Quantitative Frameworks by Programming Language & Their GitHub Repositories

This list is compiled by TheQuantHackers. A meticulously curated collection of outstanding quantitative finance libraries, packages, and resources. For learning and communication purposes only. Copyright belongs to the original authors.

Languages

• Python - The most popular language for quantitative finance, with rich data analysis, machine learning libraries, and financial toolkits
• R - The go-to language for statistical analysis, with unique advantages in financial modeling and risk analysis
• Matlab - Widely used in financial engineering and numerical computing, especially suited for matrix operations
• Julia - An emerging language designed for high-performance numerical computing, gaining popularity in quantitative finance
• Java - The standard choice for enterprise applications, ideal for building large-scale trading systems
• JavaScript - Primarily used for financial data visualization and web-based trading interfaces
• Haskell - A functional programming language with advantages in complex financial product modeling
• Scala - Combines object-oriented and functional programming, suitable for building high-concurrency trading systems
• Ruby - Known for its simplicity, mainly used for rapid prototyping and small trading systems
• Elixir/Erlang - Excels in building fault-tolerant and distributed trading systems
• Golang - Known for high performance and concurrency features, suitable for developing HFT systems
• CPP - The best language for developing low-latency trading systems, widely used in high-frequency trading
• CSharp - The go-to for the Microsoft technology stack, ideal for developing quantitative trading systems on Windows
• Rust - A next-generation systems programming language offering memory safety alongside performance
• Frameworks - Cross-language quantitative finance frameworks providing complete trading and analysis solutions
• Reproducing Research, Training & Books - Code implementations of learning resources and classic research

Selection Guide

1. Beginner Learning

   • Python: Best choice for beginners, rich learning resources, mature ecosystem
   • R: Suitable for learners focusing on statistical analysis and risk modeling

2. Professional Development

   • C++: For ultra-low-latency HFT systems
   • Java: Enterprise-level trading platform development
   • Golang: Modern high-concurrency trading systems

3. Specific Use Cases

   • Julia: High-performance numerical computing
   • JavaScript: Web trading interface development
   • Rust: When both performance and safety are required

4. Research-Oriented

   • Python/R: Data analysis and strategy research
   • Matlab: Financial engineering research
   • Julia: Algorithm optimization research

Technology Stack Trends

• Python ecosystem continues to dominate quantitative finance
• Julia emerging in high-performance computing
• Rust gradually replacing C++ in systems-level development
• Go language gaining traction in microservices architecture

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Python

Numerical Libraries & Data Structures

• numpy - NumPy is the fundamental package for scientific computing in Python.
• scipy - SciPy (pronounced "Sigh Pie") is an open-source Python-based ecosystem for mathematics, science, and engineering.
• pandas - pandas is an open-source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for Python.
• polars - Polars is a blazingly fast DataFrame library for manipulating structured data.
• quantdsl - A domain-specific language for quantitative analysis in finance and trading.
• statistics - Python's built-in basic statistical computation library.
• sympy - SymPy is a Python library for symbolic mathematics.
• pymc3 - Probabilistic programming in Python: Bayesian modeling and probabilistic machine learning based on Theano.
• modelx - Reimagining spreadsheets as formula-based objects interoperable with pandas.
• ArcticDB - High-performance data store for time series and tick data.

