Awesome Quant

August 14, 2026 · View on GitHub

A curated list of quantitative research, trading research, and market microstructure resources.

The list is automatically refreshed from GitHub repository metadata.

Contents

Research Frameworks

  • xbtlin/ai-berkshire — AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code / Codex. 4 masters' methodologies + multi-agent adversarial analysis. Python · ⭐ 6,925 · forks 0 · updated 2026-06-30 · license MIT
  • initial-d/ml-quant-trading — PyTorch research stack for ML multi-factor trading: 213 factors, bias correction, portfolio optimization, and vectorized backtesting. Python · ⭐ 54 · forks 0 · updated 2026-07-27 · license MIT
  • mirror29/inalpha — 🦊 Open-source professional quant agent framework. Agents pick the factors working now to time entries, write full strategies, and evolve them in a sandbox — every order through machine approval, the LLM never on the order path. Multi-market, audit-grade. Python · ⭐ 22 · forks 0 · updated 2026-07-21 · license AGPL-3.0
  • TauricResearch/TradingAgents — TradingAgents: Multi-Agents LLM Financial Trading Framework Python · ⭐ 0 · forks 0 · updated 2026-06-01 · license Apache-2.0
  • tradingstrategy-ai/trading-strategy — Python framework for quantitative financial analysis and trading algorithms on decentralised exchanges Python · ⭐ 0 · forks 0 · updated 2026-05-28 · license NOASSERTION
  • Drakkar-Software/OctoBot-Script — Quant trading framework by OctoBot. Write, backtest & automate Python trading strategies like TradingView Pine Script. Work in progress. TypeScript · ⭐ 0 · forks 0 · updated 2026-05-24 · license GPL-3.0
  • arteemg/AutoHypothesis — Open-source framework for agentic quantitative finance research. Python · ⭐ 0 · forks 0 · updated 2026-04-29 · license N/A
  • zvtvz/zvt — modular quant framework. Python · ⭐ 0 · forks 0 · updated 2026-04-13 · license MIT
  • horizon-llm/AlphaQuanter — [ACL2026] AlphaQuanter: An End-to-End Tool-Orchestrated Agentic Reinforcement Learning Framework for Stock Trading. Python · ⭐ 0 · forks 0 · updated 2025-10-17 · license N/A
  • joshuaulrich/quantmod — Quantitative Financial Modelling Framework R · ⭐ 0 · forks 0 · updated 2025-08-07 · license GPL-3.0
  • Go-Quant/goquant — GoQuant is a powerful Go framework designed for financial data analysis and visualizations, with no boundaries! Go · ⭐ 0 · forks 0 · updated 2024-09-17 · license NOASSERTION
  • jsmidt/QuantPy — A framework for quantitative finance In python. Python · ⭐ 0 · forks 0 · updated 2023-05-25 · license BSD-4-Clause
  • foolcage/fooltrader — quant framework for stock Python · ⭐ 0 · forks 0 · updated 2023-05-22 · license MIT
  • constverum/Quantdom — Python-based framework for backtesting trading strategies & analyzing financial markets [GUI :neckbeard:] Python · ⭐ 0 · forks 0 · updated 2022-07-06 · license Apache-2.0
  • AshiteshSingh/Tpu-Accelerated-Quantum-JAX — High-performance, differentiable quantum state-vector & tensor network simulator in 100% pure JAX (no classical framework overhead). Accelerated on NVIDIA GPUs and Google Cloud TPU v6e-64/v5e VM clusters up to 37 qubits! Supported by Google's TPU Research Cloud (TRC) program. Jupyter Notebook · ⭐ 103 · forks 0 · updated 2026-06-12 · license Apache-2.0
  • akfamily/akquant — AKQuant is a high-performance quantitative research and trading framework built on Rust and Python! 开源量化回测框架 Python · ⭐ 0 · forks 0 · updated 2026-06-01 · license MIT

Backtesting

  • mementum/backtrader — Python Backtesting library for trading strategies Python · ⭐ 22,839 · forks 5,236 · updated 2024-08-19 · license GPL-3.0
  • hummingbot/hummingbot — Open source software that helps you create and deploy high-frequency crypto trading bots Python · ⭐ 18,945 · forks 0 · updated 2026-06-19 · license Apache-2.0
  • HKUDS/Vibe-Trading — "Vibe-Trading: Your Personal Trading Agent" Python · ⭐ 12,834 · forks 0 · updated 2026-06-20 · license MIT
  • OpenByteInc/QuantDinger — AI quantitative trading platform for crypto, stocks, and forex with backtesting, live trading, market data, and multi-agent research.vibe-trading ,trading-agents,ai-trader,ai-trading Python · ⭐ 9,794 · forks 0 · updated 2026-07-19 · license Apache-2.0
  • kernc/backtesting.py — 🔎 📈 🐍 💰 Backtest trading strategies in Python. Python · ⭐ 8,545 · forks 0 · updated 2025-12-20 · license AGPL-3.0
  • brokermr810/QuantDinger — AI quantitative trading platform for crypto, stocks, and forex with backtesting, live trading, market data, and multi-agent research.vibe-trading ,trading-agents,ai-trader,ai-trading Python · ⭐ 8,410 · forks 0 · updated 2026-06-19 · license Apache-2.0
  • ricequant/rqalpha — A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities Python · ⭐ 6,495 · forks 0 · updated 2026-06-17 · license NOASSERTION
  • nkaz001/hftbacktest — Free, open source, a high frequency trading and market making backtesting and trading bot, which accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books(Level-2 and Level-3), with real-world crypto trading examples for Binance and Bybit Rust · ⭐ 4,207 · forks 0 · updated 2025-12-23 · license MIT
  • mhallsmoore/qstrader — QuantStart.com - QSTrader backtesting simulation engine. Python · ⭐ 3,396 · forks 0 · updated 2024-06-30 · license MIT
  • cuemacro/finmarketpy — Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians) Python · ⭐ 3,777 · forks 0 · updated 2026-04-16 · license Apache-2.0
  • blankly-finance/blankly — 🚀 💸 Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges w/ one package. Python · ⭐ 2,464 · forks 314 · updated 2024-12-30 · license LGPL-3.0
  • edtechre/pybroker — Algorithmic Trading in Python with Machine Learning Python · ⭐ 3,430 · forks 0 · updated 2026-05-11 · license NOASSERTION
  • pmorissette/bt — bt - flexible backtesting for Python Python · ⭐ 2,893 · forks 0 · updated 2026-05-05 · license MIT
  • letianzj/QuantResearch — Quantitative analysis, strategies and backtests Jupyter Notebook · ⭐ 2,959 · forks 0 · updated 2023-08-26 · license MIT
  • fasiondog/hikyuu — Hikyuu Quant Framework 基于C++/Python的超高速开源量化交易研究框架，同时可基于策略部件进行资产重用，快速累积策略资产。 C++ · ⭐ 3,266 · forks 0 · updated 2026-06-21 · license Apache-2.0
  • barter-rs/barter-rs — Open-source Rust framework for building event-driven live-trading & backtesting systems Rust · ⭐ 2,172 · forks 0 · updated 2026-06-06 · license MIT
  • cinar/indicator — Indicator Go delivers a rich set of technical analysis indicators, customizable strategies, and a powerful backtesting framework. No dependencies, just pure simplicity. ✨ See how! 👀 Go · ⭐ 1,222 · forks 199 · updated 2026-08-10 · license AGPL-3.0
  • whittlem/pycryptobot — Python Crypto Bot (PyCryptoBot) Python · ⭐ 2,053 · forks 0 · updated 2026-03-26 · license Apache-2.0
  • Lumiwealth/lumibot — Backtestable AI trading agents and Python algorithmic trading strategies for stocks, options, crypto, futures, forex, SEC filings, FRED macro data, and real brokers. Python · ⭐ 1,883 · forks 0 · updated 2026-08-05 · license GPL-3.0
  • Kismuz/btgym — Scalable, event-driven, deep-learning-friendly backtesting library Python · ⭐ 1,034 · forks 258 · updated 2021-08-28 · license LGPL-3.0

Simulation & Synthetic Data

  • Alinebm17/trade-backtesting-engine — Trade backtesting engine for DCA (Dollar Cost Averaging) and Grid trading strategies with technical indicator support and historical market data simulation for TypeScript · ⭐ 141 · forks 0 · updated 2026-07-14 · license MIT
  • cunarist/solie — GUI trading bot designed for targeting the futures markets of Binance Python · ⭐ 59 · forks 0 · updated 2026-05-28 · license GPL-3.0
  • Jackson-Wozniak/Stock-Market-Simulation — A virtual stock market and trading platform. Includes a fully simulated stock market, with dynamic price changes and news events. Simulation models a real calendar with time sped up Java · ⭐ 60 · forks 0 · updated 2026-04-29 · license MIT
  • tum-ens/HAMLET — HAMLET: Hierarchical Agent-based Markets for Local Energy Trading Python · ⭐ 25 · forks 0 · updated 2026-08-12 · license MIT
  • Surbeivol/PythonMatchingEngine — High performance trading Matching Engine / Market Simulator using Level 3 Market Data for realistic simulation of High Frequency Trading Strategies Python · ⭐ 135 · forks 0 · updated 2024-05-03 · license MIT
  • jmcph4/PyOBSim — A Python module for market simulation Python · ⭐ 24 · forks 0 · updated 2026-06-29 · license MIT
  • harrypapadakis/StockSim — 💹 StockSim: Multi-Agent LLM Financial Market Simulator — A realistic trading simulation platform for evaluating large language models in dynamic financial environments. Python · ⭐ 37 · forks 0 · updated 2025-07-15 · license N/A
  • NicolaNardino/TradingMachine — TradingMachine is a mini-trading system simulation, whose components (market data and order feeds, FIX acceptor and initiator, back-end for filled orders) interact by queues and topics. Java · ⭐ 41 · forks 0 · updated 2024-12-26 · license N/A
  • ronilbhatia/EasyTrade — A clone of the popular stock-trading app Robinhood, allowing for the simulation of trades for all stocks listed on the NASDAQ and NYSE exchanges, using real-time market data Ruby · ⭐ 95 · forks 0 · updated 2023-01-19 · license N/A
  • hoangsonww/Stock-Market-Simulator — 📈 This repository hosts a Stock Market Simulation in Python, providing tools to mimic market behaviors, portfolio management, and trading strategies. It serves as an educational resource for learning about financial markets and algorithmic trading, offering a practical platform for testing theories and strategies in a risk-free environment. Python · ⭐ 23 · forks 0 · updated 2023-03-27 · license EPL-2.0
  • JohnNay/predMarket — Computational simulation framework for analyzing trading behavior in climate prediction markets HTML · ⭐ 24 · forks 0 · updated 2020-07-12 · license N/A

