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R package for fast trading system design and backtesting.

Backtest and run stock trading CFD strategies tick by tick

A quantitative tool that selects stocks through a large model semantic filtering and completes A-share strategy backtesting and strategy report output, aiming to quickly verify investment ideas.

A reproducible trading research lab. No free lunch. No magic backtests.

Bloomberg-style terminal for public U.S. politician stock disclosures (STOCK Act): backtests on their real exits, copyability leaderboards, AI screening, Alpaca copy-trading automation, and an MCP server. Delayed public data; not financial advice.

Analyze Jesse backtest results and indicators with clean TradingView charts in Jupyter

Open-source Rust framework for building event-driven live-trading & backtesting systems

Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges one package.

Claude Hedge - The Princeton Anomaly | AI-driven systematic futures trading | 2003 Princeton thesis | +54% live (32 days) | +240% CAGR (4yr backtest) | Time-zone arbitrage + VIX-adaptive risk

This repository demonstrates application of unsupervised learning in the financial markets. K-Means clustering is employed to create a diversified portfolio of stocks and the resulting portfolio is backtesting against the S&P500 Index