Financial Tools & Pricing

• OpenBB Terminal - An investment research terminal for everyone.
• Fincept Terminal - Financial asset research terminal powered by advanced data and AI.
• PyQL - Python port of QuantLib.
• pyfin - Basic option pricing in Python. Archived project
• vollib - A Python library for calculating option prices, implied volatility, and Greeks.
• QuantPy - A quantitative finance framework in Python.
• Finance-Python - Python financial toolkit.
• ffn - A financial function library.
• pynance - A lightweight Python library for assembling and analyzing financial data.
• tia - Toolkit for integration and analysis.
• hasura/base-python-dash - Hasura quickstart for deploying the Dash framework. Dash is based on Flask, Plotly.js, and React.js, ideal for building data visualization apps in pure Python.
• hasura/base-python-bokeh - Hasura quickstart for data visualization with the bokeh library.
• pysabr - Python implementation of the SABR model.
• FinancePy - A Python library focused on pricing and risk management of financial derivatives, including fixed income, equities, FX, and credit derivatives.
• gs-quant - Goldman Sachs' quantitative finance Python toolkit.
• willowtree - Python implementation of willow tree lattices for derivative pricing.
• financial-engineering - Monte Carlo methods applied to financial engineering projects in Python.
• optlib - An option pricing library in Python.
• tf-quant-finance - High-performance quantitative finance library based on TensorFlow.
• Q-Fin - A Python library for mathematical finance.
• Quantsbin - Toolkit for pricing and plotting vanilla option prices, Greeks, and more.
• finoptions - A Python library fully implementing the R package fOptions and parts of fExoticOptions for pricing various options.
• pypme - A tool for computing the Public Market Equivalent (PME).
• AbsBox - A Python library for modeling cash flows of structured products such as asset-backed securities (ABS) and mortgage-backed securities (MBS).
• Intrinsic-Value-Calculator - A stock intrinsic value calculator based on discounted cash flow (DCF) analysis.
• Kelly-Criterion - Python implementation of the Kelly Criterion for portfolio position sizing.
• rateslib - A fixed income library for pricing bonds, treasury futures, and derivatives such as IRS, cross-currency, and FX swaps.
• fypy - A library for pricing vanilla and exotic options for research and development, with a focus on models beyond Black-Scholes and market data calibration.

Indicators

• pandas_talib - Technical analysis indicators implemented with Pandas.
• finta - Pandas implementation of common financial technical analysis indicators.
• Tulipy - A financial technical analysis indicator library (Python wrapper for tulipindicators).
• lppls - A Python fitting module for the Log-Periodic Power Law Singularity (LPPLS) model.
• talipp - An incremental technical analysis indicator library for Python.
• streaming_indicators - A Python library for computing technical analysis indicators on streaming data.