Alpha Research

  • VivekPa/AIAlpha — Use unsupervised and supervised learning to predict stocks Python · ⭐ 1,951 · forks 448 · updated 2020-06-18 · license MIT
  • ICT-FinD-Lab/alphagen — Generating sets of formulaic alpha (predictive) stock factors via reinforcement learning. Python · ⭐ 1,189 · forks 320 · updated 2026-06-04 · license N/A
  • alphavantage/alpha_vantage_mcp — Alpha Vantage MCP Server Python · ⭐ 188 · forks 0 · updated 2026-07-26 · license MIT
  • ArturSepp/factorlasso — Sparse factor models with sign-constrained, grouped and cooperative LASSO penalties (HCGL, FCGL, SGL) via CVXPY - scikit-learn compatible Python · ⭐ 20 · forks 0 · updated 2026-07-24 · license GPL-3.0
  • yupoet/aurumq-rl — RL stock selection for China A-share — bundled polars-native factor library (105 Alpha101 + 191 GTJA Alpha191 = 296 factors), board-aware price limits, GPU train + ONNX CPU infer, MIT-licensed. Python · ⭐ 21 · forks 0 · updated 2026-07-05 · license NOASSERTION
  • husainm97/quant-lab-alpha — Open-source investment analytics platform bridging academic research and retail finance. Features include portfolio risk decomposition [Fama-French Five Factor Model], retirement sustainability modeling [Block Bootstrap Monte Carlo], max drawdown/CVaR dashboards, and risk-return optimisation [Markowitz, Ledoit-Wolf] via an intuitive user interface. Python · ⭐ 0 · forks 0 · updated 2026-05-17 · license MIT
  • stefanoviana/deepalpha — AI crypto trading bot with deep neural network (84.9% accuracy, 25 coins). BiLSTM + Attention trained on GPU. Bybit, Binance, OKX, Gate.io. Free cloud or self-hosted. Python · ⭐ 0 · forks 0 · updated 2026-05-12 · license MIT
  • QuantaAlpha/QuantaAlpha — QuantaAlpha transforms how you discover quantitative alpha factors by combining LLM intelligence with evolutionary strategies. Just describe your research direction, and watch as factors are automatically mined, evolved, and validated through self-evolving trajectories. Python · ⭐ 0 · forks 0 · updated 2026-05-07 · license N/A
  • VernonOY/alpha-skills — Quantitative factor research skills for AI coding assistants N/A · ⭐ 0 · forks 0 · updated 2026-04-14 · license Apache-2.0
  • FinStep-AI/Alpha-R1 — Alpha Screening with LLM Reasoning via Reinforcement Learning N/A · ⭐ 0 · forks 0 · updated 2025-12-30 · license N/A
  • AlphaSmartDog/DeepLearningNotes — 机器学习和量化分析学习进行中 Jupyter Notebook · ⭐ 379 · forks 0 · updated 2018-02-03 · license MIT
  • braverock/FactorAnalytics — No description provided. R · ⭐ 0 · forks 0 · updated 2024-12-12 · license N/A
  • quantopian/alphalens — Performance analysis of predictive (alpha) stock factors Jupyter Notebook · ⭐ 0 · forks 0 · updated 2024-02-12 · license Apache-2.0
  • alpha-miner/Finance-Python — python tools for Finance with the functionality of indicator calculation, business day calculation and so on. Python · ⭐ 0 · forks 0 · updated 2024-01-01 · license MIT
  • nuglifeleoji/Factor-Research — Advanced Quantitative Factor Research: ML-powered stock return prediction with 72% performance improvement. Features comprehensive alpha factor library, systematic feature selection, and deep learning models (LSTM+ResNet achieving IC=0.06476). Jupyter Notebook · ⭐ 413 · forks 0 · updated 2025-08-22 · license N/A
  • leosmigel/analyzingalpha — No description provided. Python · ⭐ 0 · forks 0 · updated 2023-08-08 · license N/A
  • je-suis-tm/machine-learning — Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression Jupyter Notebook · ⭐ 0 · forks 0 · updated 2022-12-16 · license Apache-2.0
  • ram-ki/101_formulaic_alphas — Implemention of 101 formulaic alphas using qstrader Python · ⭐ 0 · forks 0 · updated 2022-07-11 · license N/A
  • dppalomar/covFactorModel — Covariance Matrix Estimation via Factor Models R · ⭐ 39 · forks 0 · updated 2019-03-25 · license GPL-3.0
  • alphanume-markets/Alphanume-Strategy-Lab — Production-ready quantitative trading research powered by Alphanume market data APIs. Python · ⭐ 59 · forks 0 · updated 2026-07-09 · license N/A

Factor Investing & Smart Beta

No repositories found in this update.

Fixed Income & Credit Models

  • rust-dd/stochastic-rs — High-performance quantitative finance in Rust — 120+ stochastic processes, option pricing, calibration, fixed income, risk & copulas, with SIMD/GPU acceleration and Python bindings. Rust · ⭐ 178 · forks 0 · updated 2026-08-11 · license MIT

Portfolio Optimization

  • PyPortfolio/PyPortfolioOpt — Financial portfolio optimization in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity Jupyter Notebook · ⭐ 5,958 · forks 1,167 · updated 2026-07-07 · license MIT
  • convexfi/riskparity.py — Fast and scalable construction of risk parity portfolios Python · ⭐ 325 · forks 75 · updated 2025-12-02 · license MIT
  • dcajasn/Riskfolio-Lib — Portfolio Optimization in Python C++ · ⭐ 0 · forks 0 · updated 2026-05-31 · license BSD-3-Clause
  • skfolio/skfolio — Python library for portfolio optimization built on top of scikit-learn Python · ⭐ 0 · forks 0 · updated 2026-05-29 · license BSD-3-Clause
  • fortitudo-tech/fortitudo.tech — Entropy Pooling views and stress testing combined with Conditional Value-at-Risk (CVaR) portfolio optimization in Python. Python · ⭐ 0 · forks 0 · updated 2026-05-07 · license GPL-3.0
  • dppalomar/pob — Supporting data package for the Portfolio Optimization Book R · ⭐ 0 · forks 0 · updated 2025-02-17 · license GPL-3.0
  • jankrepl/deepdow — Portfolio optimization with deep learning. Python · ⭐ 0 · forks 0 · updated 2024-01-24 · license Apache-2.0
  • lequant40/portfolio_allocation_js — A JavaScript library to allocate and optimize financial portfolios. JavaScript · ⭐ 0 · forks 0 · updated 2023-03-03 · license MIT
  • johnsoong216/pymarkowitz — Mean Variance (Markowitz) Portfolio Optimization and Beyond Python · ⭐ 0 · forks 0 · updated 2024-04-25 · license MIT
  • manujajay/portfolio-optimize — A simple Python package for optimizing investment portfolios using historical return data from Yahoo Finance. Users can easily determine the optimal portfolio allocation among a given set of tickers based on the mean-variance optimization method or other algorithms. Python · ⭐ 0 · forks 0 · updated 2024-03-11 · license MIT
  • dppalomar/riskParityPortfolio — Design of Risk Parity Portfolios R · ⭐ 0 · forks 0 · updated 2022-11-15 · license GPL-3.0

Financial Visualization & Dashboards

  • alihaskar/pycharting — A high-performance, open-source Python charting library for visualizing financial data with technical indicators. Built with FastAPI, uPlot, and modern web technologies. Python · ⭐ 115 · forks 0 · updated 2026-08-04 · license N/A
  • Jebel-Quant/jquantstats — Time series and portfolio analytics for quantitative finance. Python · ⭐ 42 · forks 0 · updated 2026-08-11 · license MIT
  • petermartens98/GPT4-LangChain-Stock-Market-Analysis-Agent — Python Streamlit web app with an SQLite user login/authentication system. Application allows users to select multiple stocks, metrics, and visualizations. A Langchain pandas agent utilizing GPT-4 and customized stock-market/financial prompts is then initiated allowing the user to intelligently interact with their specified data. Python · ⭐ 82 · forks 0 · updated 2023-07-13 · license N/A
  • nancyyanyu/kafka_stock — A financial data processing and visualization platform using Apache Kafka, Apache Cassandra, and Bokeh. Python · ⭐ 74 · forks 0 · updated 2021-10-05 · license Apache-2.0
  • SheikhRabiul/A-Deep-Learning-Based-Illegal-Insider-Trading-Detection-and-Prediction-Technique-in-Stock-Market — Illegal insider trading of stocks is based on releasing non-public information (e.g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public. Detecting illegal insider trading is difficult due to the complex, nonlinear, and non-stationary nature of the stock market. In this work, we present an approach that detects and predicts illegal insider trading proactively from large heterogeneous sources of structured and unstructured data using a deep-learning based approach combined with discrete signal processing on the time series data. In addition, we use a tree-based approach that visualizes events and actions to aid analysts in their understanding of large amounts of unstructured data. Using existing data, we have discovered that our approach has a good success rate in detecting illegal insider trading patterns. My research paper (IEEE Big Data 2018) on this can be found here: https://arxiv.org/pdf/1807.00939.pdf Python · ⭐ 120 · forks 0 · updated 2019-01-08 · license N/A

Risk Modeling

  • The-Swarm-Corporation/Volara — An open source risk-management tool built for stock and security risk analysis Python · ⭐ 40 · forks 13 · updated 2025-10-23 · license MIT
  • AliHabibnia/ECON_5984_CMDA_4984_Data_Science_for_Quantitative_Finance — This course in applied data science covers the theoretical foundations of advanced quantitative approaches in machine learning, econometrics, risk and portfolio management, algorithmic trading, and financial forecasting. (first taught at Virginia Tech in 2019) Jupyter Notebook · ⭐ 0 · forks 0 · updated 2026-02-26 · license MIT

Derivatives & Options Pricing

  • dbrojas/optlib — A library for financial options pricing written in Python. Python · ⭐ 1,630 · forks 0 · updated 2022-11-18 · license MIT
  • dedwards25/Python_Option_Pricing — An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options Jupyter Notebook · ⭐ 851 · forks 0 · updated 2025-05-13 · license MIT
  • just-krivi/option-pricing-models — Simple python/streamlit web app for European option pricing using Black-Scholes model, Monte Carlo simulation and Binomial model. Spot prices for the underlying are fetched from Yahoo Finance API. Python · ⭐ 332 · forks 0 · updated 2025-01-17 · license N/A
  • nl2992/fourier-option-pricer — Research-grade Python library for characteristic-function option pricing across stochastic-volatility, jump, Lévy, and hybrid models, with validated Fourier engines and reproducible benchmarks. Jupyter Notebook · ⭐ 176 · forks 0 · updated 2026-07-06 · license MIT
  • jkirkby3/fypy — Vanilla and exotic option pricing library to support quantitative R&D. Focus on pricing interesting/useful models and contracts (including and beyond Black-Scholes), as well as calibration of financial models to market data. Python · ⭐ 145 · forks 0 · updated 2025-02-27 · license MIT
  • Talha-Tariq/poptions — Custom Python code for calculating the Probability of Profit (POP) for options trading strategies using Monte Carlo Simulations. The Monte Carlo Simulation runs thousands of individual stock price simulations and uses the data from these simulations to average out a POP number. Python · ⭐ 67 · forks 0 · updated 2026-01-08 · license MIT
  • yassinemaaroufi/MibianLib — Python Options Pricing Library Python · ⭐ 289 · forks 0 · updated 2021-06-14 · license N/A
  • vicaws/arbitragerepair — Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options. Jupyter Notebook · ⭐ 127 · forks 0 · updated 2024-01-10 · license MIT
  • yzoz/python-option-calculator — Vanilla option pricing and visualisation using Black-Scholes model in pure Python Python · ⭐ 136 · forks 0 · updated 2022-09-13 · license MIT
  • MySybil/tradier-options-plotter — Quick little Python CLI tool for plotting options price history. Powered by Tradier's Sandbox API. Python · ⭐ 71 · forks 0 · updated 2022-12-05 · license N/A
  • VivekPa/BinomialOptModel — A python program to implement the discrete binomial option pricing model Python · ⭐ 84 · forks 0 · updated 2022-04-05 · license MIT
  • romanmichaelpaolucci/Algorithmic_Delta_Hedging — A library for black-scholes euro options pricing, algorithmic delta hedging, and visualization Python · ⭐ 66 · forks 0 · updated 2020-01-05 · license MIT
  • arraystream/fftoptionlib — FFT-based Option Pricing Methods in Python Python · ⭐ 59 · forks 0 · updated 2018-08-29 · license BSD-3-Clause

