A research-driven algorithmic trading system for developing, validating, and deploying quantitative strategies.
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Updated
Sep 4, 2026 - Python
A research-driven algorithmic trading system for developing, validating, and deploying quantitative strategies.
A low-allocation MachineLearning and Algorithmic trading framework. It is designed for high-throughput real-time services
This is a well-architected, modular Go streaming Technical Analysis (TA) library designed for high-frequency trading workloads requiring zero-allocation mathematical calculations.
Blankly-Finance-Plugin: Advanced RSI-Trading-Strategy and Machine-Learning tools. Features a Technical-Analysis-API for Crypto-Asset-Management.
Shared workspace for ESGF_School Quant Connect organization
Native C++ shared library implementing quantitative trading algorithms: Altman Z, Piotroski, DCF, PEG, Greenblatt, momentum, composite scoring.and much more.
Structural trading research mapping synthetic market engines, actor behavior, spike ignition, timing sync, liquidation flow, and candle microstructure. Built from spatiotemporal pattern recognition, dynamic systems perception, and microstructure intuition.
π Educational virtual trading platform using Streamlit & Supabase. Features a hybrid price engine for risk-free simulation, strategy backtesting, and quantitative research. Perfect for fintech open-source contributors!
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