Explore live open-source projects and AI models.

OpenAI Codex + GPT-5.5 assisted A-share quantitative finance research toolkit using Harness-style backtesting, stock selection, paper trading, and risk review

Uses Reddit, Twitter, Google, Historic, Technical Analysis and Blockchain based data to predict crypto currency prices. Done as my undergrad dissertation. Uses a self made backtest module.

Algotrading framework for C++17

Built in C# & Winforms, QuantTrade provides a way to quickly build and backtest stock investment strategies using technical indicators such as the MACD, SMA, etc.

Opening Range Breakout system in Python — reproducible backtest, risk management and walk-forward validation. Results are in the repo; no return promises.

End-to-end algorithmic trading terminal featuring PyTorch LSTM forecasting, NLP market sentiment analysis, Lasso ML feature selection, and vectorbt backtesting. Built for multi-asset quantitative research.

PHP & Laravel SDK for the CoinQuant Public API. Streaming prompts, one-call backtests, strategy materialization, and all 37 endpoints via Guzzle. Works standalone or with Laravel auto-discovery. PHP 8.1+, Laravel 10–13.

Event-Driven BackTesting Framework

Бэктестинг торговых стратегий с помощью библиотек на Python

Backtesting Engine for Indian Traders