Market Microstructure

  • alpacahq/example-hftish — Example Order Book Imbalance Algorithm Python · ⭐ 868 · forks 0 · updated 2023-07-25 · license N/A
  • LeonardoBerti00/DeepMarket — DeepMarket is a framework for performing Limit Order Book simulation with Deep Learning. This is also the official repository for the paper 'TRADES: Generating Realistic Market Simulations with Diffusion Models'. Python · ⭐ 0 · forks 0 · updated 2026-01-27 · license MIT
  • crypto-lake/lake-api — Python API for accessing Lake high frequency tick trades & order book data Python · ⭐ 0 · forks 0 · updated 2025-11-02 · license Apache-2.0
  • alexgolec/tda-api — A TD Ameritrade API client for Python. Includes historical data for equities and ETFs, options chains, streaming order book data, complex order construction, and more. Python · ⭐ 0 · forks 0 · updated 2024-06-16 · license MIT
  • alexey-ernest/go-hft-orderbook — Golang implementation of a Limit Order Book (LOB) for high frequency trading in crypto exchanges Go · ⭐ 0 · forks 0 · updated 2023-12-18 · license MIT
  • DrAshBooth/PyLOB — Fully functioning fast Limit Order Book written in Python Python · ⭐ 0 · forks 0 · updated 2023-01-01 · license NOASSERTION
  • nkaz001/algotrading-example — algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex, binance futures, market making) Jupyter Notebook · ⭐ 323 · forks 0 · updated 2023-12-04 · license N/A
  • laurensa453/polymarket-btc-5m-clob-hedge-ladder-bot — Open-source Polymarket trading bot for BTC Up/Down 5-minute markets — Python CLOB bot with orderbook prediction, hedge ladder pair arbitrage & locked edge. Dry-run, live trading & paper dashboard. Python · ⭐ 22 · forks 0 · updated 2026-08-04 · license MIT
  • laurensa453/polymarket-btc-5m-hedge-ladder — Live Polymarket BTC 5m trading bot: gradient-boost orderbook prediction, hedge ladder strategy, locked pair edge. Python CLOB bot for UP/DOWN markets — 76.8% accuracy, 91.2% hedge completion. Dry-run + live trading, paper dashboard, open source. Python · ⭐ 21 · forks 0 · updated 2026-08-04 · license MIT
  • LabinatorSolutions/awesome-institutional-trading — The ultimate collection of institutional trading resources: order flow, market microstructure, options GEX, and algorithmic frameworks. N/A · ⭐ 21 · forks 0 · updated 2026-06-10 · license CC-BY-4.0
  • visualHFT/VisualHFT — VisualHFT is a WPF/C# desktop GUI that shows market microstructure in real time. You can track advanced limit‑order‑book dynamics and execution quality, then use its modular plugins to shape the analysis to your workflow. C# · ⭐ 0 · forks 0 · updated 2026-05-29 · license Apache-2.0
  • bigmacman1129/crypto-ai-trading-bot — Crypto liquidity detection & algorithmic trading bot. Order book analysis, stop-loss clusters, liquidity sweeps. Multi-exchange (Binance, Bybit, Kraken, OKX). Trading signals, quant research, market microstructure. JavaScript · ⭐ 0 · forks 0 · updated 2026-05-22 · license N/A
  • python-telegramBot/crypto-liquidity-ai-trading-bot — crypto trading bot liquidity order book market microstructure algorithmic trading quant Python Node.js websocket Binance crypto signals HFT order flow sweep detection depth analysis JavaScript · ⭐ 0 · forks 0 · updated 2026-05-13 · license N/A
  • Leo-Hawking/IMC-Prosperity-4-Review — IMC Prosperity 4 algorithmic trading retrospective: strategies, backtester, market microstructure analysis, and round-by-round research notes. Top 0.5% overall. Jupyter Notebook · ⭐ 0 · forks 0 · updated 2026-05-13 · license N/A
  • ozankenangungor/orderbook-replay-lab — Low-latency Limit Order Book research and deterministic replay engine. Rust · ⭐ 0 · forks 0 · updated 2026-04-29 · license MIT
  • aitradingbotspro/crypto-liquidity-ai-trading-bot — Crypto liquidity detection & algorithmic trading bot. Order book analysis, stop-loss clusters, liquidity sweeps. Multi-exchange (Binance, Bybit, Kraken, OKX). Trading signals, quant research, market microstructure. JavaScript · ⭐ 0 · forks 0 · updated 2026-03-12 · license N/A
  • suislanchez/polymarket-kalshi-weather-bot — Multi-platform prediction market trading bot: trades weather temperature markets on Kalshi (KXHIGH series) and Polymarket using 31-member GFS ensemble forecasts + BTC 5-min microstructure signals. Kelly criterion sizing, signal calibration, React dashboard. (Highest profits $1.8k) Python · ⭐ 0 · forks 0 · updated 2026-03-02 · license N/A
  • kpetridis24/lobsim — Ultra fast, deterministic L3 limit order book replay + paper-execution engine designed for market microstructure research and strategy prototyping. C++ · ⭐ 0 · forks 0 · updated 2026-02-03 · license Apache-2.0
  • Haohao-end/AI-Agent-Alpha-quantitative-trading-strategy — AI-Agent Alpha Quant Strategy: A-Share Sentiment Index — Daily 0–100 sentiment score from Tushare market microstructure signals + AI commentary for risk warnings and position management. Python · ⭐ 0 · forks 0 · updated 2026-01-06 · license N/A
  • TexasCoding/project-x-py — A high-performance Python SDK for the ProjectX Trading Platform Gateway API. This library enables developers to build sophisticated trading strategies and applications by providing comprehensive access to futures trading operations, historical market data, real-time streaming, technical analysis, and advanced market microstructure tools Python · ⭐ 0 · forks 0 · updated 2025-09-23 · license MIT

Execution and HFT

  • stefan-jansen/machine-learning-for-trading — Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution. N/A · ⭐ 19,220 · forks 0 · updated 2026-06-19 · license MIT
  • kungfu-systems/kungfu — Your agents don’t hand off the work. Kungfu keeps the same Work moving across Codex, Claude, OpenCode, and your own execution surface. C++ · ⭐ 4,463 · forks 1,283 · updated 2026-08-14 · license Apache-2.0
  • fremantle-industries/tai — A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine Elixir · ⭐ 498 · forks 84 · updated 2024-12-07 · license MIT
  • godzilla-foundation/godzilla-community — godzilla.dev is an open-source C++/Python infrastructure for self-hosted crypto funding rate arbitrage and market making, with ultra low-latency and enterprise private deployment C++ · ⭐ 359 · forks 0 · updated 2026-07-15 · license Apache-2.0
  • StratCraftsAI/NexusFix — A zero-alloc, compile-time hardened FIX engine built for sub-100ns execution. C++ · ⭐ 98 · forks 16 · updated 2026-07-21 · license MIT
  • bhftbootcamp/CryptoExchangeAPIs.jl — Cryptocurrency exchange API client for Julia Julia · ⭐ 0 · forks 0 · updated 2026-05-22 · license Apache-2.0
  • bhftbootcamp/TimeArrays.jl — Time series library for Julia Julia · ⭐ 0 · forks 0 · updated 2026-05-13 · license MIT
  • bhftbootcamp/CcyConv.jl — Currency conversion library for Julia Julia · ⭐ 0 · forks 0 · updated 2026-05-13 · license MIT
  • bhftbootcamp/LightweightCharts.jl — Julia wrapper for Lightweight Charts™ by TradingView Julia · ⭐ 0 · forks 0 · updated 2026-05-05 · license MIT
  • rburkholder/trade-frame — C++ 17 based library (with sample applications) for testing equities, futures, currencies, etfs & options based automated trading ideas using DTN IQFeed real time data feed and Interactive Brokers (IB TWS API) for trade execution. libtorch/lstm/cuda demo. Support for Alpaca & Phemex. Notifications via Telegram. C++ · ⭐ 0 · forks 0 · updated 2026-03-05 · license NOASSERTION
  • fremantle-industries/workbench — From Idea to Execution - Manage your trading operation across a distributed cluster Elixir · ⭐ 0 · forks 0 · updated 2023-03-06 · license MIT
  • fremantle-industries/prop — An open and opinionated trading platform using productive & familiar open source libraries and tools for strategy research, execution and operation. Elixir · ⭐ 0 · forks 0 · updated 2023-03-06 · license MIT
  • alpacahq/pylivetrader — Python live trade execution library with zipline interface. Python · ⭐ 0 · forks 0 · updated 2022-10-04 · license Apache-2.0
  • Markfans/cryptoquant-ai — CryptoQuant AI is an advanced, open-source quantitative trading platform designed to bridge the gap between algorithmic market execution and artificial intelligence. Built entirely on a modern Node.js, Vite, and TypeScript stack, this project provides a robust, highly responsive frontend dashboard paired with powerful automation capabilities. TypeScript · ⭐ 178 · forks 0 · updated 2026-05-01 · license MIT
  • automatedalgo/apex — Algorithmic trading strategies research and execution platform C++ · ⭐ 94 · forks 0 · updated 2026-07-12 · license LGPL-3.0
  • Thomvanoorschot/zigma — Zigma is an algorithmic trading framework built with the Zig programming language, leveraging an actor-based concurrency model. It aims to provide an efficient, low-latency system for algorithmic trading through components handling market data, strategy execution, order management, risk, and data persistence. Zig · ⭐ 103 · forks 0 · updated 2025-08-03 · license MIT
  • ghgr/HFT_Bitcoin — Analysis of High Frequency Trading on Bitcoin exchanges Jupyter Notebook · ⭐ 0 · forks 0 · updated 2017-08-21 · license N/A
  • klaush26/okx-trade-script-executor — A browser-based trading automation utility for OKX. Streamline algorithmic and manual crypto trades, configure custom API settings, and run a local execution suite. HTML · ⭐ 40 · forks 0 · updated 2026-08-07 · license GPL-3.0
  • Skyboi94/Quant-Trading-Projects — 11 hands-on quant trading projects in Python: backtesting, options pricing, stat arb, ML prediction, and execution algorithms. Jupyter Notebook · ⭐ 21 · forks 0 · updated 2026-07-08 · license N/A
  • dsinyakov/quant — Codera Quant is a Java framework for algorithmic trading strategies development, execution and backtesting via Interactive Brokers TWS API or other brokers API Java · ⭐ 184 · forks 0 · updated 2022-12-10 · license MIT

Brokerage & Exchange APIs (Execution Frameworks)

  • rediar/InteractiveBrokers-Algo-Trading-API — Java/MySQL real-time algorithmic trading using Interactive Brokers API Java · ⭐ 275 · forks 0 · updated 2023-06-12 · license Apache-2.0
  • aicheung/0dte-trader — Trade 0DTE options algorithmically using Interactive Brokers (IBKR) API. Python · ⭐ 95 · forks 0 · updated 2023-01-27 · license N/A
  • romanmichaelpaolucci/Quant_Dev — A solution to critical stages of algorithmic trading system development using Interactive Broker's Java API N/A · ⭐ 65 · forks 0 · updated 2020-01-03 · license N/A