Trading & Backtesting

• skfolio - A portfolio optimization Python library based on scikit-learn, providing a unified interface and sklearn-compatible tools for building, tuning, and cross-validating portfolio models.
• Investing algorithm framework - A framework for developing, backtesting, and deploying automated trading algorithms.
• QSTrader - QSTrader backtesting simulation engine.
• Blankly - Fully integrated backtesting, paper trading, and live deployment.
• TA-Lib - Python wrapper for TA-Lib (http://ta-lib.org/).
• zipline - A Pythonic algorithmic trading library.
• zipline-reloaded - A fork of Zipline, a Pythonic algorithmic trading library.
• QuantSoftware Toolkit - An open-source Python-based software framework for supporting portfolio construction and management.
• quantitative - A quantitative finance and backtesting library.
• analyzer - A Python framework for real-time financial and backtesting trading strategies.
• bt - A flexible Python backtesting library.
• backtrader - A Python library for backtesting trading strategies.
• pythalesians - A Python library for backtesting trading strategies, charting, seamlessly downloading market data, and analyzing market patterns.
• pybacktest - A vectorized backtesting framework using Python/pandas, making backtesting simpler.
• pyalgotrade - A Python algorithmic trading library.
• basana - An asynchronous event-driven algorithmic trading framework in Python, focused on cryptocurrencies.
• tradingWithPython - A collection of functions and classes for quantitative trading.
• Pandas TA - An easy-to-use Python 3 Pandas extension with 115+ indicators for building custom strategies.
• ta - A technical analysis library using Pandas (Python).
• algobroker - An execution engine for algorithmic trading.
• pysentosa - Python API for the Sentosa trading system.
• finmarketpy - A Python library for backtesting trading strategies and analyzing financial markets.
• binary-martingale - A computer program for automated binary option trading using the Martingale strategy.
• fooltrader - A project that uses big data technology to uniformly analyze the entire market.
• zvt - Provides a unified, extensible way using SQL and pandas to record data, compute factors, select stocks, backtest, and trade in real time, with clear visualization of the entire process.
• pylivetrader - A zipline-compatible live trading library.
• pipeline-live - Zipline pipeline functionality for live trading using IEX data.
• zipline-extensions - Zipline extensions and adaptations for the QuantRocket environment.
• moonshot - A vectorized backtesting and trading engine based on Pandas, adapted for QuantRocket.
• PyPortfolioOpt - Portfolio optimization in Python, including classic efficient frontier and advanced methods.
• Eiten - An open-source toolkit by Tradytics containing various portfolio algorithms (minimum variance, maximum Sharpe ratio, genetic algorithm portfolios, etc.).
• riskparity.py - Fast and scalable risk parity portfolio design using TensorFlow 2.0.
• mlfinlab - Implements techniques from Marcos Lopez de Prado's "Advances in Financial Machine Learning" (feature engineering, financial data structures, meta-labeling).
• pyqstrat - A fast, scalable, and transparent Python library for quantitative strategy backtesting.
• NowTrade - A Python library for backtesting technical/mechanical strategies on stocks and forex.
• pinkfish - A backtesting and spreadsheet library for security analysis.
• aat - An asynchronous algorithmic trading engine.
• Backtesting.py - Backtest trading strategies with Python.
• catalyst - A Python algorithmic trading library for crypto assets.
• quantstats - A portfolio analysis library for quantitative research (Python).
• qtpylib - A Pythonic algorithmic trading library http://qtpylib.io.
• Quantdom - A Python-based framework for backtesting trading strategies and market analysis [with GUI].
• freqtrade - A free, open-source cryptocurrency trading bot.
• algorithmic-trading-with-python - Examples and resources from "Algorithmic Trading with Python".
• DeepDow - Portfolio optimization using deep learning.
• Qlib - Microsoft's AI-oriented quantitative investment platform, covering data processing, model training, backtesting, and supporting alpha discovery, risk modeling, portfolio optimization, and order execution.
• machine-learning-for-trading - Code and resources for "Machine Learning for Algorithmic Trading".
• AlphaPy - An automated machine learning [AutoML] library supporting Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost.
• jesse - An advanced cryptocurrency trading bot written in Python.
• rqalpha - An extensible, replaceable Python algorithmic backtesting and trading framework supporting multiple financial products.
• FinRL-Library - A deep reinforcement learning library for quantitative finance. NeurIPS 2020.
• bulbea - A deep learning-based Python library for stock market prediction and modeling.
• ib_nope - An automated trading system for the NOPE strategy based on IBKR TWS.
• OctoBot - An open-source cryptocurrency trading bot supporting HFT, arbitrage, technical analysis, and social trading with an advanced web interface.
• bta-lib - A Pandas-based technical analysis library for backtesting and quantitative analysis.
• Stock-Prediction-Models - Integrated stock prediction models using various machine learning and deep learning methods, including trading bots and simulations.
• TuneTA - Optimizes technical indicators using distance correlation to align with user-defined target features such as next-day returns.
• AutoTrader - A Python-based platform for developing automated trading systems, including backtesting, optimization, and live trading.
• fast-trade - A backtesting library focused on portability and performance.
• qf-lib - Provides high-quality tools for quantitative finance analysis, covering trading strategies and backtesting.
• tda-api - A Python client for TDAmeritrade for retrieving real-time/historical quotes and placing orders.
• vectorbt - A powerful toolkit for backtesting, algorithmic trading, and research.
• Lean - QuantConnect's open-source .NET/Mono/Python algorithmic trading engine.
• fast-trade - A low-code backtesting library based on pandas and technical indicators.
• pysystemtrade - Robert Carver's open-source backtesting trading engine, implementing the strategy framework from his book "Systematic Trading" and further expanded on his blog.
• pytrendseries - Detects time series trends, drawdowns, fixed-window maximum drawdowns, and underwater time.
• PyLOB - A high-performance Limit Order Book written in Python.
• PyBroker - A Python framework for algorithmic trading with machine learning.
• OctoBot Script - A quantitative framework for creating cryptocurrency strategies, supporting backtesting, optimization, and live trading.
• hftbacktest - A backtesting tool for HFT and market-making strategies handling limit orders, queue positions, and latency, using tick-level and order book data.
• vnpy - VeighNa, an open-source quantitative trading system development framework based on Python.
• Intelligent Trading Bot - Automated trading signal generation and execution based on machine learning and feature engineering.
• fastquant - Easily backtest investment strategies in Python with just three lines of code.
• nautilus_trader - A high-performance event-driven backtesting and live algorithmic trading platform.
• YABTE - Yet Another (Python) BackTesting Engine.
• Trading Strategy - A research, backtesting, live trading, and investment management framework for decentralized finance (DeFi).
• Hikyuu - A Python/C++ based open-source high-performance quantitative framework providing complete trading system components for easy combination and reuse.

