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Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
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Wilson Freitas
2026-03-28 18:22:12 -03:00
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@@ -27,15 +27,15 @@ A curated list of insanely awesome libraries, packages and resources for Quants
## Numerical Libraries & Data Structures
- [numpy](https://www.numpy.org) - `Python` - NumPy is the fundamental package for scientific computing with Python. [GitHub](https://github.com/numpy/numpy)
- [scipy](https://www.scipy.org) - `Python` - SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering. [GitHub](https://github.com/scipy/scipy)
- [pandas](https://pandas.pydata.org) - `Python` - pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. [GitHub](https://github.com/pandas-dev/pandas)
- [polars](https://docs.pola.rs/) - `Python` - Polars is a blazingly fast DataFrame library for manipulating structured data. [GitHub](https://github.com/pola-rs/polars)
- [numpy](https://www.numpy.org) - `Python` - NumPy is the fundamental package for scientific computing with Python. [GitHub](https://github.com/numpy/numpy).
- [scipy](https://www.scipy.org) - `Python` - SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering. [GitHub](https://github.com/scipy/scipy).
- [pandas](https://pandas.pydata.org) - `Python` - pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. [GitHub](https://github.com/pandas-dev/pandas).
- [polars](https://docs.pola.rs/) - `Python` - Polars is a blazingly fast DataFrame library for manipulating structured data. [GitHub](https://github.com/pola-rs/polars).
- [quantdsl](https://github.com/johnbywater/quantdsl) - `Python` - Domain specific language for quantitative analytics in finance and trading.
- [statistics](https://docs.python.org/3/library/statistics.html) - `Python` - Builtin Python library for all basic statistical calculations.
- [sympy](https://www.sympy.org/) - `Python` - SymPy is a Python library for symbolic mathematics. [GitHub](https://github.com/sympy/sympy)
- [pymc3](https://docs.pymc.io/) - `Python` - Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano. [GitHub](https://github.com/pymc-devs/pymc)
- [modelx](https://docs.modelx.io/) - `Python` - Python reimagination of spreadsheets as formula-centric objects that are interoperable with pandas. [GitHub](https://github.com/fumitoh/modelx)
- [sympy](https://www.sympy.org/) - `Python` - SymPy is a Python library for symbolic mathematics. [GitHub](https://github.com/sympy/sympy).
- [pymc3](https://docs.pymc.io/) - `Python` - Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano. [GitHub](https://github.com/pymc-devs/pymc).
- [modelx](https://docs.modelx.io/) - `Python` - Python reimagination of spreadsheets as formula-centric objects that are interoperable with pandas. [GitHub](https://github.com/fumitoh/modelx).
- [ArcticDB](https://github.com/man-group/ArcticDB) - `Python` - High performance datastore for time series and tick data.
- [xts](https://github.com/joshuaulrich/xts) - `R` - eXtensible Time Series: Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.
- [data.table](https://github.com/Rdatatable/data.table) - `R` - Extension of data.frame: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns and a fast file reader (fread). Offers a natural and flexible syntax, for faster development.
@@ -47,14 +47,14 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [tfplot](https://cran.r-project.org/web/packages/tfplot/index.html) - `R` - Utilities for simple manipulation and quick plotting of time series data.
- [tframe](https://cran.r-project.org/web/packages/tframe/index.html) - `R` - A kernel of functions for programming time series methods in a way that is relatively independently of the representation of time.
- [Temporal.jl](https://github.com/dysonance/Temporal.jl) - `Julia` - Flexible and efficient time series class & methods.
- [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl) - `Julia` - In-memory tabular data in Julia
- [TSFrames.jl](https://github.com/xKDR/TSFrames.jl) - `Julia` - Handle timeseries data on top of the powerful and mature DataFrames.jl
- [TimeArrays.jl](https://github.com/bhftbootcamp/TimeArrays.jl) - `Julia` - Time series handling for Julia
- [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl) - `Julia` - In-memory tabular data in Julia.
- [TSFrames.jl](https://github.com/xKDR/TSFrames.jl) - `Julia` - Handle timeseries data on top of the powerful and mature DataFrames.jl.
- [TimeArrays.jl](https://github.com/bhftbootcamp/TimeArrays.jl) - `Julia` - Time series handling for Julia.
## Financial Instruments & Pricing
- [PyQL](https://github.com/enthought/pyql) - `Python` - QuantLib's Python port.
- [pyfin](https://github.com/opendoor-labs/pyfin) - `Python` - Basic options pricing in Python. *ARCHIVED*
- [pyfin](https://github.com/opendoor-labs/pyfin) - `Python` - Basic options pricing in Python. *ARCHIVED*.
- [vollib](https://github.com/vollib/vollib) - `Python` - vollib is a python library for calculating option prices, implied volatility and greeks.
- [QuantPy](https://github.com/jsmidt/QuantPy) - `Python` - A framework for quantitative finance In python.
- [Finance-Python](https://github.com/alpha-miner/Finance-Python) - `Python` - Python tools for Finance.
@@ -63,7 +63,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [tia](https://github.com/bpsmith/tia) - `Python` - Toolkit for integration and analysis.
- [pysabr](https://github.com/ynouri/pysabr) - `Python` - SABR model Python implementation.
- [FinancePy](https://github.com/domokane/FinancePy) - `Python` - A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
- [gs-quant](https://github.com/goldmansachs/gs-quant) - `Python` - Python toolkit for quantitative finance
- [gs-quant](https://github.com/goldmansachs/gs-quant) - `Python` - Python toolkit for quantitative finance.
- [willowtree](https://github.com/federicomariamassari/willowtree) - `Python` - Robust and flexible Python implementation of the willow tree lattice for derivatives pricing.
- [financial-engineering](https://github.com/federicomariamassari/financial-engineering) - `Python` - Applications of Monte Carlo methods to financial engineering projects, in Python.
- [optlib](https://github.com/dbrojas/optlib) - `Python` - A library for financial options pricing written in Python.
@@ -82,7 +82,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [optionlab](https://github.com/rgaveiga/optionlab) - `Python` - A Python library for evaluating option trading strategies.
- [flashalpha](https://github.com/FlashAlpha-lab/flashalpha-python) - `Python` - Python client for the FlashAlpha options analytics API.
- [RQuantLib](https://github.com/eddelbuettel/rquantlib) - `R` - RQuantLib connects GNU R with QuantLib.
- [quantmod](https://cran.r-project.org/web/packages/quantmod/index.html) - `R` - Quantitative Financial Modelling Framework. [GitHub](https://github.com/joshuaulrich/quantmod)
- [quantmod](https://cran.r-project.org/web/packages/quantmod/index.html) - `R` - Quantitative Financial Modelling Framework. [GitHub](https://github.com/joshuaulrich/quantmod).
- [Rmetrics](https://www.rmetrics.org) - `R` - The premier open source software solution for teaching and training quantitative finance.
- [fAsianOptions](https://cran.r-project.org/web/packages/fAsianOptions/index.html) - EBM and Asian Option Valuation.
- [fAssets](https://cran.r-project.org/web/packages/fAssets/index.html) - Analysing and Modelling Financial Assets.
@@ -103,7 +103,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [tvm](https://cran.r-project.org/web/packages/tvm/index.html) - `R` - Time Value of Money Functions.