Machine Learning for Trading

  • tensorflow/tensorflow — An Open Source Machine Learning Framework for Everyone C++ · ⭐ 195,786 · forks 0 · updated 2026-06-21 · license Apache-2.0
  • scikit-learn/scikit-learn — scikit-learn: machine learning in Python Python · ⭐ 66,378 · forks 0 · updated 2026-06-20 · license BSD-3-Clause
  • keras-team/keras — Deep Learning for humans Python · ⭐ 64,094 · forks 0 · updated 2026-06-18 · license Apache-2.0
  • lutzroeder/netron — Visualizer for neural network, deep learning and machine learning models JavaScript · ⭐ 33,101 · forks 0 · updated 2026-06-19 · license MIT
  • ChristosChristofidis/awesome-deep-learning — A curated list of awesome Deep Learning tutorials, projects and communities. N/A · ⭐ 28,462 · forks 0 · updated 2025-05-26 · license N/A
  • AI4Finance-Foundation/FinRL — FinRL®: Financial Reinforcement Learning. 🔥 Jupyter Notebook · ⭐ 16,004 · forks 3,463 · updated 2026-07-13 · license MIT
  • firmai/financial-machine-learning — A curated list of practical financial machine learning tools and applications. Python · ⭐ 8,651 · forks 0 · updated 2025-01-03 · license N/A
  • tensortrade-org/tensortrade — An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents. Python · ⭐ 6,350 · forks 0 · updated 2026-02-19 · license Apache-2.0
  • gorgonia/gorgonia — Gorgonia is a library that helps facilitate machine learning in Go. Go · ⭐ 5,919 · forks 0 · updated 2024-08-12 · license Apache-2.0
  • hudson-and-thames/mlfinlab — MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools. Python · ⭐ 4,839 · forks 0 · updated 2023-10-02 · license NOASSERTION
  • ZhengyaoJiang/PGPortfolio — PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf). Python · ⭐ 1,848 · forks 757 · updated 2021-10-09 · license GPL-3.0
  • PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading — Hands-On Machine Learning for Algorithmic Trading, published by Packt Jupyter Notebook · ⭐ 1,907 · forks 684 · updated 2023-01-18 · license MIT
  • Rachnog/Deep-Trading — Algorithmic trading with deep learning experiments OpenEdge ABL · ⭐ 1,462 · forks 686 · updated 2018-08-07 · license N/A
  • LastAncientOne/Deep_Learning_Machine_Learning_Stock — Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders. Jupyter Notebook · ⭐ 1,782 · forks 365 · updated 2024-03-01 · license MIT
  • mfrdixon/ML_Finance_Codes — Machine Learning in Finance: From Theory to Practice Book Jupyter Notebook · ⭐ 2,607 · forks 0 · updated 2020-06-13 · license N/A
  • TradeMaster-NTU/TradeMaster — TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning :fire: :zap: :rainbow: Jupyter Notebook · ⭐ 2,789 · forks 0 · updated 2025-06-04 · license Apache-2.0
  • asavinov/intelligent-trading-bot — Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering Python · ⭐ 1,843 · forks 0 · updated 2026-08-04 · license MIT
  • BlackArbsCEO/Adv_Fin_ML_Exercises — Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado] Jupyter Notebook · ⭐ 1,945 · forks 0 · updated 2022-12-08 · license MIT
  • cdipaolo/goml — On-line Machine Learning in Go (and so much more) Go · ⭐ 1,615 · forks 133 · updated 2022-07-15 · license MIT
  • rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy — Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data. Jupyter Notebook · ⭐ 2,322 · forks 0 · updated 2022-08-27 · license N/A

Financial NLP (Traditional)

  • alphanome-ai/sec-parser — Parse SEC EDGAR HTML documents into a tree of elements that correspond to the visual (semantic) structure of the document. Python · ⭐ 291 · forks 0 · updated 2026-06-25 · license MIT
  • vrunm/Text-Classification-Financial-Phrase-Bank — Built a sentiment analysis model to predict the sentiment of a Financial News article. A comparative study of different optimizers used for training was done. Python · ⭐ 33 · forks 0 · updated 2026-06-04 · license MIT
  • xwww333/Machine_Learning_NLP_Sentiment_Analysis — A machine learning app that analyzes the sentiment of financial analyst reports and detects potential bias in tone. It uses NLP techniques to classify report sentiment and assess whether analysts consistently lean positive or negative beyond expected norms. Jupyter Notebook · ⭐ 28 · forks 0 · updated 2025-10-03 · license N/A
  • asupraja3/nlp-finance-forecast — An End-to-End Machine Learning Pipeline that combines financial news sentiment analysis with historical stock price features to predict short-term market movements. Python · ⭐ 21 · forks 0 · updated 2025-11-03 · license N/A

Crypto Quant

  • freqtrade/freqtrade — Free, open source crypto trading bot Python · ⭐ 51,693 · forks 0 · updated 2026-06-20 · license GPL-3.0
  • ccxt/ccxt — A cryptocurrency trading API with more than 100 exchanges in JavaScript / TypeScript / Python / C# / PHP / Go / Java Python · ⭐ 42,995 · forks 0 · updated 2026-06-21 · license MIT
  • NoFxAiOS/nofx — Your AI trading terminal assistant for US stocks, commodities, forex, and crypto. Go · ⭐ 12,458 · forks 0 · updated 2026-06-11 · license AGPL-3.0
  • jnv/lists — The definitive list of lists (of lists) curated on GitHub and elsewhere N/A · ⭐ 11,275 · forks 0 · updated 2026-03-23 · license CC0-1.0
  • StockSharp/StockSharp — Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options). C# · ⭐ 10,155 · forks 0 · updated 2026-06-20 · license Apache-2.0
  • CryptoSignal/Crypto-Signal — Github.com/CryptoSignal - Trading & Technical Analysis Bot - 4,100+ stars, 1,100+ forks Python · ⭐ 5,614 · forks 1,339 · updated 2024-07-07 · license MIT
  • jesse-ai/jesse — An advanced crypto trading bot written in Python JavaScript · ⭐ 8,071 · forks 0 · updated 2026-06-20 · license MIT
  • JerBouma/FinanceDatabase — This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets. Python · ⭐ 7,926 · forks 0 · updated 2026-06-17 · license MIT
  • polakowo/vectorbt — The backtesting engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one. Python · ⭐ 7,988 · forks 0 · updated 2026-06-10 · license NOASSERTION
  • Drakkar-Software/OctoBot — Free open source crypto trading bot to automate AI, Grid, DCA and TradingView strategies on Binance, Hyperliquid and 15+ exchanges, with a simple interface. Python · ⭐ 6,089 · forks 0 · updated 2026-06-17 · license GPL-3.0
  • chrisleekr/binance-trading-bot — Automated Binance trading bot with pluggable strategies, historical backtesting, and a live dashboard TypeScript · ⭐ 5,540 · forks 0 · updated 2026-08-01 · license Apache-2.0
  • Superalgos/Superalgos — Free, open-source crypto trading bot, automated bitcoin / cryptocurrency trading software, algorithmic trading bots. Visually design your crypto trading bot, leveraging an integrated charting system, data-mining, backtesting, paper trading, and multi-server crypto bot deployments. JavaScript · ⭐ 5,531 · forks 0 · updated 2026-06-21 · license Apache-2.0
  • thrasher-corp/gocryptotrader — A cryptocurrency trading bot and framework supporting multiple exchanges written in Golang. Go · ⭐ 3,441 · forks 0 · updated 2026-06-18 · license MIT
  • Mathieu2301/TradingView-API — 📈 Get real-time stocks from TradingView JavaScript · ⭐ 3,916 · forks 0 · updated 2026-04-11 · license N/A
  • bmoscon/cryptofeed — Cryptocurrency Exchange Websocket Data Feed Handler Python · ⭐ 2,859 · forks 0 · updated 2026-02-01 · license NOASSERTION
  • atilaahmettaner/tradingview-mcp — TradingView MCP server — real-time market data, technical analysis, screeners & backtesting for Claude, ChatGPT, Cursor & any MCP client. Stocks, crypto, forex & futures across global exchanges. Hosted or self-host. Python · ⭐ 3,197 · forks 0 · updated 2026-06-21 · license MIT
  • maxme/bitcoin-arbitrage — Bitcoin arbitrage - opportunity detector Python · ⭐ 2,584 · forks 0 · updated 2024-10-20 · license MIT
  • OffcierCia/ultimate-defi-research-base — Here we collect and discuss the best DeFI & Blockchain researches and tools. Feel free to DM me on Twitter or open pool request. N/A · ⭐ 2,198 · forks 0 · updated 2026-03-14 · license NOASSERTION
  • nntaoli-project/goex — Cryptocurrency Exchange REST API SDK Wrapper Implemented With the golang, Supporting OKX, Binance Go · ⭐ 1,989 · forks 0 · updated 2026-06-01 · license MIT
  • bitcoinvsalts/node-binance-trader — 💰 Cryptocurrency Trading Strategy & Portfolio Management Development Framework for Binance. 🤖 TypeScript · ⭐ 1,223 · forks 370 · updated 2024-08-19 · license MIT

Data and Feeds

  • Fincept-Corporation/FinceptTerminal — FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment. C++ · ⭐ 27,213 · forks 0 · updated 2026-06-13 · license NOASSERTION
  • ranaroussi/yfinance — Download market data from Yahoo! Finance's API Python · ⭐ 24,382 · forks 0 · updated 2026-06-22 · license Apache-2.0
  • RomelTorres/alpha_vantage — A python wrapper for Alpha Vantage API for financial data. Python · ⭐ 4,841 · forks 0 · updated 2026-06-07 · license MIT
  • matplotlib/mplfinance — Financial Markets Data Visualization using Matplotlib Python · ⭐ 4,391 · forks 0 · updated 2024-08-08 · license NOASSERTION
  • shashankvemuri/Finance — 150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data Python · ⭐ 3,960 · forks 0 · updated 2026-03-26 · license MIT
  • financial-datasets/mcp-server — An MCP server for interacting with the Financial Datasets stock market API. Python · ⭐ 2,247 · forks 0 · updated 2025-06-05 · license MIT
  • FinMind/FinMind — Open Data, more than 50 financial data. 提供超過 50 個金融資料(台股為主)，每天更新 https://finmind.github.io/ HTML · ⭐ 2,653 · forks 0 · updated 2026-06-15 · license Apache-2.0
  • cuemacro/findatapy — Python library to download market data via Bloomberg, Eikon, Quandl, Yahoo etc. Python · ⭐ 2,062 · forks 0 · updated 2026-04-11 · license Apache-2.0
  • JoinQuant/jqdatasdk — 简单易用的量化金融数据包(easy utility for getting financial market data of China) Python · ⭐ 1,329 · forks 0 · updated 2026-01-29 · license MIT
  • simonlin1212/global-stock-data — US & HK stock market data for AI coding assistants — zero-auth, official sources. CBOE options with full Greeks + 0DTE flow, FINRA market-wide short volume, SEC EDGAR filing stream, and a free market-wide screener. 13 layers, 30+ endpoints, 11 sources. Every source labeled with its compliance tier. N/A · ⭐ 1,228 · forks 0 · updated 2026-07-24 · license Apache-2.0
  • defeat-beta/defeatbeta-api — An open-source alternative to Yahoo Finance's market data APIs with higher reliability. Python · ⭐ 674 · forks 0 · updated 2026-06-10 · license Apache-2.0
  • je-suis-tm/web-scraping — Detailed web scraping tutorials for dummies with financial data crawlers on Reddit WallStreetBets, CME (both options and futures), US Treasury, CFTC, LME, MacroTrends, SHFE and alternative data crawlers on Tomtom, BBC, Wall Street Journal, Al Jazeera, Reuters, Financial Times, Bloomberg, CNN, Fortune, The Economist Python · ⭐ 884 · forks 0 · updated 2022-02-01 · license Apache-2.0
  • piquette/finance-go — :bar_chart: Financial markets data library implemented in go. Go · ⭐ 783 · forks 0 · updated 2023-08-07 · license MIT
  • Finnhub-Stock-API/finnhub-python — Finnhub Python API Client. Finnhub API provides institutional-grade financial data to investors, fintech startups and investment firms. We support real-time stock price, global fundamentals, global ETFs holdings and alternative data. https://finnhub.io/docs/api Python · ⭐ 1,030 · forks 0 · updated 2026-04-22 · license Apache-2.0
  • jugaad-py/jugaad-data — Download live and historical data for Indian stock market Python · ⭐ 533 · forks 0 · updated 2026-03-16 · license N/A
  • hongtaocai/googlefinance — Python module to get real-time stock data from Google Finance API Python · ⭐ 826 · forks 0 · updated 2018-09-23 · license MIT
  • massive-com/mcp_massive — An MCP server for Massive.com Financial Market Data Python · ⭐ 373 · forks 0 · updated 2026-06-11 · license MIT
  • Alex2Yang97/yahoo-finance-mcp — This is a Model Context Protocol (MCP) server that provides comprehensive financial data from Yahoo Finance. It allows you to retrieve detailed information about stocks, including historical prices, company information, financial statements, options data, and market news. Python · ⭐ 332 · forks 0 · updated 2026-03-23 · license MIT
  • zwldarren/akshare-one-mcp — MCP server that provides access to Chinese stock market data using akshare-one Python · ⭐ 221 · forks 49 · updated 2026-03-14 · license MIT
  • twelvedata/twelvedata-python — Twelve Data Python Client - Financial data API & WebSocket Python · ⭐ 767 · forks 0 · updated 2026-07-27 · license MIT