Risk Analysis

• QuantLibRisks - Fast risk computation based on QuantLib.
• XAD - Automatic differentiation (AAD) library.
• pyfolio - Portfolio and risk analysis.
• empyrical - Common financial risk and performance metrics.
• fecon235 - Computational tools for financial economics, including mixed Gaussian models, Boltzmann adaptive portfolios, etc.
• finance - Financial risk computation, emphasizing ease of use through classes and operator overloading.
• qfrm - Quantitative financial risk management: OOP risk measurement, management, and visualization for financial instruments and portfolios.
• visualize-wealth - Portfolio construction and quantitative analysis.
• VisualPortfolio - A tool for visualizing portfolio performance.
• universal-portfolios - A collection of online portfolio selection algorithms.
• FinQuant - Tools for portfolio management, analysis, and optimization.
• Empyrial - Portfolio risk and performance analysis, and return forecasting.
• risktools - Risk tools for crude oil and refined products trading scenarios, partially implementing R's PerformanceAnalytics.
• Riskfolio-Lib - A Python library for portfolio optimization and quantitative asset allocation.
• empyrical-reloaded - A fork of empyrical for common financial risk and performance metrics.
• pyfolio-reloaded - A fork of pyfolio for portfolio and risk analysis.
• fortitudo.tech - Portfolio optimization and stress testing using CVaR (Conditional Value at Risk) and entropy pooling.

Factor Analysis

• alphalens - Performance analysis of predictive alpha factors.
• alphalens-reloaded - A fork for performance analysis of predictive (alpha) stock factors.
• Spectre - GPU-accelerated factor analysis library and backtesting tool.

Sentiment Analysis

• Asset News Sentiment Analyzer - News sentiment analysis and report generation for financial assets and securities using GPT models.

Quantitative Research Environment

• Jupyter Quant - A Dockerized Jupyter quantitative research environment pre-loaded with statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, and more.

Time Series

• ARCH - ARCH models in Python.
• statsmodels - A Python module for data exploration, statistical model estimation, and statistical testing.
• dynts - A Python package for time series analysis and manipulation.
• PyFlux - A Python library for time series modeling and inference (frequentist and Bayesian).
• tsfresh - Automatic extraction of relevant features from time series.
• hasura/quandl-metabase - Hasura quickstart for visualizing Quandl time series datasets with Metabase.
• Facebook Prophet - A high-quality forecasting tool for time series data with multiple seasonality and linear or non-linear growth.
• tsmoothie - A vectorized time series smoothing and outlier detection Python library.
• pmdarima - A statistical library providing a Python equivalent of R's auto.arima function.
• gluon-ts - A Python toolkit for probabilistic time series modeling.
• functime - A large-scale time series machine learning library using Polars for parallel feature extraction and panel data forecasting.

Calendars

• exchange_calendars - A collection of stock exchange trading calendars.
• bizdays - Business (trading) day calculation and tools.
• pandas_market_calendars - Exchange calendars integrated with pandas for quantitative trading applications.