- [OptionPricing](https://cran.r-project.org/web/packages/OptionPricing/index.html) - `R` - Option Pricing with Efficient Simulation Algorithms.
- [credule](https://github.com/blenezet/credule) - `R` - Credit Default Swap Functions.
- [derivmkts](https://cran.r-project.org/web/packages/derivmkts/index.html) - `R` - Functions and R Code to Accompany Derivatives Markets. [GitHub](https://github.com/rmcd1024/derivmkts)
- [derivmkts](https://cran.r-project.org/web/packages/derivmkts/index.html) - `R` - Functions and R Code to Accompany Derivatives Markets. [GitHub](https://github.com/rmcd1024/derivmkts).
- [FinCal](https://github.com/felixfan/FinCal) - `R` - Package for time value of money calculation, time series analysis and computational finance.
- [r-quant](https://github.com/artyyouth/r-quant) - `R` - R code for quantitative analysis in finance.
- [options.studies](https://github.com/taylorizing/options.studies) - `R` - options trading studies functions for use with options.data package and shiny.
@@ -112,9 +112,9 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [QuantLib.jl](https://github.com/pazzo83/QuantLib.jl) - `Julia` - Quantlib implementation in pure Julia.
- [Ito.jl](https://github.com/aviks/Ito.jl) - `Julia` - A Julia package for quantitative finance.
- [Miletus.jl](https://github.com/JuliaComputing/Miletus.jl) - `Julia` - A financial contract definition, modeling language, and valuation framework.
- [Strata](http://strata.opengamma.io/) - `Java` - Modern open-source analytics and market risk library designed and written in Java. [GitHub](https://github.com/OpenGamma/Strata)
- [Strata](http://strata.opengamma.io/) - `Java` - Modern open-source analytics and market risk library designed and written in Java. [GitHub](https://github.com/OpenGamma/Strata).
- [JQuantLib](https://github.com/frgomes/jquantlib) - `Java` - JQuantLib is a free, open-source, comprehensive framework for quantitative finance, written in 100% Java.
- [finmath.net](http://finmath.net) - `Java` - Java library with algorithms and methodologies related to mathematical finance. [GitHub](https://github.com/finmath/finmath-lib)
- [finmath.net](http://finmath.net) - `Java` - Java library with algorithms and methodologies related to mathematical finance. [GitHub](https://github.com/finmath/finmath-lib).
- [quantcomponents](https://github.com/lsgro/quantcomponents) - `Java` - Free Java components for Quantitative Finance and Algorithmic Trading.
- [DRIP](https://lakshmidrip.github.io/DRIP) - `Java` - Fixed Income, Asset Allocation, Transaction Cost Analysis, XVA Metrics Libraries.
- [finance.js](https://github.com/ebradyjobory/finance.js) - `JavaScript` - A JavaScript library for common financial calculations.
@@ -123,19 +123,19 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [Ffinar](https://github.com/MarcusRainbow/Ffinar) - `Haskell` - A financial maths library in Haskell.
- [QuantScale](https://github.com/choucrifahed/quantscale) - `Scala` - Scala Quantitative Finance Library.
- [Scala Quant](https://github.com/frankcash/Scala-Quant) - `Scala` - Scala library for working with stock data from IFTTT recipes or Google Finance.
- [QuantMath](https://github.com/MarcusRainbow/QuantMath) - `Rust` - Financial maths library for risk-neutral pricing and risk
- [QuantMath](https://github.com/MarcusRainbow/QuantMath) - `Rust` - Financial maths library for risk-neutral pricing and risk.
- [RustQuant](https://github.com/avhz/RustQuant) - `Rust` - Quantitative finance library written in Rust.
## Technical Indicators
- [pandas_talib](https://github.com/femtotrader/pandas_talib) - `Python` - A Python Pandas implementation of technical analysis indicators.
- [finta](https://github.com/peerchemist/finta) - `Python` - Common financial technical analysis indicators implemented in Pandas.
- [Tulipy](https://github.com/cirla/tulipy) - `Python` - Financial Technical Analysis Indicator Library (Python bindings for [tulipindicators](https://github.com/TulipCharts/tulipindicators))
- [Tulipy](https://github.com/cirla/tulipy) - `Python` - Financial Technical Analysis Indicator Library (Python bindings for [tulipindicators](https://github.com/TulipCharts/tulipindicators)).
- [lppls](https://github.com/Boulder-Investment-Technologies/lppls) - `Python` - A Python module for fitting the [Log-Periodic Power Law Singularity (LPPLS)](https://en.wikipedia.org/wiki/Didier_Sornette#The_JLS_and_LPPLS_models) model.
- [talipp](https://github.com/nardew/talipp) - `Python` - Incremental technical analysis library for Python.
- [streaming_indicators](https://github.com/mr-easy/streaming_indicators) - `Python` - A python library for computing technical analysis indicators on streaming data.
- [TA-Lib](https://github.com/mrjbq7/ta-lib) - `Python` - Python wrapper for TA-Lib (<http://ta-lib.org/>).
- [ta](https://github.com/bukosabino/ta) - `Python` - Technical Analysis Library using Pandas (Python)
- [ta](https://github.com/bukosabino/ta) - `Python` - Technical Analysis Library using Pandas (Python).
- [bta-lib](https://github.com/mementum/bta-lib) - `Python` - Technical Analysis library in pandas for backtesting algotrading and quantitative analysis.
- [TuneTA](https://github.com/jmrichardson/tuneta) - `Python` - TuneTA optimizes technical indicators using a distance correlation measure to a user defined target feature such as next day return.
- [TTR](https://github.com/joshuaulrich/TTR) - `R` - Technical Trading Rules.
@@ -186,19 +186,19 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [pinkfish](https://github.com/fja05680/pinkfish) - `Python` - A backtester and spreadsheet library for security analysis.
- [PRISM-INSIGHT](https://github.com/dragon1086/prism-insight) - `Python` - AI-powered stock analysis system with 13 specialized agents, automated trading via KIS API, supporting Korean & US markets.
- [FinClaw](https://github.com/NeuZhou/finclaw) - `Python` - AI-powered financial intelligence engine with 8 master strategies across US, CN, and HK markets. Multi-agent architecture with +29.1% annual alpha. 227 tests.
- [aat](https://github.com/timkpaine/aat) - `Python` - Async Algorithmic Trading Engine
- [Backtesting.py](https://kernc.github.io/backtesting.py/) - `Python` - Backtest trading strategies in Python
- [catalyst](https://github.com/enigmampc/catalyst) - `Python` - An Algorithmic Trading Library for Crypto-Assets in Python
- [quantstats](https://github.com/ranaroussi/quantstats) - `Python` - Portfolio analytics for quants, written in Python
- [aat](https://github.com/timkpaine/aat) - `Python` - Async Algorithmic Trading Engine.
- [Backtesting.py](https://kernc.github.io/backtesting.py/) - `Python` - Backtest trading strategies in Python.
- [catalyst](https://github.com/enigmampc/catalyst) - `Python` - An Algorithmic Trading Library for Crypto-Assets in Python.
- [quantstats](https://github.com/ranaroussi/quantstats) - `Python` - Portfolio analytics for quants, written in Python.