Alternative Data & Web Scraping

  • mvkro1/Web-Scraper — A Python-based web scraper for extracting financial data from multiple sources. N/A · ⭐ 34 · forks 0 · updated 2025-02-03 · license N/A
  • dwallach1/Stocker — Financial Web Scraper & Sentiment Classifier Python · ⭐ 155 · forks 0 · updated 2020-10-02 · license N/A

Time-Series Databases & Data Infrastructure

  • kevinlawler/kerf1 — Kerf (Kerf1) is a columnar tick database and time-series language for Linux/OSX/BSD/iOS/Android. It is written in C and natively speaks JSON and SQL. Kerf can be used for trading platforms, feedhandlers, low-latency networking, high-volume analysis of realtime and historical data, logfile processing, and more. C · ⭐ 547 · forks 0 · updated 2024-09-03 · license N/A
  • kevinlawler/kerf — Kerf (Kerf2) is a columnar tick database and time-series language for Linux/OSX/BSD/iOS/Android. It is written in C++ and natively speaks JSON and SQL. Kerf can be used for trading platforms, feedhandlers, low-latency networking, high-volume analysis of realtime and historical data, logfile processing, and more. C++ · ⭐ 38 · forks 0 · updated 2026-02-27 · license BSD-2-Clause

Research Papers & Articles

  • Maximum extractable value (mev) mitigation approaches in ethereum and layer-2 chains: A comprehensive survey — Z Alipanahloo, AS Hafid, K Zhang - IEEE Access, 2024 - ieeexplore.ieee.org. … MEV arises when miners or validators manipulate transaction ordering (eg… MEV. This paper presents a comprehensive survey of MEV mitigation techniques as applied to both Ethereum’…
  • Mev on ethereum: A policy analysis — M Barczentewicz - ICLE White Paper, 2023 - papers.ssrn.com. … regarding what we know today about MEV, but perhaps even more importantly, … by MEV extraction on the Ethereum blockchain.The paper is intended both for those unfamiliar with MEV …
  • Mev ecosystem evolution from ethereum 1.0 — Y Chaurasia, P Desai, S Gujar - arXiv preprint arXiv:2406.13585, 2024 - arxiv.org. … While extracted, MEV might not always be high; there have been instances of MEV revenue … Consider Figure 3, which shows Ethereum blocks where MEV extracted by ordering …
  • Exploiting ethereum after “the merge”: The interplay between pos and mev strategies — D Mancino, A Leporati, M Viviani… - CEUR WORKSHOP …, 2023 - boa.unimib.it. … and the introduction of these new MEV-related players in the Ethereum ecosystem has been … in detail Ethereum and its PoS consensus mechanism; Section 3 describes current MEV on-…
  • The future of mev — J Burian - arXiv preprint arXiv:2404.04262, 2024 - arxiv.org. … 1 on Ethereum Research, unveiling its potential to revolutionize the Ethereum blockchain’s … anism poised to redefine how the Ethereum protocol distributes the value associated with …
  • Maximal extractable value: Current understanding, categorization, and open research questions — V Gramlich, D Jelito, J Sedlmeir - Electronic Markets, 2024 - Springer. … definition of MEV (Section “Defining maximalextractable value”) from the references we … in which it can manifest (Section “Defining maximal extractable value”). We discuss our results in …
  • Maximal extractable value (mev) protection on a dag — D Malkhi, P Szalachowski - arXiv preprint arXiv:2208.00940, 2022 - arxiv.org. … The original work called the measure miner extractable value, which was later extended by maximal extractable value (MEV) [33] and blockchain extractable value (BEV) [36], to include …
  • Towards a theory of maximal extractable value i: Constant function market makers — K Kulkarni, T Diamandis, T Chitra - arXiv preprint arXiv:2207.11835, 2022 - arxiv.org. … Maximal Extractable Value (MEV) refers to excess value captured by miners (or validators) from users in a cryptocurrency network. This excess value … when the maximum price impact …
  • Maximal extractable value in decentralized finance: Taxonomy, detection, and mitigation — H Materwala, SM Naik, A Taha, TA Abed… - IEEE Transactions …, 2025 - ieeexplore.ieee.org. … , insert, or remove transactions to extract value, often at the expense of others. This extracted value is known as the Maximal Extractable Value (MEV). MEV causes financial losses and …
  • Unity is strength: A formalization of cross-domain maximal extractable value — A Obadia, A Salles, L Sankar, T Chitra… - arXiv preprint arXiv …, 2021 - arxiv.org. … whether there exists extractable value that depends on the … the definitions of Extractable and Maximal Extractable Value, … Note that we define the extractable value for a sequence of …
  • Flash loan arbitrage bot — R Kanojia - Available at SSRN 4447220, 2023 - papers.ssrn.com. … paper describes how to use flash loans to leverage arbitrage possibilities in DEXs. To highlight the efficiency of their strategy, the authors offer a case study of exploiting an arbitrage …
  • How Do Flash Loans Affect Market Liquidity? — S Li - Available at SSRN 5932835, 2025 - papers.ssrn.com. … Our evidence shows that scaling up cross-venue arbitrage via flash loans is associated with deeper liquidity and, at larger sizes, slightly better execution quality, while leverage-seeking …
  • Limits to Arbitrage in Decentralized Finance — S Balasubramaniam - Available at SSRN 6079846, 2025 - papers.ssrn.com. … We document that flash-loan arbitrage exhibits substantially higher concentration than … : flash-loan arbitrage is substantially more concentrated than traditional capital-funded arbitrage. …
  • Entwicklung eines arbitrage-bots unter verwendung von flash loans — P Baumann - 2023 - monami.hs-mittweida.de. … an arbitrage bot was developed that uses so-called flash loans … Sushiswap on Ethereum for arbitrage options. After executing … The largest potential profit identified by the arbitrage bot …
  • An exploration of novel trading and arbitrage methods within decentralised finance — S Byrne - scss.tcd.ie. … with the loan being paid back within the transaction. Flash loans become useful for arbitrage … capital through a flash loan, complete a token swap between exchanges, pay back the …
  • Bitcoin and portfolio diversification: A portfolio optimization approach — W Bakry, A Rashid, S Al-Mohamad… - Journal of Risk and …, 2021 - mdpi.com. … This study investigates the performance of Bitcoin as a diversifier under different constraining portfolio optimization frameworks. The study employs different constraining optimization …
  • Cryptocurrency portfolio optimization using Value-at-Risk measure — P Hrytsiuk, T Babych… - … Conference on Strategies …, 2019 - atlantis-press.com. … portfolio of financial assets is one of its instruments. In this paper, the formation of cryptocurrency investment portfolio … By changing the proportion of certain assets in a portfolio, it can be …
  • Crypto-assets portfolio optimization under the omega measure — JG Castro, EAH Tito, LET Brandão… - The Engineering …, 2020 - Taylor & Francis. … isn’t the case for crypto-assets. We develop a portfolio optimization model based on the Omega … model, and apply this to four crypto-asset investment portfolios by means of a numerical …
  • Portfolio optimization in the era of digital financialization using cryptocurrencies — Y Ma, F Ahmad, M Liu, Z Wang - Technological forecasting and social …, 2020 - Elsevier. … the addition of multiple cryptocurrencies in a portfolio provides enhanced results for diversification, and Ethereum provides a better diversification opportunity as compared to Bitcoin. …
  • Risk-based portfolio optimization in the cryptocurrency world — T Burggraf - Available at SSRN 3454764, 2019 - papers.ssrn.com. … In the next step, we apply our risk-based portfolio optimization strategies to our cryptocurrency portfolio8. Input parameters are estimated using a rolling window of 252 daily …
  • QuantCode-Bench: A Benchmark for Evaluating the Ability of Large Language Models to Generate Executable Algorithmic Trading Strategies — Authors: Alexey Khoroshilov, Alexey Chernysh, Orkhan Ekhtibarov, Nini Kamkia, Dmitry Zmitrovich. Large language models have demonstrated strong performance on general-purpose programming tasks, yet their ability to generate executable algorithmic trading strategies remains underexplored. Unlike standard code benchmarks, trading-strategy generation requires simultaneous mastery of domain-spec... · published 2026-04-16
  • FinMCP-Bench: Benchmarking LLM Agents for Real-World Financial Tool Use under the Model Context Protocol — Authors: Jie Zhu, Yimin Tian, Boyang Li, Kehao Wu, Zhongzhi Liang, Junhui Li, Xianyin Zhang, Lifan Guo, Feng Chen, Yong Liu, Chi Zhang. This paper introduces \textbf{FinMCP-Bench}, a novel benchmark for evaluating large language models (LLMs) in solving real-world financial problems through tool invocation of financial model context protocols. FinMCP-Bench contains 613 samples spanning 10 main scenarios and 33 sub-scenarios, feat... · published 2026-03-26
  • QuantaAlpha: An Evolutionary Framework for LLM-Driven Alpha Mining — Authors: Jun Han, Shuo Zhang, Wei Li, Yifan Dong, Tu Hu, Yumo Zhu, Xiaomin Yu, Xin Guo, Zhaowei Liu, Kunyi Wang, Jingping Liu, Tianyi Jiang, Ruichuan An, Sen Hu, Zhi Yang, Ronghao Che, Huacan Wang. Financial markets are noisy and non-stationary, making alpha mining highly sensitive to backtest noise and regime shifts. While recent agentic frameworks improve automation, they often lack controllable multi-round search and reliable reuse of validated experience. To address these challenges, we... · published 2026-02-06
  • FinDeepForecast: A Live Multi-Agent System for Benchmarking Deep Research Agents in Financial Forecasting — Authors: Xiangyu Li, Xuan Yao, Guohao Qi, Fengbin Zhu, Kelvin J. L. Koa, Xiang Yao Ng, Ziyang Liu, Xingyu Ni, Chang Liu, Yonghui Yang, Yang Zhang, Wenjie Wang, Fuli Feng, Chao Wang, Huanbo Luan, Xiaofen Xing, Xiangmin Xu, Tat-Seng Chua, Ke-Wei Huang. Deep Research (DR) Agents powered by advanced Large Language Models (LLMs) have fundamentally shifted the paradigm for completing complex research tasks. Yet, a comprehensive and live evaluation of their forecasting performance on real-world, research-oriented tasks in high-stakes domains (e.g., ... · published 2026-01-08
  • StockMem: An Event-Reflection Memory Framework for Stock Forecasting — Authors: He Wang, Wenyilin Xiao, Songqiao Han, Hailiang Huang. Stock price prediction is challenging due to market volatility and its sensitivity to real-time events. While large language models (LLMs) offer new avenues for text-based forecasting, their application in finance is hindered by noisy news data and the lack of explicit answers in text. General-pu... · published 2025-12-02
  • FinRpt: Dataset, Evaluation System and LLM-based Multi-agent Framework for Equity Research Report Generation — Authors: Song Jin, Shuqi Li, Shukun Zhang, Rui Yan. While LLMs have shown great success in financial tasks like stock prediction and question answering, their application in fully automating Equity Research Report generation remains uncharted territory. In this paper, we formulate the Equity Research Report (ERR) Generation task for the first time... · published 2025-11-10
  • RETuning: Upgrading Inference-Time Scaling for Stock Movement Prediction with Large Language Models — Authors: Xueyuan Lin, Cehao Yang, Ye Ma, Ming Li, Rongjunchen Zhang, Yang Ni, Xiaojun Wu, Chengjin Xu, Jian Guo, Hui Xiong. Recently, large language models (LLMs) have demonstrated outstanding reasoning capabilities on mathematical and coding tasks. However, their application to financial tasks-especially the most fundamental task of stock movement prediction-remains underexplored. We study a three-class classificatio... · published 2025-10-24
