Quantitative Finance
Showing 31 of 31 projects
An open-source data platform that integrates proprietary, licensed, and public financial data sources for analysts, quants, and AI agents.
A multi-agent LLM framework for financial trading that simulates real-world trading firms with specialized AI agents for market analysis and decision-making.
A community-maintained list of Summer 2026 tech internship opportunities across software engineering, data science, product management, and more.
A curated list of insanely awesome libraries, packages, and resources for Quantitative Finance (Quants).
An open-source, event-driven algorithmic trading engine for backtesting and live trading across multiple financial markets.
An elegant and simple Python library for fetching financial data from various sources, designed for quantitative research.
A community-maintained list of entry-level software engineering, product management, quant, and tech jobs for new graduates.
An open-source framework for applying deep reinforcement learning to quantitative finance, featuring a train-test-trade pipeline for stock and crypto trading.
An open-source C# platform for algorithmic trading and quantitative analysis across stocks, forex, crypto, and options markets.
A collection of Python scripts for backtesting quantitative trading strategies, including technical indicators, options strategies, and quantamental analysis.
A comprehensive collection of machine learning and deep learning models, trading agents, and simulations for stock market forecasting.
A curated list of practical financial machine learning tools, applications, and research repositories.
A free/open-source C++ library for modeling, trading, and risk management in quantitative finance.
An open-source AI agent platform for financial analysis, automating equity research, algorithmic trading, and risk assessment using LLMs.
A Python library for performance and risk analysis of financial portfolios, generating comprehensive tear sheets.
An open-source Python framework for building, training, and evaluating reinforcement learning agents for algorithmic trading.
A curated list of awesome resources for applying LLMs and deep learning to financial market analysis and algorithmic trading.
A command-line tool that automates cryptocurrency technical analysis and trading alerts using Docker.
A high-performance TensorFlow library for quantitative finance, providing mathematical methods, pricing models, and calibration tools.
A modular quantitative finance framework for data collection, analysis, strategy backtesting, and machine learning across multiple markets.
A Python framework for developing and backtesting algorithmic trading strategies with machine learning.
A Python library for pricing and risk management of financial derivatives including fixed-income, equity, FX, and credit derivatives.
A collection of Python notebooks and tools for quantitative finance research, including backtesting, machine learning, and portfolio optimization.
A Python-based high-frequency trading model using Interactive Brokers API for pairs trading and mean-reversion strategies.
A Java library for building, testing, and deploying automated trading strategies with 200+ technical indicators and production-ready tooling.
A machine learning framework for developing high-frequency trading strategies using full orderbook tick data.
A Python library implementing over 80 financial technical indicators using Pandas for trading analysis.
A Python toolkit for training reinforcement learning agents and backtesting rule-based algorithms in financial markets.
A deep reinforcement learning framework for financial portfolio management with policy gradient optimization and backtesting tools.
A comprehensive Rust library for quantitative finance, offering pricing models, risk analysis, and financial data tools.
A financial market simulation engine powered by a generative foundation model for realistic, interactive, and controllable order generation.
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