- [jquantstats](https://github.com/Jebel-Quant/jquantstats) - `Python` - Modern variation of quantstats, with additional features and performance improvements.
- [qtpylib](https://github.com/ranaroussi/qtpylib) - `Python` - QTPyLib, Pythonic Algorithmic Trading <http://qtpylib.io>
- [Quantdom](https://github.com/constverum/Quantdom) - `Python` - Python-based framework for backtesting trading strategies & analyzing financial markets [GUI :neckbeard:]
- [freqtrade](https://github.com/freqtrade/freqtrade) - `Python` - Free, open source crypto trading bot
- [qtpylib](https://github.com/ranaroussi/qtpylib) - `Python` - QTPyLib, Pythonic Algorithmic Trading <http://qtpylib.io>.
- [Quantdom](https://github.com/constverum/Quantdom) - `Python` - Python-based framework for backtesting trading strategies & analyzing financial markets [GUI :neckbeard:.]
- [freqtrade](https://github.com/freqtrade/freqtrade) - `Python` - Free, open source crypto trading bot.
- [algorithmic-trading-with-python](https://github.com/chrisconlan/algorithmic-trading-with-python) - `Python` - Free `pandas` and `scikit-learn` resources for trading simulation, backtesting, and machine learning on financial data.
- [Qlib](https://github.com/microsoft/qlib) - `Python` - An AI-oriented Quantitative Investment Platform by Microsoft. Full ML pipeline of data processing, model training, back-testing; and covers the entire chain of quantitative investment: alpha seeking, risk modeling, portfolio optimization, and order execution.
- [machine-learning-for-trading](https://github.com/stefan-jansen/machine-learning-for-trading) - `Python` - Code and resources for Machine Learning for Algorithmic Trading
- [AlphaPy](https://github.com/ScottfreeLLC/AlphaPy) - `Python` - Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost
- [jesse](https://github.com/jesse-ai/jesse) - `Python` - An advanced crypto trading bot written in Python
- [machine-learning-for-trading](https://github.com/stefan-jansen/machine-learning-for-trading) - `Python` - Code and resources for Machine Learning for Algorithmic Trading.
- [AlphaPy](https://github.com/ScottfreeLLC/AlphaPy) - `Python` - Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost.
- [jesse](https://github.com/jesse-ai/jesse) - `Python` - An advanced crypto trading bot written in Python.
- [rqalpha](https://github.com/ricequant/rqalpha) - `Python` - A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities.
- [FinRL-Library](https://github.com/AI4Finance-LLC/FinRL-Library) - `Python` - A Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020.
- [bulbea](https://github.com/achillesrasquinha/bulbea) - `Python` - Deep Learning based Python Library for Stock Market Prediction and Modelling.
@@ -219,11 +219,11 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [OctoBot Script](https://github.com/Drakkar-Software/OctoBot-Script) - `Python` - A quant framework to create cryptocurrencies strategies - from backtesting to optimization to livetrading.
- [hftbacktest](https://github.com/nkaz001/hftbacktest) - `Python` - A high-frequency trading and market-making backtesting tool accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.
- [vnpy](https://github.com/vnpy/vnpy) - `Python` - VeighNa is a Python-based open source quantitative trading system development framework.
- [Intelligent Trading Bot](https://github.com/asavinov/intelligent-trading-bot) - `Python` - Automatically generating signals and trading based on machine learning and feature engineering
- [Intelligent Trading Bot](https://github.com/asavinov/intelligent-trading-bot) - `Python` - Automatically generating signals and trading based on machine learning and feature engineering.
- [fastquant](https://github.com/enzoampil/fastquant) - `Python` - fastquant allows you to easily backtest investment strategies with as few as 3 lines of python code.
- [nautilus_trader](https://github.com/nautechsystems/nautilus_trader) - `Python` `Rust` - A high-performance algorithmic trading platform and event-driven backtester.
- [YABTE](https://github.com/bsdz/yabte) - `Python` - Yet Another (Python) BackTesting Engine.
- [Trading Strategy](https://github.com/tradingstrategy-ai/getting-started) - `Python` - TradingStrategy.ai is a market data, backtesting, live trading and investor management framework for decentralised finance
- [Trading Strategy](https://github.com/tradingstrategy-ai/getting-started) - `Python` - TradingStrategy.ai is a market data, backtesting, live trading and investor management framework for decentralised finance.
- [Hikyuu](https://github.com/fasiondog/hikyuu) - `Python` `C++` - A base on Python/C++ open source high-performance quant framework for faster analysis and backtesting, contains the complete trading system components for reuse and combination.
- [rust_bt](https://github.com/jensnesten/rust_bt) - `Python` - A high performance, low-latency backtesting engine for testing quantitative trading strategies on historical and live data in Rust.
- [Gunbot Quant](https://github.com/GuntharDeNiro/gunbot-quant) - `Python` - Toolkit for quantitative trading analysis. It integrates an advanced market screener, a multi-strategy, multi-asset backtesting engine. Use with built-in GUI or through CLI.
@@ -240,7 +240,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [blotter](https://github.com/braverock/blotter) - `R` - Transaction infrastructure for defining instruments, transactions, portfolios and accounts for trading systems and simulation. Provides portfolio support for multi-asset class and multi-currency portfolios. Actively maintained and developed.
- [quantstrat](https://github.com/braverock/quantstrat) - `R` - Transaction-oriented infrastructure for constructing trading systems and simulation. Provides support for multi-asset class and multi-currency portfolios for backtesting and other financial research.
- [QUANTAXIS](https://github.com/yutiansut/quantaxis) - `Matlab` - Integrated Quantitative Toolbox with Matlab.
- [PROJ_Option_Pricing_Matlab](https://github.com/jkirkby3/PROJ_Option_Pricing_Matlab) - `Matlab` - Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader
- [PROJ_Option_Pricing_Matlab](https://github.com/jkirkby3/PROJ_Option_Pricing_Matlab) - `Matlab` - Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader.
- [Fastback.jl](https://github.com/rbeeli/Fastback.jl) - `Julia` - Blazing fast Julia backtester.
- [Lucky.jl](https://github.com/oliviermilla/Lucky.jl) - `Julia` - Modular, asynchronous trading engine in pure Julia.
- [Strategems.jl](https://github.com/dysonance/Strategems.jl) - `Julia` - Quantitative systematic trading strategy development and backtesting.
@@ -248,18 +248,18 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [TradeClaw](https://github.com/naimkatiman/tradeclaw) - `JavaScript` - Open-source AI trading signal platform with RSI/MACD/EMA confluence scoring, real-time signals for 10+ assets, self-hostable with one Docker command.
- [Jiji](https://github.com/unageanu/jiji2) - `Ruby` - Open Source Forex algorithmic trading framework using OANDA REST API.
- [Tai](https://github.com/fremantle-capital/tai) - `Elixir/Erlang` - Open Source composable, real time, market data and trade execution toolkit.
- [Workbench](https://github.com/fremantle-industries/workbench) - `Elixir/Erlang` - From Idea to Execution - Manage your trading operation across a globally distributed cluster
- [Workbench](https://github.com/fremantle-industries/workbench) - `Elixir/Erlang` - From Idea to Execution - Manage your trading operation across a globally distributed cluster.