  • FinSearchComp: Towards a Realistic, Expert-Level Evaluation of Financial Search and Reasoning — Authors: Liang Hu, Jianpeng Jiao, Jiashuo Liu, Yanle Ren, Zhoufutu Wen, Kaiyuan Zhang, Xuanliang Zhang, Xiang Gao, Tianci He, Fei Hu, Yali Liao, Zaiyuan Wang, Chenghao Yang, Qianyu Yang, Mingren Yin, Zhiyuan Zeng, Ge Zhang, Xinyi Zhang, Xiying Zhao, Zhenwei Zhu, Hongseok Namkoong, Wenhao Huang, Yuwen Tang. Search has emerged as core infrastructure for LLM-based agents and is widely viewed as critical on the path toward more general intelligence. Finance is a particularly demanding proving ground: analysts routinely conduct complex, multi-step searches over time-sensitive, domain-specific data, maki... · published 2025-09-16
  • Trading-R1: Financial Trading with LLM Reasoning via Reinforcement Learning — Authors: Yijia Xiao, Edward Sun, Tong Chen, Fang Wu, Di Luo, Wei Wang. Developing professional, structured reasoning on par with human financial analysts and traders remains a central challenge in AI for finance, where markets demand interpretability and trust. Traditional time-series models lack explainability, while LLMs face challenges in turning natural-language... · published 2025-09-14
  • QuantHarness: Price-Driven Multi-Agent LLMs for High-Frequency Trading — Authors: Fei Xiong, Xiang Zhang, Aosong Feng, Siqi Sun, Chenyu You. Recent advances in Large Language Models (LLMs) have shown remarkable capabilities in financial reasoning and market understanding. Multi-agent LLM frameworks such as TradingAgent and FINMEM augment these models to long-horizon investment tasks by leveraging fundamental and sentiment-based inputs... · published 2025-09-12
  • AlphaAgents: Large Language Model based Multi-Agents for Equity Portfolio Constructions — Authors: Tianjiao Zhao, Jingrao Lyu, Stokes Jones, Harrison Garber, Stefano Pasquali, Dhagash Mehta. The field of artificial intelligence (AI) agents is evolving rapidly, driven by the capabilities of Large Language Models (LLMs) to autonomously perform and refine tasks with human-like efficiency and adaptability. In this context, multi-agent collaboration has emerged as a promising approach, en... · published 2025-08-15
  • ContestTrade: A Multi-Agent Trading System Based on Internal Contest Mechanism — Authors: Rui Sun, Li Zhao, Zuoyou Jiang, Bo Yang, Yuxiao Bai, Mengting Chen, Jing Li, Zuo Bai. In financial trading, large language model (LLM)-based agents demonstrate significant potential, but their decisions can be sensitive to noisy and non-stationary market information. We propose ContestTrade, a multi-agent trading system with an internal competitive mechanism inspired by institutio... · published 2025-08-01
  • Machine Learning Enhanced Multi-Factor Quantitative Trading: A Cross-Sectional Portfolio Optimization Approach with Bias Correction — Authors: Yimin Du. Rolling-window factor pipelines for Chinese A-share markets contain a subtle but costly flaw: daily price-move limits (+/-10% main-board, +/-20% STAR/ChiNext) render a fraction of closing prices non-executable, yet standard implementations ingest these values before any row-filtering runs. The co... · published 2025-06-02
  • Can LLM-based Financial Investing Strategies Outperform the Market in Long Run? — Authors: Weixian Waylon Li, Hyeonjun Kim, Mihai Cucuringu, Tiejun Ma. Large Language Models (LLMs) have recently been leveraged for asset pricing tasks and stock trading applications, enabling AI agents to generate investment decisions from unstructured financial data. However, most evaluations of LLM timing-based investing strategies are conducted on narrow timefr... · published 2025-05-11
  • LLMs Meet Finance: Fine-Tuning Foundation Models for the Open FinLLM Leaderboard — Authors: Varun Rao, Youran Sun, Mahendra Kumar, Tejas Mutneja, Agastya Mukherjee, Haizhao Yang. This paper investigates the application of large language models (LLMs) to financial tasks. We fine-tuned foundation models using the Open FinLLM Leaderboard as a benchmark. Building on Qwen2.5 and Deepseek-R1, we employed techniques including supervised fine-tuning (SFT), direct preference optim... · published 2025-04-17
  • TradingAgents: Multi-Agents LLM Financial Trading Framework — Authors: Yijia Xiao, Edward Sun, Di Luo, Wei Wang. Significant progress has been made in automated problem-solving using societies of agents powered by large language models (LLMs). In finance, efforts have largely focused on single-agent systems handling specific tasks or multi-agent frameworks independently gathering data. However, the multi-ag... · published 2024-12-28
  • Financial Statement Analysis with Large Language Models — Authors: Alex Kim, Maximilian Muhn, Valeri Nikolaev. We investigate whether large language models (LLMs) can successfully perform financial statement analysis in a way similar to a professional human analyst. We provide standardized and anonymous financial statements to GPT4 and instruct the model to analyze them to determine the direction of firms... · published 2024-07-25
  • FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making — Authors: Yangyang Yu, Zhiyuan Yao, Haohang Li, Zhiyang Deng, Yupeng Cao, Zhi Chen, Jordan W. Suchow, Rong Liu, Zhenyu Cui, Zhaozhuo Xu, Denghui Zhang, Koduvayur Subbalakshmi, Guojun Xiong, Yueru He, Jimin Huang, Dong Li, Qianqian Xie. Large language models (LLMs) have demonstrated notable potential in conducting complex tasks and are increasingly utilized in various financial applications. However, high-quality sequential financial investment decision-making remains challenging. These tasks require multiple interactions with a... · published 2024-07-09
  • A Reflective LLM-based Agent to Guide Zero-shot Cryptocurrency Trading — Authors: Yuan Li, Bingqiao Luo, Qian Wang, Nuo Chen, Xu Liu, Bingsheng He. The utilization of Large Language Models (LLMs) in financial trading has primarily been concentrated within the stock market, aiding in economic and financial decisions. Yet, the unique opportunities presented by the cryptocurrency market, noted for its on-chain data's transparency and the critic... · published 2024-06-27
  • A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist — Authors: Wentao Zhang, Lingxuan Zhao, Haochong Xia, Shuo Sun, Jiaze Sun, Molei Qin, Xinyi Li, Yuqing Zhao, Yilei Zhao, Xinyu Cai, Longtao Zheng, Xinrun Wang, Bo An. Financial trading is a crucial component of the markets, informed by a multimodal information landscape encompassing news, prices, and Kline charts, and encompasses diverse tasks such as quantitative trading and high-frequency trading with various assets. While advanced AI techniques like deep le... · published 2024-02-28
  • FinBen: A Holistic Financial Benchmark for Large Language Models — Authors: Qianqian Xie, Weiguang Han, Zhengyu Chen, Ruoyu Xiang, Xiao Zhang, Yueru He, Mengxi Xiao, Dong Li, Yongfu Dai, Duanyu Feng, Yijing Xu, Haoqiang Kang, Ziyan Kuang, Chenhan Yuan, Kailai Yang, Zheheng Luo, Tianlin Zhang, Zhiwei Liu, Guojun Xiong, Zhiyang Deng, Yuechen Jiang, Zhiyuan Yao, Haohang Li, Yangyang Yu, Gang Hu, Jiajia Huang, Xiao-Yang Liu, Alejandro Lopez-Lira, Benyou Wang, Yanzhao Lai, Hao Wang, Min Peng, Sophia Ananiadou, Jimin Huang. LLMs have transformed NLP and shown promise in various fields, yet their potential in finance is underexplored due to a lack of comprehensive evaluation benchmarks, the rapid development of LLMs, and the complexity of financial tasks. In this paper, we introduce FinBen, the first extensive open-s... · published 2024-02-20
  • FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design — Authors: Yangyang Yu, Haohang Li, Zhi Chen, Yuechen Jiang, Yang Li, Denghui Zhang, Rong Liu, Jordan W. Suchow, Khaldoun Khashanah. Recent advancements in Large Language Models (LLMs) have exhibited notable efficacy in question-answering (QA) tasks across diverse domains. Their prowess in integrating extensive web knowledge has fueled interest in developing LLM-based autonomous agents. While LLMs are efficient in decoding hum... · published 2023-11-23
  • FinanceBench: A New Benchmark for Financial Question Answering — Authors: Pranab Islam, Anand Kannappan, Douwe Kiela, Rebecca Qian, Nino Scherrer, Bertie Vidgen. FinanceBench is a first-of-its-kind test suite for evaluating the performance of LLMs on open book financial question answering (QA). It comprises 10,231 questions about publicly traded companies, with corresponding answers and evidence strings. The questions in FinanceBench are ecologically vali... · published 2023-11-20
  • Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models — Authors: Alejandro Lopez-Lira, Yuehua Tang. We document the capability of large language models (LLMs) like ChatGPT to predict stock market reactions from news headlines without direct financial training. Using post-knowledge-cutoff headlines, GPT-4 captures initial market responses, achieving approximately 90% portfolio-day hit rates for ... · published 2023-04-15
  • BloombergGPT: A Large Language Model for Finance — Authors: Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David Rosenberg, Gideon Mann. The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering. Large Language Models (LLMs) have been shown to be effective on a variety of tasks; however, no LLM specialized for the f... · published 2023-03-30
  • Deep Learning Statistical Arbitrage — Authors: Jorge Guijarro-Ordonez, Markus Pelger, Greg Zanotti. Statistical arbitrage exploits temporal price differences between similar assets. We develop a unifying conceptual framework for statistical arbitrage and a novel data driven solution. First, we construct arbitrage portfolios of similar assets as residual portfolios from conditional latent asset ... · published 2021-06-08
  • FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance — Authors: Xiao-Yang Liu, Hongyang Yang, Qian Chen, Runjia Zhang, Liuqing Yang, Bowen Xiao, Christina Dan Wang. As deep reinforcement learning (DRL) has been recognized as an effective approach in quantitative finance, getting hands-on experiences is attractive to beginners. However, to train a practical DRL trading agent that decides where to trade, at what price, and what quantity involves error-prone an... · published 2020-11-19
  • Adversarial Attacks on Deep Algorithmic Trading Policies — Authors: Yaser Faghan, Nancirose Piazza, Vahid Behzadan, Ali Fathi. Deep Reinforcement Learning (DRL) has become an appealing solution to algorithmic trading such as high frequency trading of stocks and cyptocurrencies. However, DRL have been shown to be susceptible to adversarial attacks. It follows that algorithmic trading DRL agents may also be compromised by ... · published 2020-10-22
  • AAMDRL: Augmented Asset Management with Deep Reinforcement Learning — Authors: Eric Benhamou, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay, Jamal Atif. Can an agent learn efficiently in a noisy and self adapting environment with sequential, non-stationary and non-homogeneous observations? Through trading bots, we illustrate how Deep Reinforcement Learning (DRL) can tackle this challenge. Our contributions are threefold: (i) the use of contextual... · published 2020-09-30
  • Deep Stock Predictions — Authors: Akash Doshi, Alexander Issa, Puneet Sachdeva, Sina Rafati, Somnath Rakshit. Forecasting stock prices can be interpreted as a time series prediction problem, for which Long Short Term Memory (LSTM) neural networks are often used due to their architecture specifically built to solve such problems. In this paper, we consider the design of a trading strategy that performs po... · published 2020-06-08