Data Sources

• yfinance - Yahoo! Finance market data downloader (faster than Pandas Datareader).
• findatapy - A Python library for downloading market data from Bloomberg, Quandl, Yahoo, and other sources.
• googlefinance - A Python module for retrieving real-time stock data from the Google Finance API.
• yahoo-finance - A Python module for fetching stock data from Yahoo! Finance.
• pandas-datareader - Reads data from many sources (Google/Yahoo/FRED/OECD/Fama-French/World Bank/Eurostat, etc.) into pandas data structures with caching.
• pandas-finance - A high-level API for financial data access and analysis.
• pyhoofinance - Fast batch queries of multiple stocks from Yahoo Finance with typed data for analysis.
• yfinanceapi - A Python wrapper for the Yahoo! Finance API.
• yql-finance - Quickly fetch stock closing prices using YQL (Yahoo Query Language).
• ystockquote - Fetch stock quote data from Yahoo Finance.
• wallstreet - Real-time stock and option data.
• stock_extractor - A general stock data extraction tool.
• Stockex - A Python wrapper for the Yahoo! Finance API.
• finsymbols - Fetch stock symbols and related information for S&P 500, AMEX, NYSE, and NASDAQ.
• FRB - A Python client for the FRED® API.
• inquisitor - A Python interface for accessing the Econdb.com API.
• yfi - A YQL (Yahoo! Query Language) library.
• chinesestockapi - A Python API for retrieving Chinese stock price data.
• exchange - Fetch current exchange rates.
• ticks - A command-line tool for fetching stock data.
• pybbg - A Python interface for the Bloomberg COM API.
• ccy - A currency Python module.
• tushare - A tool for retrieving historical and real-time Chinese stock market data.
• jsm - Retrieve Japanese stock market data.
• cn_stock_src - A tool for fetching Chinese stock fundamental data from different sources.
• coinmarketcap - A Python API for CoinMarketCap.
• after-hours - Retrieve pre-market and after-hours stock prices.
• bronto-python - A Python wrapper for the Bronto API.
• pytdx - A Python interface to TDX (Tongdaxin) market data servers for retrieving real-time Chinese stock quotes.
• pdblp - A simple interface integrating pandas with the Bloomberg Open API.
• tiingo - A Python wrapper for accessing the Tiingo data platform (including daily prices, real-time news).
• iexfinance - A Python interface for retrieving real-time and historical stock and other financial data from IEX.
• pyEX - A Python interface for IEX with pandas support, streaming data, paid data, financial data, and technical indicators.
• alpaca-trade-api - A Python interface for retrieving real-time/historical price data and executing trades from the Alpaca API.
• metatrader5 - An API connector for the MetaTrader 5 terminal.
• akshare - An elegant and simple financial data interface library for Python enthusiasts.
• yahooquery - An unofficial Yahoo Finance Python interface.
• investpy - A Python tool for retrieving financial data from Investing.com!
• yliveticker - Real-time market data streaming via the Yahoo Finance websocket.
• bbgbridge - A convenient Python wrapper for the Bloomberg Desktop API.
• alpha_vantage - A Python wrapper for the Alpha Vantage API for financial data.
• FinanceDataReader - An open-source financial data reader supporting US, Korean, Japanese, Chinese, Vietnamese, and other markets.
• pystlouisfed - A Python client for the Federal Reserve Bank of St. Louis APIs (FRED, ALFRED, GeoFRED, FRASER).
• python-bcb - A Python interface for the Brazilian Central Bank web services.
• market-prices - Generates meaningful OHLCV datasets using information from exchange-calendars.
• tardis-python - A Python wrapper for Tardis.dev high-frequency cryptocurrency market data.
• lake-api - A Python wrapper for Crypto Lake high-frequency cryptocurrency market data.
• tessa - Quickly fetches financial asset prices (based on yfinance and pycoingecko) with search and Symbol class.
• pandaSDMX - A Python library implementing SDMX 2.1 (ISO 17369:2013) for statistical data and metadata exchange, widely used by national statistical agencies, central banks, and international organizations.
• cif - A Python package containing several composite indicators that integrate multidimensional relationships among economic indicators.
• finagg - Python implementations of several free financial APIs, tools for aggregating historical data into SQL databases, and converting aggregated data into features suitable for analysis or AI/ML.
• FinanceDatabase - A database of 300,000+ security symbols, including stocks, ETFs, funds, indices, currencies, cryptocurrencies, and money market instruments.
• Trading Strategy - Download price data from decentralized exchanges and lending protocols (DeFi).
• datamule-python - A toolkit for SEC data processing, combining datamule endpoints.

Excel Integration

• xlwings - Makes Excel and Python work together.
• openpyxl - A library for reading and writing Excel 2007 xlsx/xlsm files.
• xlrd - A Python library for extracting data from Excel files.
• xlsxwriter - Write files in Excel 2007+ XLSX format.
• xlwt - A library for creating spreadsheets compatible with MS Excel 97/2000/XP/2003 XLS files.
• DataNitro - DataNitro provides full Python-Excel integration, including custom functions (UDFs). A trial is available, but a license is required.
• xlloop - An open-source framework for implementing Excel custom functions (UDFs) on a centralized server (function server).
• expy - A plugin that enables executing Python code directly in Excel spreadsheets and defining new Excel functions.
• pyxll - An Excel plugin that extends Excel functionality with just Python code.