- [Prop](https://github.com/fremantle-industries/prop) - `Elixir/Erlang` - An open and opinionated trading platform using productive & familiar open source libraries and tools for strategy research, execution and operation.
- [Kelp](https://github.com/stellar/kelp) - `Golang` - Kelp is an open-source Golang algorithmic cryptocurrency trading bot that runs on centralized exchanges and Stellar DEX (command-line usage and desktop GUI).
- [TradeFrame](https://github.com/rburkholder/trade-frame) - `CPP` - C++ 17 based framework/library (with sample applications) for testing options based automated trading ideas using DTN IQ real time data feed and Interactive Brokers (TWS API) for trade execution. Comes with built-in [Option Greeks/IV](https://github.com/rburkholder/trade-frame/tree/master/lib/TFOptions) calculation library.
- [Hikyuu](https://github.com/fasiondog/hikyuu) - `Python` `C++` - A base on Python/C++ open source high-performance quant framework for faster analysis and backtesting, contains the complete trading system components for reuse and combination. You can use python or c++ freely.
- [OrderMatchingEngine](https://github.com/PIYUSH-KUMAR1809/order-matching-engine) - `CPP` - A production-grade, lock-free, high-frequency trading matching engine achieving 150M+ orders/sec.
- [PandoraTrader](https://github.com/pegasusTrader/PandoraTrader) - `CPP` - A C++ CTP trading framework, with very clear logic
- [PandoraTrader](https://github.com/pegasusTrader/PandoraTrader) - `CPP` - A C++ CTP trading framework, with very clear logic.
- [NexusFix](https://github.com/SilverstreamsAI/NexusFix) - `CPP` - C++23 FIX protocol engine with zero-copy parsing and SIMD acceleration, 3x faster than QuickFIX.
- [QuantConnect](https://github.com/QuantConnect/Lean) - `CSharp` - Lean Engine is an open-source fully managed C# algorithmic trading engine built for desktop and cloud usage.
- [StockSharp](https://github.com/StockSharp/StockSharp) - `CSharp` - Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
- [TDAmeritrade.DotNetCore](https://github.com/NVentimiglia/TDAmeritrade.DotNetCore) - `CSharp` - Free, open-source .NET Client for the TD Ameritrade Trading Platform. Helps developers integrate TD Ameritrade API into custom trading solutions.
- [Barter](https://github.com/barter-rs/barter-rs) - `Rust` - Open-source Rust framework for building event-driven live-trading & backtesting systems
- [Barter](https://github.com/barter-rs/barter-rs) - `Rust` - Open-source Rust framework for building event-driven live-trading & backtesting systems.
- [LFEST](https://github.com/MathisWellmann/lfest-rs) - `Rust` - Simulated perpetual futures exchange to trade your strategy against.
- [OpenFinClaw](https://github.com/cryptoSUN2049/openFinclaw) - `Python` `Rust` - AI-native one-person hedge fund platform with Rust trading engine. Natural language → strategy → backtest → execution in 60s. Multi-market (US/HK/CN/Crypto), self-evolving strategy pipeline. Built on OpenClaw (68K+ stars).
@@ -268,16 +268,16 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [skfolio](https://github.com/skfolio/skfolio) - `Python` - Python library for portfolio optimization built on top of scikit-learn. It provides a unified interface and sklearn compatible tools to build, tune and cross-validate portfolio models.
- [PyPortfolioOpt](https://github.com/robertmartin8/PyPortfolioOpt) - `Python` - Financial portfolio optimization in python, including classical efficient frontier and advanced methods.
- [Eiten](https://github.com/tradytics/eiten) - `Python` - Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic investing strategies such as Eigen Portfolios, Minimum Variance Portfolios, Maximum Sharpe Ratio Portfolios, and Genetic Algorithms based Portfolios.
- [riskparity.py](https://github.com/dppalomar/riskparity.py) - `Python` - fast and scalable design of risk parity portfolios with TensorFlow 2.0
- [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) - `Python` - Implementations regarding "Advances in Financial Machine Learning" by Marcos Lopez de Prado. (Feature Engineering, Financial Data Structures, Meta-Labeling)
- [DeepDow](https://github.com/jankrepl/deepdow) - `Python` - Portfolio optimization with deep learning
- [QuantLibRisks](https://github.com/auto-differentiation/QuantLib-Risks-Py) - `Python` - Fast risks with QuantLib
- [XAD](https://github.com/auto-differentiation/xad-py) - `Python` - Automatic Differentation (AAD) Library
- [riskparity.py](https://github.com/dppalomar/riskparity.py) - `Python` - fast and scalable design of risk parity portfolios with TensorFlow 2.0.
- [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) - `Python` - Implementations regarding "Advances in Financial Machine Learning" by Marcos Lopez de Prado. (Feature Engineering, Financial Data Structures, Meta-Labeling).
- [DeepDow](https://github.com/jankrepl/deepdow) - `Python` - Portfolio optimization with deep learning.
- [QuantLibRisks](https://github.com/auto-differentiation/QuantLib-Risks-Py) - `Python` - Fast risks with QuantLib.
- [XAD](https://github.com/auto-differentiation/xad-py) - `Python` - Automatic Differentation (AAD) Library.
- [pyfolio](https://github.com/quantopian/pyfolio) - `Python` - Portfolio and risk analytics in Python.
- [empyrical](https://github.com/quantopian/empyrical) - `Python` - Common financial risk and performance metrics.
- [fecon235](https://github.com/rsvp/fecon235) - `Python` - Computational tools for financial economics include: Gaussian Mixture model of leptokurtotic risk, adaptive Boltzmann portfolios.
- [finance](https://pypi.org/project/finance/) - `Python` - Financial Risk Calculations. Optimized for ease of use through class construction and operator overload.
- [qfrm](https://pypi.org/project/qfrm/) - `Python` - Quantitative Financial Risk Management: awesome OOP tools for measuring, managing and visualizing risk of financial instruments and portfolios. (Last updated: 2015-12-12)
- [qfrm](https://pypi.org/project/qfrm/) - `Python` - Quantitative Financial Risk Management: awesome OOP tools for measuring, managing and visualizing risk of financial instruments and portfolios. (Last updated: 2015-12-12).
- [visualize-wealth](https://github.com/benjaminmgross/visualize-wealth) - `Python` - Portfolio construction and quantitative analysis.
- [VisualPortfolio](https://github.com/wegamekinglc/VisualPortfolio) - `Python` - This tool is used to visualize the performance of a portfolio.
- [universal-portfolios](https://github.com/Marigold/universal-portfolios) - `Python` - Collection of algorithms for online portfolio selection.
@@ -306,7 +306,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [alphalens](https://github.com/quantopian/alphalens) - `Python` - Performance analysis of predictive alpha factors.
- [alphalens-reloaded](https://github.com/stefan-jansen/alphalens-reloaded) - `Python` - Performance analysis of predictive (alpha) stock factors.
- [Spectre](https://github.com/Heerozh/spectre) - `Python` - GPU-accelerated Factors analysis library and Backtester
- [Spectre](https://github.com/Heerozh/spectre) - `Python` - GPU-accelerated Factors analysis library and Backtester.