Academic Resources

  • facebook/prophet — Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. Python · ⭐ 20,264 · forks 0 · updated 2026-05-08 · license MIT
  • hugo2046/QuantsPlaybook — 量化研究-券商金工研报复现 Jupyter Notebook · ⭐ 5,399 · forks 0 · updated 2026-05-08 · license N/A
  • gopherdata/gophernotes — The Go kernel for Jupyter notebooks and nteract. Go · ⭐ 3,965 · forks 0 · updated 2023-11-03 · license MIT
  • nickmccullum/algorithmic-trading-python — The repository for freeCodeCamp's YouTube course, Algorithmic Trading in Python Jupyter Notebook · ⭐ 2,845 · forks 0 · updated 2024-06-20 · license N/A
  • yhilpisch/py4fi2nd — Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch. Jupyter Notebook · ⭐ 2,232 · forks 0 · updated 2025-06-06 · license NOASSERTION
  • cerlymarco/MEDIUM_NoteBook — Repository containing notebooks of my posts on Medium Jupyter Notebook · ⭐ 2,139 · forks 0 · updated 2024-09-22 · license MIT
  • rsvp/fecon235 — Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics Jupyter Notebook · ⭐ 1,274 · forks 0 · updated 2023-01-20 · license NOASSERTION
  • LechGrzelak/QuantFinanceBook — Quantitative Finance book Python · ⭐ 920 · forks 0 · updated 2025-04-14 · license BSD-3-Clause
  • PacktPublishing/Python-for-Finance-Cookbook — Python for Finance Cookbook, published by Packt Jupyter Notebook · ⭐ 794 · forks 0 · updated 2026-03-02 · license N/A
  • yhilpisch/py4at — Jupyter Notebooks and code for the book Python for Algorithmic Trading (O'Reilly) by Yves Hilpisch. Jupyter Notebook · ⭐ 838 · forks 0 · updated 2023-10-09 · license NOASSERTION
  • 0b01/tectonicdb — Database for L2 orderbook Rust · ⭐ 749 · forks 0 · updated 2024-01-25 · license NOASSERTION
  • LechGrzelak/Computational-Finance-Course — Here you will find materials for the course of Computational Finance Python · ⭐ 562 · forks 0 · updated 2024-03-01 · license BSD-3-Clause
  • yhilpisch/dawp — Jupyter Notebooks and code for Derivatives Analytics with Python (Wiley Finance) by Yves Hilpisch. Jupyter Notebook · ⭐ 639 · forks 0 · updated 2021-02-22 · license NOASSERTION
  • yhilpisch/aiif — Jupyter Notebooks and code for the book Artificial Intelligence in Finance (O'Reilly) by Yves Hilpisch. Jupyter Notebook · ⭐ 395 · forks 0 · updated 2024-01-14 · license NOASSERTION
  • YichengYang-Ethan/oracle3 — Prediction-market trading engine — Wang Transform pricing on 291K+ contracts; paper-traded across Kalshi · Polymarket · Solana DFlow (Jito bundles) · 633 tests Python · ⭐ 256 · forks 0 · updated 2026-05-08 · license Apache-2.0
  • robcarver17/systematictradingexamples — Examples of code related to book www.systematictrading.org and blog qoppac.blogspot.com Python · ⭐ 483 · forks 0 · updated 2020-07-22 · license GPL-2.0
  • industry-report/huatai-finengi-report — :books: 华泰金工研究报告 N/A · ⭐ 280 · forks 0 · updated 2023-02-28 · license N/A
  • MarcosCarreira/DermanPapers — Notebooks that replicate original quantitative finance papers from Emanuel Derman Jupyter Notebook · ⭐ 529 · forks 0 · updated 2017-10-21 · license N/A
  • rmbell09-lang/tradesight — Self-hosted AI trading strategy lab — paper trading, overnight strategy tournaments, 15+ technical indicators Python · ⭐ 92 · forks 0 · updated 2026-06-23 · license N/A
  • proompteng/bilig — Formula workbooks for Node services: edit inputs, recalculate formulas, read outputs, persist WorkPaper JSON, and expose MCP tools. TypeScript · ⭐ 35 · forks 19 · updated 2026-08-10 · license MIT

Interview / Learning

  • eslazarev/purged-cross-validation — scikit-learn-compatible time-series cross-validation: purging, embargo, combinatorial purged CV, and deflated Sharpe ratios Python · ⭐ 20 · forks 0 · updated 2026-06-16 · license MIT
  • Nixtla/mlforecast — Scalable machine 🤖 learning for time series forecasting. Python · ⭐ 0 · forks 0 · updated 2026-05-26 · license Apache-2.0
  • go-training/training — Learning Golang one day HTML · ⭐ 0 · forks 0 · updated 2025-11-08 · license MIT
  • pskrunner14/trading-bot — Stock Trading Bot using Deep Q-Learning Jupyter Notebook · ⭐ 0 · forks 0 · updated 2023-12-03 · license MIT
  • rocketlaunchr/dataframe-go — DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration Go · ⭐ 0 · forks 0 · updated 2022-04-02 · license NOASSERTION
  • tudorelu/tudorials — A repsitory hosting all the code written for my tutorials. HTML · ⭐ 0 · forks 0 · updated 2020-08-04 · license N/A
  • pa-m/sklearn — bits of sklearn ported to Go #golang Go · ⭐ 0 · forks 0 · updated 2020-07-11 · license MIT
  • laikasinjason/deep-q-learning-trading-system-on-hk-stocks-market — Deep q learning on determining buy/sell signal and placing orders Python · ⭐ 0 · forks 0 · updated 2019-05-21 · license N/A
  • shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading — Using deep actor-critic model to learn best strategies in pair trading Python · ⭐ 0 · forks 0 · updated 2017-05-18 · license N/A
  • kh-kim/stock_market_reinforcement_learning — This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient. Python · ⭐ 0 · forks 0 · updated 2016-12-23 · license N/A
  • carlos8f/zenbrain — A framework for machine-learning bots CSS · ⭐ 0 · forks 0 · updated 2016-08-29 · license N/A

LLM / AI Agents for Finance

  • OpenBB-finance/OpenBB — Open Data Platform for analysts, quants and AI agents. Python · ⭐ 71,848 · forks 7,398 · updated 2026-07-30 · license NOASSERTION
  • microsoft/qlib — Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process. Python · ⭐ 44,901 · forks 0 · updated 2026-04-22 · license MIT
  • virattt/dexter — An autonomous agent for deep financial research TypeScript · ⭐ 27,140 · forks 0 · updated 2026-06-15 · license N/A
  • AI4Finance-Foundation/FinGPT — FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace. Jupyter Notebook · ⭐ 20,552 · forks 0 · updated 2026-06-01 · license MIT
  • HKUDS/AI-Trader — "AI-Trader: 100% Fully-Automated Agent-Native Trading" Python · ⭐ 19,946 · forks 0 · updated 2026-06-11 · license N/A
  • microsoft/RD-Agent — Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report Python · ⭐ 13,562 · forks 0 · updated 2026-06-15 · license MIT
  • ValueCell-ai/valuecell — ValueCell is a community-driven, multi-agent platform for financial applications. Python · ⭐ 10,812 · forks 0 · updated 2026-03-09 · license Apache-2.0
  • AI4Finance-Foundation/FinRobot — FinRobot: An Open-Source AI Agent Platform for Financial Analysis using LLMs 🚀 🚀 🚀 Jupyter Notebook · ⭐ 7,336 · forks 0 · updated 2026-05-10 · license Apache-2.0
  • Nixtla/nixtla — TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀. Jupyter Notebook · ⭐ 3,932 · forks 0 · updated 2026-06-12 · license NOASSERTION
  • kungfu-systems/kungfu — Kungfu - Agent Work Ledger C++ · ⭐ 3,881 · forks 0 · updated 2026-07-08 · license Apache-2.0
  • LLMQuant/quant-wiki — We are committed to the open-sourcing quantitative knowledge, aiming to bridge the information gap between the domestic and international quantitative finance industries. 我们致力于量化知识的开源与汉化，打破国内外量化金融行业信息差。 N/A · ⭐ 3,774 · forks 0 · updated 2026-04-16 · license N/A
  • Y-Research-SBU/QuantAgent — Official Repository for QuantAgent HTML · ⭐ 2,749 · forks 0 · updated 2026-05-08 · license MIT
  • chrisworsey55/atlas-gic — ATLAS by General Intelligence Capital — Self-improving AI trading agents using Karpathy-style autoresearch Python · ⭐ 1,972 · forks 0 · updated 2026-05-27 · license NOASSERTION
  • onestardao/WFGY — WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg. Jupyter Notebook · ⭐ 1,759 · forks 0 · updated 2026-06-21 · license NOASSERTION
  • mnemox-ai/tradememory-protocol — Decision audit trail + persistent memory for AI trading agents. Outcome-weighted recall, SHA-256 tamper detection, 17 MCP tools. Python · ⭐ 1,401 · forks 0 · updated 2026-07-14 · license MIT
  • The-FinAI/PIXIU — This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI). Jupyter Notebook · ⭐ 879 · forks 121 · updated 2025-03-04 · license MIT
  • alpacahq/alpaca-mcp-server — Alpaca’s official MCP Server lets you trade stocks, ETFs, crypto, and options, run data analysis, and build strategies in plain English directly from your favorite LLM tools and IDEs Python · ⭐ 890 · forks 0 · updated 2026-07-23 · license MIT
  • aliyun/qwen-dianjin — Qwen DianJin: LLMs for the Financial Industry by Alibaba Cloud（通义点金：阿里云金融大模型） Python · ⭐ 586 · forks 66 · updated 2026-07-06 · license N/A
  • ariadng/metatrader-mcp-server — Model Context Protocol (MCP) to enable AI LLMs to trade using MetaTrader platform Python · ⭐ 685 · forks 0 · updated 2026-03-28 · license MIT
  • FinStep-AI/ContestTrade — A Multi-Agent Trading System Based on Internal Contest Mechanism Python · ⭐ 678 · forks 0 · updated 2025-12-22 · license Apache-2.0

