Quantitative Finance
Showing 36 of 48 projects
A multi-agent LLM framework for financial trading that simulates real-world trading firms with specialized AI agents for market analysis and decision-making.
An open-source data platform that integrates proprietary, licensed, and public financial data sources for analysts, quants, and AI agents.
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 elegant and simple Python library for fetching financial data from various sources, designed for quantitative research.
An open-source, event-driven algorithmic trading engine for backtesting and live trading across multiple financial markets.
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.
A Python library for calculating common financial risk and performance metrics used in quantitative finance.
A pandas DataFrame wrapper for calculating over 70 stock market indicators and statistics with inline column access.
A comprehensive Go library for technical analysis, offering indicators, strategies, and backtesting with no external dependencies.
Experimental implementations of financial machine learning techniques from 'Advances in Financial Machine Learning' for stochastic time series data.
A .NET library for computing technical indicators, building trading strategies, and backtesting automated stock trading systems.
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