- [quant-lab-alpha](https://github.com/husainm97/quant-lab-alpha) - `Python` - Open-source investment analytics platform bridging academic research and retail finance.
- [covFactorModel](https://github.com/dppalomar/covFactorModel) - `R` - Covariance matrix estimation via factor models.
- [FactorAnalytics](https://github.com/braverock/FactorAnalytics) - `R` - The FactorAnalytics package contains fitting and analysis methods for the three main types of factor models used in conjunction with portfolio construction, optimization and risk management, namely fundamental factor models, time series factor models and statistical factor models.
@@ -320,7 +320,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
## Time Series Analysis
- [ARCH](https://github.com/bashtage/arch) - `Python` - ARCH models in Python.
- [statsmodels](http://statsmodels.sourceforge.net) - `Python` - Python module that allows users to explore data, estimate statistical models, and perform statistical tests. [GitHub](https://github.com/statsmodels/statsmodels)
- [statsmodels](http://statsmodels.sourceforge.net) - `Python` - Python module that allows users to explore data, estimate statistical models, and perform statistical tests. [GitHub](https://github.com/statsmodels/statsmodels).
- [dynts](https://github.com/quantmind/dynts) - `Python` - Python package for timeseries analysis and manipulation.
- [PyFlux](https://github.com/RJT1990/pyflux) - `Python` - Python library for timeseries modelling and inference (frequentist and Bayesian) on models.
- [tsfresh](https://github.com/blue-yonder/tsfresh) - `Python` - Automatic extraction of relevant features from time series.
@@ -348,7 +348,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [OpenBB Terminal](https://github.com/OpenBB-finance/OpenBBTerminal) - `Python` - Terminal for investment research for everyone.
- [Fincept Terminal](https://github.com/Fincept-Corporation/FinceptTerminal) - `Python` - Advance Data Based A.I Terminal for all Types of Financial Asset Research.
- [yfinance](https://github.com/ranaroussi/yfinance) - `Python` - Yahoo! Finance market data downloader (+faster Pandas Datareader)
- [yfinance](https://github.com/ranaroussi/yfinance) - `Python` - Yahoo! Finance market data downloader (+faster Pandas Datareader).
- [defeatbeta-api](https://github.com/defeat-beta/defeatbeta-api) - `Python` - An open-source alternative to Yahoo Finance's market data APIs with higher reliability.
- [findatapy](https://github.com/cuemacro/findatapy) - `Python` - Python library to download market data via Bloomberg, Quandl, Yahoo etc.
- [googlefinance](https://github.com/hongtaocai/googlefinance) - `Python` - Python module to get real-time stock data from Google Finance API.
@@ -366,17 +366,17 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [wallstreet](https://github.com/mcdallas/wallstreet) - `Python` - Real time stock and option data.
- [stock_extractor](https://github.com/ZachLiuGIS/stock_extractor) - `Python` - General Purpose Stock Extractors from Online Resources.
- [Stockex](https://github.com/cttn/Stockex) - `Python` - Python wrapper for Yahoo! Finance API.
- [SwapAPI](https://swapapi.dev) - `Python` - Free DEX aggregator API returning executable swap calldata across 46 EVM chains. No API key required. [GitHub](https://github.com/swap-api/swap-api)
- [SwapAPI](https://swapapi.dev) - `Python` - Free DEX aggregator API returning executable swap calldata across 46 EVM chains. No API key required. [GitHub](https://github.com/swap-api/swap-api).
- [finsymbols](https://github.com/skillachie/finsymbols) - `Python` - Obtains stock symbols and relating information for SP500, AMEX, NYSE, and NASDAQ.
- [FRB](https://github.com/avelkoski/FRB) - `Python` - Python Client for FRED® API.
- [inquisitor](https://github.com/econdb/inquisitor) - `Python` - Python Interface to Econdb.com API.
- [yfi](https://github.com/nickelkr/yfi) - `Python` - Yahoo! YQL library.
- [chinesestockapi](https://pypi.org/project/chinesestockapi/) - `Python` - Python API to get Chinese stock price. (Last updated: 2015-03-21)
- [chinesestockapi](https://pypi.org/project/chinesestockapi/) - `Python` - Python API to get Chinese stock price. (Last updated: 2015-03-21).
- [exchange](https://github.com/akarat/exchange) - `Python` - Get current exchange rate.
- [ticks](https://github.com/jamescnowell/ticks) - `Python` - Simple command line tool to get stock ticker data.
- [pybbg](https://github.com/bpsmith/pybbg) - `Python` - Python interface to Bloomberg COM APIs.
- [ccy](https://github.com/lsbardel/ccy) - `Python` - Python module for currencies.
- [tushare](https://pypi.org/project/tushare/) - `Python` - A utility for crawling historical and Real-time Quotes data of China stocks. (Last updated: 2024-08-27)
- [tushare](https://pypi.org/project/tushare/) - `Python` - A utility for crawling historical and Real-time Quotes data of China stocks. (Last updated: 2024-08-27).
- [edinetdb](https://edinetdb.com/) - `Python` - Free API and MCP server for Japanese company financials. Normalizes EDINET XBRL across JP-GAAP, IFRS, and US-GAAP for 3,800+ listed companies with 90 metrics, screening, and securities report text.
- [edinet-mcp](https://github.com/ajtgjmdjp/edinet-mcp) - `Python` - Parse Japanese XBRL financial statements from EDINET with 161 normalized labels, 26 financial metrics, and multi-company screening.
- [estat-mcp](https://github.com/ajtgjmdjp/estat-mcp) - `Python` - Access Japanese government statistics (e-Stat) covering population, GDP, CPI, labor, and trade data with MCP integration and Polars export.
@@ -385,43 +385,43 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [coinmarketcap](https://github.com/barnumbirr/coinmarketcap) - `Python` - Python API for coinmarketcap.
- [coinpulse](https://github.com/soutone/coinpulse-python) - `Python` - Python SDK for cryptocurrency portfolio tracking with real-time prices, P/L calculations, and price alerts. Free tier available.
- [after-hours](https://github.com/datawrestler/after-hours) - `Python` - Obtain pre market and after hours stock prices for a given symbol.
- [bronto-python](https://pypi.org/project/bronto-python/) - `Python` - Bronto API Integration for Python. [GitHub](https://github.com/Scotts-Marketplace/bronto-python)
- [bronto-python](https://pypi.org/project/bronto-python/) - `Python` - Bronto API Integration for Python. [GitHub](https://github.com/Scotts-Marketplace/bronto-python).
- [pytdx](https://github.com/rainx/pytdx) - `Python` - Python Interface for retrieving chinese stock realtime quote data from TongDaXin Nodes.
- [pdblp](https://github.com/matthewgilbert/pdblp) - `Python` - A simple interface to integrate pandas and the Bloomberg Open API.
- [tiingo](https://github.com/hydrosquall/tiingo-python) - `Python` - Python interface for daily composite prices/OHLC/Volume + Real-time News Feeds, powered by the Tiingo Data Platform.
- [iexfinance](https://github.com/addisonlynch/iexfinance) - `Python` - Python Interface for retrieving real-time and historical prices and equities data from The Investor's Exchange.