Visualization

• D-Tale - A visual analysis tool for pandas DataFrames and xarray Datasets.
• mplfinance - Financial data visualization and analysis based on matplotlib.
• finplot - A high-performance, easy-to-use financial visualization tool.
• finvizfinance - A Python library for Finviz data analysis.
• market-analy - Interactive chart analysis using market-prices and bqplot.
• QuantInvestStrats - A Python analysis library for Quantitative Investment Strategies (QIS), used for financial data visualization and backtesting reports.

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R

Numerical Libraries & Data Structures

• xts - eXtensible Time Series: Provides a unified interface for different time series classes in R.
• data.table - An extension of data.frame enabling fast aggregation, fast ordered joins, and column add/update/delete operations without copying on large datasets.
• sparseEigen - Sparse principal component analysis.
• TSdbi - Provides a common interface for time series databases.
• tseries - Time series analysis and computational finance.
• zoo - S3 infrastructure for regular and irregular time series (Z's Ordered Observations).
• tis - Functions and S3 classes for time-indexed and time-indexed sequences compatible with FAME frequencies.
• tfplot - Tools for fast processing and plotting of time series data.
• tframe - Core functions for time series method programming, independent of various time series representations.

Data Sources

• IBrokers - Access to Interactive Brokers TWS API through R.
• Rblpapi - An R interface for accessing the Bloomberg API.
• Quandl - Import financial data directly into R.
• Rbitcoin - A unified cryptocurrency exchange API interface (bitstamp, kraken, btce, bitmarket, etc.).
• GetTDData - Download and aggregate Brazilian government bond data from the Tesouro Direto website.
• GetHFData - Download and aggregate high-frequency trading data for Brazilian financial products from Bovespa FTP.
• Reddit WallstreetBets API - API for retrieving the top 50 most discussed stocks and their sentiment from r/wallstreetbets daily.
• td - Access to the twelvedata API for stock and (digital and fiat) currency data.
• rbcb - An R interface for accessing the Brazilian Central Bank web services.
• rb3 - A collection of functions for downloading and parsing data from the Brazilian exchange (B3).
• simfinapi - Makes data from SimFin easily accessible in R.
• tidyfinance - Transforms raw financial data into tidy format, including date conversion, size factors, etc., for subsequent research.

Financial Tools & Pricing

• RQuantLib - RQuantLib connects GNU R with the QuantLib library.
• quantmod - A quantitative financial modeling framework.
• Rmetrics - Rmetrics is the leading open-source solution for quantitative finance education and training.
  • fAsianOptions - EBM and Asian option valuation.
  • fAssets - Financial asset analysis and modeling.
  • fBasics - Markets and basic statistics.
  • fBonds - Bond and interest rate models.
  • fExoticOptions - Exotic option valuation.
  • fOptions - Basic option pricing and evaluation.
  • fPortfolio - Portfolio selection and optimization.
• portfolio - Stock portfolio analysis.
• sparseIndexTracking - Sparse index tracking portfolio design.
• covFactorModel - Covariance matrix estimation via factor models.
• riskParityPortfolio - Ultra-fast risk parity portfolio design.
• sde - Simulation and inference for stochastic differential equations.
• YieldCurve - Yield curve modeling and estimation.
• SmithWilsonYieldCurve - Construction of yield curves from LIBOR and SWAP rates using the Smith-Wilson method.
• ycinterextra - Interpolation and extrapolation of yield curves or zero-coupon bond prices.
• AmericanCallOpt - American call option pricing with dividend-paying underlying assets.
• VarSwapPrice - Pricing of variance swaps.
• RND - A toolkit for extracting risk-neutral distributions.
• LSMonteCarlo - American option pricing via least-squares Monte Carlo.
• OptHedging - Estimation of call/put option values and hedging strategies.
• tvm - Time value of money functions.
• OptionPricing - Option pricing and efficient simulation algorithms.
• credule - Functions for credit default swaps (CDS).
• derivmkts - Functions and example R code from "Derivatives Markets".
• FinCal - A library of time value of money, time series analysis, and computational finance functions.
• r-quant - Example code for quantitative finance analysis in R.
• options.studies - Option trading research functions for use with the options.data package and shiny.
• PortfolioAnalytics - Portfolio analysis and numerical optimization methods.
• fmbasics - Basic building blocks for financial markets.
• R-fixedincome - R tools for fixed income products.

