the project and try asking an LLM to generate a profitable trading strategy using the framework.

You can also just train your own model (or use mine) and use its signals for live trades. Beware that this is a work in progress. I've already integrated an explicit split for a the validation set, but that code is not pushed yet -- I'll probably do it today. More improvements are also on the way.

In either case, the current version of the code on GitHub works, so you can download and run it.

GitHub Repository Link: https://github.com/iluxonchik/random-forest-cat-ml-factory