QSTrader offers a modular Python backtesting framework for long-short equity strategies using daily OHLC data and calendar-driven rebalancing. Its clean separation of signal, portfolio, and execution components stands out.
A curated GitHub repo consolidates 200+ quality resources for quantitative and ML-driven algorithmic trading, bridging academic research and practical strategies.
FinRL-Trading offers a modular Python framework for quantitative trading focused on a weight-centric architecture unifying backtesting and live execution, with classical and DRL portfolio methods.
QuantDinger unifies AI-assisted research, Python strategy development, backtesting, and live trading in a self-hosted platform with scoped AI agent tokens and strict safety defaults.
rust-trade is a Rust quantitative crypto trading system combining real-time data collection, backtesting, and a Tauri desktop app. Its multi-level caching achieves ~390µs insert latency and ~13ms batch processing.
TradeMaster offers a full pipeline for RL-based quantitative trading with 13+ algorithms and a rigorous 6-axis, 17-measure evaluation framework across multiple asset classes and trading tasks.