Trading

• backtest - For exploring portfolio-based hypotheses.
• pa - Performance attribution for equity portfolios.
• TTR - Technical trading rules.
• QuantTools - Enhanced quantitative trading modeling tools.
• blotter - A transaction framework for defining instruments, transactions, portfolios, and accounts, supporting multi-asset, multi-currency portfolios and simulations.

Backtesting

• quantstrat - A transaction framework for building and simulating trading systems, supporting multi-asset, multi-currency portfolios.

Risk Analysis

• PerformanceAnalytics - Econometric tools for portfolio and risk analysis.

Factor Analysis

• FactorAnalytics - A toolkit covering the three main types of factor models (fundamental, time series, statistical), as well as portfolio construction, optimization, and risk management.
• Expected Returns - Implementation in R of various portfolio methods and replication examples discussed in "Expected Returns" by Antti Ilmanen.

Time Series

• tseries - Time series analysis and computational finance.
• fGarch - Autoregressive conditional heteroskedasticity models from Rmetrics.
• timeSeries - Financial time series objects from Rmetrics.
• rugarch - Univariate GARCH models.
• rmgarch - Multivariate GARCH models.
• tidypredict - Run predictions inside databases.
• tidyquant - Bringing financial analysis into the tidyverse.
• timetk - A toolkit for time series analysis in R.
• tibbletime - Time-aware tibble extensions based on the tidyverse.
• matrixprofile - A time series data mining library based on the matrix profile structure and algorithms.
• garchmodels - A parsnip backend implementation for GARCH models.

Calendars

• timeDate - Time and calendar objects.
• bizdays - Business (trading) day calculation and related tools.

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Matlab

Frameworks

• QUANTAXIS - Matlab edition integrated quantitative toolkit.
• PROJ_Option_Pricing_Matlab - Quantitative option pricing (exotic/vanilla): barrier options, Asian options, European/American options, Parisian options, lookback options, Cliquet, variance swaps, Swing, forward-start options, ladder options, Fader options, etc.

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Julia

• Lucky.jl - A modular, asynchronous trading engine in pure Julia.
• QuantLib.jl - Julia implementation of QuantLib.
• Ito.jl - A quantitative finance package for Julia.
• TALib.jl - Julia wrapper for TA-Lib.
• IncTA.jl - Incremental technical analysis indicators in Julia.
• Miletus.jl - A financial contract definition, modeling language, and pricing framework.
• Temporal.jl - Flexible and efficient time series classes and methods.
• Indicators.jl - Financial market technical analysis and indicator library based on Temporal.
• Strategems.jl - Quantitative systematic trading strategy development and backtesting.
• TimeSeries.jl - A time series toolkit for Julia.
• MarketTechnicals.jl - Technical analysis of financial time series based on TimeSeries.
• MarketData.jl - Financial market time series data.
• TimeFrames.jl - A Julia library for resampling on TimeSeries.
• DataFrames.jl - In-memory tabular data structures in Julia.
• TSFrames.jl - Time series data handling based on DataFrames.jl.

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Java

• Strata - A modern open-source analytics and market risk library by OpenGamma.
• JQuantLib - A 100% Java free open-source quantitative finance framework, ported from QuantLib.
• finmath.net - Java libraries and algorithms related to mathematical finance.
• quantcomponents - Free Java components for quantitative finance and algorithmic trading.
• DRIP - A library for fixed income, asset allocation, transaction cost analysis, and XVA metrics.
• ta4j - A Java library for technical analysis.

