Quantitative Trading
Showing 13 of 13 projects
A curated list of insanely awesome libraries, packages, and resources for Quantitative Finance (Quants).
An open-source Python quantitative trading system supporting stocks, options, futures, and cryptocurrencies with integrated machine learning.
A collection of Python scripts for backtesting quantitative trading strategies, including technical indicators, options strategies, and quantamental analysis.
An open-source, low-latency trading execution system for quantitative traders, supporting Python and C++ strategies.
A curated collection of high-quality resources for quantitative and algorithmic trading with a focus on machine learning applications.
An AI-native modular infrastructure for quantitative trading, featuring a weight-centric architecture for building, testing, and deploying algorithmic strategies.
A collection of Python notebooks and tools for quantitative finance research, including backtesting, machine learning, and portfolio optimization.
A machine learning framework for developing high-frequency trading strategies using full orderbook tick data.
A repository implementing Deep Reinforcement Learning and Supervised Learning methods with a simulated financial market environment for quantitative trading.
A modern, high-performance technical analysis library built in Rust with Python and WebAssembly bindings.
A reinforcement learning environment for training trading agents using real Korean equities orderbook and execution data.
A collection of quantitative trading research experiments exploring uncommon strategies and techniques through Jupyter notebooks.
A collection of academic papers and code implementations for quantitative trading strategies.
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