QuantMuse

Why we included this project

Quant developers and traders tired of cobbling together separate scripts for each stage of a pipeline will find this a useful base. It ingests live market data from several exchanges over WebSockets, runs factor analysis on momentum, value, quality and volatility, and feeds machine learning models like XGBoost and neural networks for signal generation. The OpenAI integration adds a layer of market commentary and sentiment pulled from news and social feeds, which is handy when you want narrative context alongside the numbers. With more than eight bundled strategies and a C++ execution core for lower-latency order handling, it is a workable place to test an idea from data intake to execution before you invest in a custom stack.