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JavaScript

• finance.js - A JavaScript library for common financial calculations.
• portfolio-allocation - A JavaScript library for building multi-asset portfolios (bonds, commodities, cryptocurrencies, FX, ETFs, stocks, etc.).
• Ghostfolio - Wealth management software for tracking financial assets such as stocks, ETFs, or cryptocurrencies and making data-driven investment decisions.
• IndicatorTS - Provides various stock technical analysis indicators, strategies, and a backtesting framework in TypeScript.
• chart-patterns - A technical analysis library for market profile, volume profile, overlay buy/sell imbalance, and high-volume node indicators.
• orderflow - An order flow trading aggregator for constructing footprint candlesticks from exchange websockets.
• ccxt - A JavaScript / Python / PHP cryptocurrency trading API supporting 100+ bitcoin/altcoin exchanges.
• PENDAX - A JavaScript SDK for data, trading APIs, and WebSocket access to FTX, FTXUS, OKX, Bybit, and other exchanges.

Data Visualization

• QUANTAXIS_Webkit - A visualization center based on QUANTAXIS.

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Haskell

• quantfin - A pure Haskell quantitative finance library.
• Haxcel - A Haskell plugin for Excel.
• Ffinar - A financial mathematics library in Haskell.

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Scala

• QuantScale - A Scala quantitative finance library.
• Scala Quant - A Scala library for processing IFTTT or Google Finance stock data.

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Ruby

• Jiji - An open-source forex algorithmic trading framework using the OANDA REST API.

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Elixir/Erlang

• Tai - An open-source, composable real-time market data and trade execution toolkit.
• Workbench - From idea to executionmanaging a trading business on a distributed cluster.
• Prop - An open and opinionated trading platform for strategy research, execution, and operations using familiar open-source libraries and tools.

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Golang

• Kelp - An open-source Golang algorithmic crypto trading bot running on centralized exchanges and Stellar DEX (supporting CLI and desktop GUI).
• marketstore - A DataFrame server for financial time series data.
• IndicatorGo - A Golang module providing various stock technical analysis indicators, strategies, and a backtesting framework.

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CPP

• QuantLib - The QuantLib project aims to provide a comprehensive quantitative finance software framework.
• QuantLibRisks - Fast C++ risk computation using QuantLib.
• XAD - Automatic differentiation (AAD) library.
• TradeFrame - A C++17 trading framework/library (with examples) for testing options trading automation strategies, including an Option Greeks/IV computation library.
• Hikyuu - A C++/Python based open-source high-performance quantitative framework for rapid analysis and backtesting, with complete reusable trading system components.

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Frameworks

• QuantLib - A comprehensive quantitative finance software framework.

  • QuantLibRisks - Fast QuantLib-based risk computation in Python and C++.
  • XAD - Automatic differentiation (AAD) library for Python and C++.
  • JQuantLib - Java port.
  • RQuantLib - R wrapper.
  • QuantLibAddin - Excel support.
  • QuantLibXL - Excel support.
  • QLNet - .NET port.
  • PyQL - Python port.
  • QuantLib.jl - Julia port.
  • QuantLib-Python Documentation - Documentation for QuantLib Python bindings.

• TA-Lib - Technical analysis of financial market data.

  • ta-lib-python
  • ta-lib

• Portfolio Optimizer - A web API-based portfolio analysis and optimization service.

• XAD: Automatic differentiation (AAD) library for Python and C++

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CSharp

• QuantConnect - Lean Engine is an open-source C# algorithmic trading engine for desktop or cloud environments.
• StockSharp - An open-source platform for algorithmic and quantitative trading, supporting development of trading bots for stocks, forex, cryptocurrencies, and options.
• TDAmeritrade.DotNetCore - A free and open-source .NET client for integrating with the TD Ameritrade API and building custom trading solutions.

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Rust

• QuantMath - A financial mathematics library for risk-neutral pricing and risk management.
• Barter - An open-source Rust framework for building event-driven real-time trading and backtesting systems.
• LFEST - Simulate a perpetual futures exchange to paper-trade your strategies.
• TradeAggregation - Aggregate trades into custom-period candles or other forms using information-driven rules.
• SlidingFeatures - Chained tree sliding windows for signal processing and technical analysis.
• RustQuant - A quantitative finance library written in Rust.
• finalytics - A Rust library for financial data analysis.

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