- [pyEX](https://github.com/timkpaine/pyEX) - `Python` - Python interface to IEX with emphasis on pandas, support for streaming data, premium data, points data (economic, rates, commodities), and technical indicators.
- [alpaca-trade-api](https://github.com/alpacahq/alpaca-trade-api-python) - `Python` - Python interface for retrieving real-time and historical prices from Alpaca API as well as trade execution.
- [metatrader5](https://pypi.org/project/MetaTrader5/) - `Python` - API Connector to MetaTrader 5 Terminal. (Last updated: 2026-02-20)
- [akshare](https://github.com/jindaxiang/akshare) - `Python` - AkShare is an elegant and simple financial data interface library for Python, built for human beings! <https://akshare.readthedocs.io>
- [metatrader5](https://pypi.org/project/MetaTrader5/) - `Python` - API Connector to MetaTrader 5 Terminal. (Last updated: 2026-02-20).
- [akshare](https://github.com/jindaxiang/akshare) - `Python` - AkShare is an elegant and simple financial data interface library for Python, built for human beings! <https://akshare.readthedocs.io>.
- [yahooquery](https://github.com/dpguthrie/yahooquery) - `Python` - Python interface for retrieving data through unofficial Yahoo Finance API.
- [investpy](https://github.com/alvarobartt/investpy) - `Python` - Financial Data Extraction from Investing.com with Python! <https://investpy.readthedocs.io/>
- [investpy](https://github.com/alvarobartt/investpy) - `Python` - Financial Data Extraction from Investing.com with Python! <https://investpy.readthedocs.io/>.
- [yliveticker](https://github.com/yahoofinancelive/yliveticker) - `Python` - Live stream of market data from Yahoo Finance websocket.
- [bbgbridge](https://github.com/ran404/bbgbridge) - `Python` - Easy to use Bloomberg Desktop API wrapper for Python.
- [polygon.io](https://github.com/polygon-io/client-python) - `Python` - A python library for Polygon.io financial data APIs.
- [alpha_vantage](https://github.com/RomelTorres/alpha_vantage) - `Python` - A python wrapper for Alpha Vantage API for financial data.
- [oilpriceapi](https://github.com/OilpriceAPI/python-sdk) - `Python` - Python SDK for real-time oil and commodity prices (WTI, Brent, Urals, natural gas, coal) with OpenBB integration.
- [FinanceDataReader](https://github.com/FinanceData/FinanceDataReader) - `Python` - Open Source Financial data reader for U.S, Korean, Japanese, Chinese, Vietnamese Stocks
- [FinanceDataReader](https://github.com/FinanceData/FinanceDataReader) - `Python` - Open Source Financial data reader for U.S, Korean, Japanese, Chinese, Vietnamese Stocks.
- [pystlouisfed](https://github.com/TomasKoutek/pystlouisfed) - `Python` - Python client for Federal Reserve Bank of St. Louis API - FRED, ALFRED, GeoFRED and FRASER.
- [python-bcb](https://github.com/wilsonfreitas/python-bcb) - `Python` - Python interface to Brazilian Central Bank web services.
- [swiss-finance-data](https://github.com/EMen11/swiss-finance-data) - `Python` - Python package for Swiss financial data (SNB Policy Rate, SARON, CHF FX rates, CPI, SMI equities, Confederation bond yields) from official SNB sources.
- [market-prices](https://github.com/maread99/market_prices) - `Python` - Create meaningful OHLCV datasets from knowledge of [exchange-calendars](https://github.com/gerrymanoim/exchange_calendars) (works out-the-box with data from Yahoo Finance).
- [tardis-python](https://github.com/tardis-dev/tardis-python) - `Python` - Python interface for Tardis.dev high frequency crypto market data
- [lake-api](https://github.com/crypto-lake/lake-api) - `Python` - Python interface for Crypto Lake high frequency crypto market data
- [tardis-python](https://github.com/tardis-dev/tardis-python) - `Python` - Python interface for Tardis.dev high frequency crypto market data.
- [lake-api](https://github.com/crypto-lake/lake-api) - `Python` - Python interface for Crypto Lake high frequency crypto market data.
- [tessa](https://github.com/ymyke/tessa) - `Python` - simple, hassle-free access to price information of financial assets (currently based on yfinance and pycoingecko), including search and a symbol class.
- [pandaSDMX](https://github.com/dr-leo/pandaSDMX) - `Python` - Python package that implements SDMX 2.1 (ISO 17369:2013), a format for exchange of statistical data and metadata used by national statistical agencies, central banks, and international organisations.
- [cif](https://github.com/LenkaV/CIF) - `Python` - Python package that include few composite indicators, which summarize multidimensional relationships between individual economic indicators.
- [finagg](https://github.com/theOGognf/finagg) - `Python` - finagg is a Python package that provides implementations of popular and free financial APIs, tools for aggregating historical data from those APIs into SQL databases, and tools for transforming aggregated data into features useful for analysis and AI/ML.
- [FinanceDatabase](https://github.com/JerBouma/FinanceDatabase) - `Python` - This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.
- [Trading Strategy](https://github.com/tradingstrategy-ai/trading-strategy/) - `Python` - download price data for decentralised exchanges and lending protocols (DeFi)
- [Trading Strategy](https://github.com/tradingstrategy-ai/trading-strategy/) - `Python` - download price data for decentralised exchanges and lending protocols (DeFi).
- [datamule-python](https://github.com/john-friedman/datamule-python) - `Python` - A package to work with SEC data. Incorporates datamule endpoints.
- [fsynth](https://github.com/welcra/fsynth) - `Python` - Python library for high-fidelity unlimited synthetic financial data generation using Heston Stochastic Volatility and Merton Jump Diffusion.
- [fedfred](https://nikhilxsunder.github.io/fedfred/) - `Python` - FRED & GeoFRED Economic data API with preprocessed dataframe output in pandas/geopandas, polars/polars_st, and dask dataframes/geodataframes.
- [edgar-sec](https://nikhilxsunder.github.io/edgar-sec/) - `Python` - EDGAR Financial data API with preprocessed dataclass outputs.
- [edgartools](https://github.com/dgunning/edgartools) - `Python` - AI-native SEC EDGAR library with XBRL financials, clean text extraction, 17+ typed forms, and pandas DataFrames.
- [FXMacroData](https://fxmacrodata.com/) - `Python` - Real-time forex macroeconomic API for all major currency pairs sourced from central bank announcements. [GitHub](https://github.com/fxmacrodata/fxmacrodata)
- [uk-sic-codes](https://github.com/borschai/uk-sic-codes) - `Python` - UK SIC 2007 industry classification code lookup, search, and validation. 731 codes, 21 sections. [PyPI](https://pypi.org/project/uk-sic-codes/)
- [uk-company-number](https://github.com/borschai/uk-company-number) - `Python` - Validate, format, and identify UK Companies House company numbers. Supports all 27 prefixes. [PyPI](https://pypi.org/project/uk-company-number/)
- [FXMacroData](https://fxmacrodata.com/) - `Python` - Real-time forex macroeconomic API for all major currency pairs sourced from central bank announcements. [GitHub](https://github.com/fxmacrodata/fxmacrodata).
- [uk-sic-codes](https://github.com/borschai/uk-sic-codes) - `Python` - UK SIC 2007 industry classification code lookup, search, and validation. 731 codes, 21 sections. [PyPI](https://pypi.org/project/uk-sic-codes/).