Utilities

  • pandas-dev/pandas — Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more Python · ⭐ 49,034 · forks 0 · updated 2026-06-21 · license BSD-3-Clause
  • akfamily/akshare — AKShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库 Python · ⭐ 22,008 · forks 3,446 · updated 2026-08-13 · license MIT
  • nautechsystems/nautilus_trader — Production-grade Rust-native trading engine with deterministic event-driven architecture Rust · ⭐ 24,066 · forks 0 · updated 2026-06-21 · license LGPL-3.0
  • quantopian/zipline — Zipline, a Pythonic Algorithmic Trading Library Python · ⭐ 19,894 · forks 0 · updated 2024-02-13 · license Apache-2.0
  • plotly/plotly.py — The interactive graphing library for Python :sparkles: Python · ⭐ 18,613 · forks 0 · updated 2026-06-19 · license MIT
  • waditu/tushare — TuShare is a utility for crawling historical data of China stocks Python · ⭐ 15,156 · forks 0 · updated 2024-03-13 · license BSD-3-Clause
  • scipy/scipy — SciPy library main repository Python · ⭐ 14,763 · forks 0 · updated 2026-06-21 · license BSD-3-Clause
  • go-echarts/go-echarts — 🎨 The adorable charts library for Golang. Go · ⭐ 7,626 · forks 0 · updated 2026-05-11 · license MIT
  • lballabio/QuantLib — The QuantLib C++ library C++ · ⭐ 7,274 · forks 0 · updated 2026-06-18 · license NOASSERTION
  • bukosabino/ta — Technical Analysis Library using Pandas and Numpy Jupyter Notebook · ⭐ 5,098 · forks 0 · updated 2026-03-18 · license MIT
  • google/tf-quant-finance — High-performance TensorFlow library for quantitative finance. Python · ⭐ 5,408 · forks 0 · updated 2026-02-12 · license Apache-2.0
  • quickfix/quickfix — QuickFIX C++ Fix Engine Library C++ · ⭐ 1,973 · forks 879 · updated 2026-05-20 · license NOASSERTION
  • xlwings/xlwings — xlwings is a Python library that makes it easy to call Python from Excel and vice versa. It works with Excel on Windows and macOS as well as with Google Sheets and Excel on the web. Python · ⭐ 3,363 · forks 0 · updated 2026-06-17 · license NOASSERTION
  • andredumas/techan.js — A visual, technical analysis and charting (Candlestick, OHLC, indicators) library built on D3. JavaScript · ⭐ 2,435 · forks 524 · updated 2020-10-02 · license MIT
  • montanaflynn/stats — A well tested and comprehensive Golang statistics library package with no dependencies. Go · ⭐ 3,021 · forks 0 · updated 2026-05-02 · license MIT
  • pmorissette/ffn — ffn - a financial function library for Python Python · ⭐ 2,607 · forks 0 · updated 2026-03-21 · license MIT
  • domokane/FinancePy — A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives. Jupyter Notebook · ⭐ 3,013 · forks 0 · updated 2026-06-16 · license GPL-3.0
  • ta4j/ta4j — A Java library for technical analysis. Java · ⭐ 2,445 · forks 0 · updated 2026-06-06 · license NOASSERTION
  • massive-com/client-python — The official Python client library for the Massive.com REST and WebSocket API. Python · ⭐ 1,496 · forks 357 · updated 2026-07-09 · license MIT
  • alkaline-ml/pmdarima — A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function. Python · ⭐ 1,734 · forks 252 · updated 2025-11-17 · license MIT

Source Lists

  • wilsonfreitas/awesome-quant — A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance) HTML · ⭐ 28,743 · forks 3,846 · updated 2026-08-14 · license N/A
  • wilsonfreitas/awesome-quant — A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance) HTML · ⭐ 26,939 · forks 0 · updated 2026-06-21 · license N/A
  • paperswithbacktest/awesome-systematic-trading — A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading. Python · ⭐ 13,281 · forks 1,614 · updated 2025-01-22 · license N/A
  • je-suis-tm/quant-trading — Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD Python · ⭐ 10,544 · forks 1,864 · updated 2026-06-20 · license Apache-2.0
  • je-suis-tm/quant-trading — Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD Python · ⭐ 9,983 · forks 0 · updated 2024-04-14 · license Apache-2.0
  • paperswithbacktest/awesome-systematic-trading — A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading. Python · ⭐ 8,291 · forks 0 · updated 2025-01-22 · license N/A
  • georgezouq/awesome-ai-in-finance — 🔬 A curated list of awesome LLMs & deep learning strategies & tools in financial market. N/A · ⭐ 6,396 · forks 773 · updated 2026-08-04 · license CC0-1.0
  • thuquant/awesome-quant — 中国的Quant相关资源索引 N/A · ⭐ 5,558 · forks 1,016 · updated 2026-08-10 · license MIT
  • wangzhe3224/awesome-systematic-trading — A curated list of insanely awesome libraries, packages and resources for systematic trading. Crypto, Stock, Futures, Options, CFDs, FX, and more | 量化交易 | 量化投资 HTML · ⭐ 4,875 · forks 638 · updated 2026-08-09 · license MIT
  • georgezouq/awesome-ai-in-finance — 🔬 A curated list of awesome LLMs & deep learning strategies & tools in financial market. N/A · ⭐ 6,010 · forks 0 · updated 2026-06-01 · license CC0-1.0
  • thuquant/awesome-quant — 中国的Quant相关资源索引 N/A · ⭐ 5,341 · forks 0 · updated 2026-05-17 · license MIT
  • grananqvist/Awesome-Quant-Machine-Learning-Trading — Quant/Algorithm trading resources with an emphasis on Machine Learning N/A · ⭐ 3,948 · forks 694 · updated 2025-05-21 · license N/A
  • wangzhe3224/awesome-systematic-trading — A curated list of insanely awesome libraries, packages and resources for systematic trading. Crypto, Stock, Futures, Options, CFDs, FX, and more | 量化交易 | 量化投资 HTML · ⭐ 4,339 · forks 0 · updated 2026-06-19 · license MIT
  • grananqvist/Awesome-Quant-Machine-Learning-Trading — Quant/Algorithm trading resources with an emphasis on Machine Learning N/A · ⭐ 3,675 · forks 0 · updated 2025-05-21 · license N/A
  • 0voice/Awesome-QuantDev-Learn — 本仓库面向所有对量化分析或开发感兴趣的量化交易从业者，提供系统性学习量化开发的技术路线，从数据获取、策略开发、回测系统到实盘部署。 N/A · ⭐ 1,040 · forks 140 · updated 2025-07-04 · license NOASSERTION
  • 0voice/Awesome-QuantDev-Learn — 本仓库面向所有对量化分析或开发感兴趣的量化交易从业者，提供系统性学习量化开发的技术路线，从数据获取、策略开发、回测系统到实盘部署。 N/A · ⭐ 859 · forks 0 · updated 2025-07-04 · license NOASSERTION
  • leoncuhk/awesome-quant-ai — A curated list of awesome resources for quantitative investment and trading strategies focusing on artificial intelligence and machine learning applications in finance. Jupyter Notebook · ⭐ 558 · forks 110 · updated 2026-08-09 · license Apache-2.0
  • SoYuCry/awesome-quant-interview — 量化金融八股文 | 55道高频考点 × 详细解答 | 数学统计 · Python/C++ · 因子与Alpha策略 · 机器学习/深度学习 | 面试 + 学习两用指南 N/A · ⭐ 592 · forks 81 · updated 2026-08-03 · license MIT
  • SoYuCry/awesome-quant-interview — 量化金融八股文 | 55道高频考点 × 详细解答 | 数学统计 · Python/C++ · 因子与Alpha策略 · 机器学习/深度学习 | 面试 + 学习两用指南 N/A · ⭐ 359 · forks 0 · updated 2026-06-17 · license MIT
  • leoncuhk/awesome-quant-ai — A curated list of awesome resources for quantitative investment and trading strategies focusing on artificial intelligence and machine learning applications in finance. Jupyter Notebook · ⭐ 356 · forks 0 · updated 2026-04-29 · license Apache-2.0

Candidates to Review

  • sindresorhus/awesome — 😎 Awesome lists about all kinds of interesting topics N/A · ⭐ 477,522 · forks 0 · updated 2026-06-02 · license CC0-1.0
  • vinta/awesome-python — An opinionated list of Python frameworks, libraries, tools, and resources Python · ⭐ 304,041 · forks 0 · updated 2026-06-12 · license NOASSERTION
  • pytorch/pytorch — Tensors and Dynamic neural networks in Python with strong GPU acceleration Python · ⭐ 100,916 · forks 0 · updated 2026-06-21 · license NOASSERTION
  • fffaraz/awesome-cpp — A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff. N/A · ⭐ 71,892 · forks 0 · updated 2026-05-31 · license MIT
  • virattt/ai-hedge-fund — An AI Hedge Fund Team Python · ⭐ 60,384 · forks 0 · updated 2026-06-17 · license MIT
  • koala73/worldmonitor — Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface TypeScript · ⭐ 57,717 · forks 0 · updated 2026-06-20 · license NOASSERTION
  • ray-project/ray — Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads. Python · ⭐ 42,953 · forks 0 · updated 2026-06-21 · license Apache-2.0
  • vnpy/vnpy — 基于Python的开源量化交易平台开发框架 Python · ⭐ 41,902 · forks 0 · updated 2026-05-17 · license MIT
  • pola-rs/polars — Extremely fast Query Engine for DataFrames, written in Rust Rust · ⭐ 38,836 · forks 0 · updated 2026-06-21 · license MIT
  • bayandin/awesome-awesomeness — A curated list of awesome awesomeness Ruby · ⭐ 33,500 · forks 0 · updated 2024-06-02 · license N/A
  • numpy/numpy — The fundamental package for scientific computing with Python. Python · ⭐ 32,226 · forks 0 · updated 2026-06-20 · license NOASSERTION
  • shiyu-coder/Kronos — Kronos: A Foundation Model for the Language of Financial Markets Python · ⭐ 30,813 · forks 0 · updated 2026-04-13 · license MIT
  • bbfamily/abu — 阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构 Python · ⭐ 18,131 · forks 4,664 · updated 2026-01-24 · license GPL-3.0
  • gocolly/colly — Elegant Scraper and Crawler Framework for Golang Go · ⭐ 25,336 · forks 0 · updated 2026-06-18 · license Apache-2.0
  • sympy/sympy — A computer algebra system written in pure Python Python · ⭐ 14,862 · forks 5,422 · updated 2026-08-13 · license NOASSERTION
  • google-research/timesfm — TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting. Python · ⭐ 24,718 · forks 0 · updated 2026-06-20 · license Apache-2.0
  • timescale/timescaledb — A time-series database for high-performance real-time analytics packaged as a Postgres extension C · ⭐ 22,945 · forks 0 · updated 2026-06-21 · license NOASSERTION
  • emirpasic/gods — GoDS (Go Data Structures) - Sets, Lists, Stacks, Maps, Trees, Queues, and much more Go · ⭐ 17,451 · forks 1,825 · updated 2025-03-12 · license NOASSERTION
  • greyireland/algorithm-pattern — Algorithm Patterns — the most scientific way to practice, the fastest path to an offer. You deserve it~ 算法模板，最科学的刷题方式，最快速的刷题路径，你值得拥有~ Go · ⭐ 15,463 · forks 2,572 · updated 2026-05-30 · license MIT
  • QuantConnect/Lean — Lean Algorithmic Trading Engine by QuantConnect (Python, C#) C# · ⭐ 20,001 · forks 0 · updated 2026-06-19 · license Apache-2.0

AI Models & Datasets

Contribution Guidelines

Pull requests are welcome.

Good additions should be:

  • relevant to quantitative research, trading research, or market structure
  • useful for research, reproducibility, education, or infrastructure
  • documented well enough for others to evaluate
  • actively maintained or historically important

Please avoid pure signal-selling projects, generic trading bots, or low-quality forks.

Disclaimer

This repository is for research and education only. Nothing here is financial advice.

Last auto-generated: 2026-08-14 04:16 UTC