This repo demystifies algorithmic trading by walking through building S&P 500 equal-weight, momentum, and value strategies in Python using Jupyter notebooks and free IEX Cloud data.
This curated repo maps the shift in systematic trading from event-driven backtesters to AI-powered strategy discovery, covering multi-asset tools, high-frequency backtesting, and AI agents.
QuantaAlpha uses large language models with evolutionary strategies to automate quantitative alpha factor discovery, achieving strong backtest metrics on major indices.