- [uk-company-number](https://github.com/borschai/uk-company-number) - `Python` - Validate, format, and identify UK Companies House company numbers. Supports all 27 prefixes. [PyPI](https://pypi.org/project/uk-company-number/).
- [IBrokers](https://cran.r-project.org/web/packages/IBrokers/index.html) - `R` - Provides native R access to Interactive Brokers Trader Workstation API.
- [Rblpapi](https://github.com/Rblp/Rblpapi) - `R` - An R Interface to 'Bloomberg' is provided via the 'Blp API'.
- [Rbitcoin](https://github.com/jangorecki/Rbitcoin) - `R` - Unified markets API interface (bitstamp, kraken, btce, bitmarket).
@@ -431,9 +431,9 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [rbcb](https://github.com/wilsonfreitas/rbcb) - `R` - R interface to Brazilian Central Bank web services.
- [rb3](https://github.com/ropensci/rb3) - `R` - A bunch of downloaders and parsers for data delivered from B3.
- [simfinapi](https://github.com/matthiasgomolka/simfinapi) - `R` - Makes 'SimFin' data (<https://simfin.com/>) easily accessible in R.
- [tidyfinance](https://github.com/tidy-finance/r-tidyfinance) - `R` - Tidy Finance helper functions to download financial data and process the raw data into a structured Format (tidy data), including
- [CcyConv.jl](https://github.com/bhftbootcamp/CcyConv.jl) - `Julia` - Currency conversion library for Julia
- [CryptoExchangeAPIs.jl](https://github.com/bhftbootcamp/CryptoExchangeAPIs.jl) - `Julia` - A Julia library for cryptocurrency exchange APIs
- [tidyfinance](https://github.com/tidy-finance/r-tidyfinance) - `R` - Tidy Finance helper functions to download financial data and process the raw data into a structured Format (tidy data), including.
- [CcyConv.jl](https://github.com/bhftbootcamp/CcyConv.jl) - `Julia` - Currency conversion library for Julia.
- [CryptoExchangeAPIs.jl](https://github.com/bhftbootcamp/CryptoExchangeAPIs.jl) - `Julia` - A Julia library for cryptocurrency exchange APIs.
- [MarketData.jl](https://github.com/JuliaQuant/MarketData.jl) - `Julia` - Time series market data.
- [OnlineResamplers.jl](https://github.com/femtotrader/OnlineResamplers.jl) - `Julia` - High-performance Julia package for real-time resampling of financial market data.
- [PENDAX](https://github.com/CompendiumFi/PENDAX-SDK) - `JavaScript` - Javascript SDK for Trading/Data API and Websockets for FTX, FTXUS, OKX, Bybit, & More.
@@ -455,8 +455,8 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [exchange_calendars](https://github.com/gerrymanoim/exchange_calendars) - `Python` - Stock Exchange Trading Calendars.
- [bizdays](https://github.com/wilsonfreitas/python-bizdays) - `Python` - Business days calculations and utilities.
- [pandas_market_calendars](https://github.com/rsheftel/pandas_market_calendars) - `Python` - Exchange calendars to use with pandas for trading applications.
- [timeDate](https://cran.r-project.org/web/packages/timeDate/index.html) - `R` - Chronological and Calendar Objects
- [bizdays](https://github.com/wilsonfreitas/R-bizdays) - `R` - Business days calculations and utilities
- [timeDate](https://cran.r-project.org/web/packages/timeDate/index.html) - `R` - Chronological and Calendar Objects.
- [bizdays](https://github.com/wilsonfreitas/R-bizdays) - `R` - Business days calculations and utilities.
## Visualization
@@ -471,12 +471,12 @@ A curated list of insanely awesome libraries, packages and resources for Quants
## Excel & Spreadsheet Integration
- [xlwings](https://www.xlwings.org/) - `Python` - Make Excel fly with Python. [GitHub](https://github.com/xlwings/xlwings)
- [xlwings](https://www.xlwings.org/) - `Python` - Make Excel fly with Python. [GitHub](https://github.com/xlwings/xlwings).
- [openpyxl](https://openpyxl.readthedocs.io/en/latest/) - `Python` - Read/Write Excel 2007 xlsx/xlsm files.
- [xlrd](https://github.com/python-excel/xlrd) - `Python` - Library for developers to extract data from Microsoft Excel spreadsheet files.
- [xlsxwriter](https://xlsxwriter.readthedocs.io/) - `Python` - Write files in the Excel 2007+ XLSX file format. [GitHub](https://github.com/jmcnamara/XlsxWriter)
- [xlsxwriter](https://xlsxwriter.readthedocs.io/) - `Python` - Write files in the Excel 2007+ XLSX file format. [GitHub](https://github.com/jmcnamara/XlsxWriter).
- [xlwt](https://github.com/python-excel/xlwt) - `Python` - Library to create spreadsheet files compatible with MS Excel 97/2000/XP/2003 XLS files, on any platform.
- [xlloop](http://xlloop.sourceforge.net) - `Python` - XLLoop is an open source framework for implementing Excel user-defined functions (UDFs) on a centralised server (a function server). [GitHub](https://github.com/poidasmith/xlloop)
- [xlloop](http://xlloop.sourceforge.net) - `Python` - XLLoop is an open source framework for implementing Excel user-defined functions (UDFs) on a centralised server (a function server). [GitHub](https://github.com/poidasmith/xlloop).
- [expy](http://www.bnikolic.co.uk/expy/expy.html) - `Python` - The ExPy add-in allows easy use of Python directly from within an Microsoft Excel spreadsheet, both to execute arbitrary code and to define new Excel functions.
- [pyxll](https://www.pyxll.com) - `Python` - PyXLL is an Excel add-in that enables you to extend Excel using nothing but Python code.
@@ -486,10 +486,10 @@ A curated list of insanely awesome libraries, packages and resources for Quants
## Cross-Language Frameworks
- [RunMat](https://runmat.org) - High performance, Open Source, MATLAB syntax runtime. [GitHub](https://github.com/runmat-org/runmat)
- [RunMat](https://runmat.org) - High performance, Open Source, MATLAB syntax runtime. [GitHub](https://github.com/runmat-org/runmat).
- [QuantLib](https://github.com/lballabio/QuantLib) - The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance.
- [QuantLibRisks](https://github.com/auto-differentiation/QuantLib-Risks-Cpp) - Fast risks with QuantLib in C++
- [XAD](https://github.com/auto-differentiation/xad) - Automatic Differentation (AAD) Library
- [QuantLibRisks](https://github.com/auto-differentiation/QuantLib-Risks-Cpp) - Fast risks with QuantLib in C++.
- [XAD](https://github.com/auto-differentiation/xad) - Automatic Differentation (AAD) Library.
- [QuantLib](https://github.com/lballabio/QuantLib) - The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance.
- QuantLibRisks - Fast risks with QuantLib in [Python](https://pypi.org/project/QuantLib-Risks/) and [C++](https://github.com/auto-differentiation/QuantLib-Risks-Cpp)
- XAD - Automatic Differentiation (AAD) Library in [Python](https://pypi.org/project/xad/) and [C++](https://github.com/auto-differentiation/xad/)
@@ -500,23 +500,23 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [QLNet](https://github.com/amaggiulli/qlnet) - .Net port.
- [PyQL](https://github.com/enthought/pyql) - Python port.
- [QuantLib.jl](https://github.com/pazzo83/QuantLib.jl) - Julia port.
- [QuantLib-Python Documentation](https://quantlib-python-docs.readthedocs.io/) - Documentation for the Python bindings for the QuantLib library
- [TA-Lib](https://ta-lib.org) - perform technical analysis of financial market data. [GitHub](https://github.com/TA-Lib/ta-lib)
- [ta-lib-python](https://github.com/TA-Lib/ta-lib-python)
- [ta-lib](https://github.com/TA-Lib/ta-lib)
- [QuantLib-Python Documentation](https://quantlib-python-docs.readthedocs.io/) - Documentation for the Python bindings for the QuantLib library.
- [TA-Lib](https://ta-lib.org) - perform technical analysis of financial market data. [GitHub](https://github.com/TA-Lib/ta-lib).
- [ta-lib-python](https://github.com/TA-Lib/ta-lib-python).
- [ta-lib](https://github.com/TA-Lib/ta-lib).
- [RunMat](https://github.com/runmat-org/runmat) - Rust runtime for MATLAB-syntax array math with automatic CPU/GPU execution and fused kernels for quant simulations.
## Reproducing Works, Training & Books
- [Special-Relativity-in-Financial-Modeling](https://github.com/Mattbusel/Special-Relativity-in-Financial-Modeling) - C++20 implementation of special-relativistic geometry applied to OHLCV data: Lorentz factors, spacetime intervals, Christoffel symbols, and geodesic deviation signals from live market data. DOI: 10.5281/zenodo.18639919
- [Special-Relativity-in-Financial-Modeling](https://github.com/Mattbusel/Special-Relativity-in-Financial-Modeling) - C++20 implementation of special-relativistic geometry applied to OHLCV data: Lorentz factors, spacetime intervals, Christoffel symbols, and geodesic deviation signals from live market data. DOI: 10.5281/zenodo.18639919.
- [Auto-Differentiation Website](https://auto-differentiation.github.io/) - Background and resources on Automatic Differentiation (AD) / Adjoint Algorithmic Differentitation (AAD).
- [Derman Papers](https://github.com/MarcosCarreira/DermanPapers) - Notebooks that replicate original quantitative finance papers from Emanuel Derman.
- [volatility-trading](https://github.com/jasonstrimpel/volatility-trading) - A complete set of volatility estimators based on Euan Sinclair's Volatility Trading.
- [quant](https://github.com/paulperry/quant) - Quantitative Finance and Algorithmic Trading exhaust; mostly ipython notebooks based on Quantopian, Zipline, or Pandas.
- [fecon235](https://github.com/rsvp/fecon235) - Open source project for software tools in financial economics. Many jupyter notebook to verify theoretical ideas and practical methods interactively.
- [Quantitative-Notebooks](https://github.com/LongOnly/Quantitative-Notebooks) - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
- [QuantEcon](https://quantecon.org/) - Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks
- [FinanceHub](https://github.com/Finance-Hub/FinanceHub) - Resources for Quantitative Finance
- [Quantitative-Notebooks](https://github.com/LongOnly/Quantitative-Notebooks) - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy.
- [QuantEcon](https://quantecon.org/) - Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks.
- [FinanceHub](https://github.com/Finance-Hub/FinanceHub) - Resources for Quantitative Finance.
- [Python_Option_Pricing](https://github.com/dedwards25/Python_Option_Pricing) - An library to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.
- [python-training](https://github.com/jpmorganchase/python-training) - J.P. Morgan's Python training for business analysts and traders.
- [Stock_Analysis_For_Quant](https://github.com/LastAncientOne/Stock_Analysis_For_Quant) - Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.
@@ -527,7 +527,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [Computational-Finance-Course](https://github.com/LechGrzelak/Computational-Finance-Course) - Materials for the course of Computational Finance.
- [Machine-Learning-for-Asset-Managers](https://github.com/emoen/Machine-Learning-for-Asset-Managers) - Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
- [Python-for-Finance-Cookbook](https://github.com/PacktPublishing/Python-for-Finance-Cookbook) - Python for Finance Cookbook, published by Packt.
- [modelos_vol_derivativos](https://github.com/ysaporito/modelos_vol_derivativos) - "Modelos de Volatilidade para Derivativos" book's Jupyter notebooks
- [modelos_vol_derivativos](https://github.com/ysaporito/modelos_vol_derivativos) - "Modelos de Volatilidade para Derivativos" book's Jupyter notebooks.
- [NMOF](https://github.com/enricoschumann/NMOF) - Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658).
- [py4fi2nd](https://github.com/yhilpisch/py4fi2nd) - Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.
- [aiif](https://github.com/yhilpisch/aiif) - Jupyter Notebooks and code for the book Artificial Intelligence in Finance (O'Reilly) by Yves Hilpisch.
@@ -542,13 +542,13 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [Deep Learning Machine Learning Stock](https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock) - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.
- [Technical Analysis and Feature Engineering](https://github.com/jo-cho/Technical_Analysis_and_Feature_Engineering) - Feature Engineering and Feature Importance of Machine Learning in Financial Market.
- [Differential Machine Learning and Axes that matter by Brian Huge and Antoine Savine](https://github.com/differential-machine-learning/notebooks) - Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.
- [systematictradingexamples](https://github.com/robcarver17/systematictradingexamples) - Examples of code related to book [Systematic Trading](www.systematictrading.org) and [blog](http://qoppac.blogspot.com)
- [systematictradingexamples](https://github.com/robcarver17/systematictradingexamples) - Examples of code related to book [Systematic Trading](www.systematictrading.org) and [blog](http://qoppac.blogspot.com).
- [pysystemtrade_examples](https://github.com/robcarver17/pysystemtrade_examples) - Examples using pysystemtrade for Robert Carver's [blog](http://qoppac.blogspot.com).
- [ML_Finance_Codes](https://github.com/mfrdixon/ML_Finance_Codes) - Machine Learning in Finance: From Theory to Practice Book
- [Hands-On Machine Learning for Algorithmic Trading](https://github.com/packtpublishing/hands-on-machine-learning-for-algorithmic-trading) - Hands-On Machine Learning for Algorithmic Trading, published by Packt
- [financialnoob-misc](https://github.com/financialnoob/misc) - Codes from @financialnoob's posts
- [ML_Finance_Codes](https://github.com/mfrdixon/ML_Finance_Codes) - Machine Learning in Finance: From Theory to Practice Book.
- [Hands-On Machine Learning for Algorithmic Trading](https://github.com/packtpublishing/hands-on-machine-learning-for-algorithmic-trading) - Hands-On Machine Learning for Algorithmic Trading, published by Packt.
- [financialnoob-misc](https://github.com/financialnoob/misc) - Codes from @financialnoob's posts.
- [MesoSim Options Trading Strategy Library](https://github.com/deltaray-io/strategy-library) - Free and public Options Trading strategy library for MesoSim.
- [Quant-Finance-With-Python-Code](https://github.com/lingyixu/Quant-Finance-With-Python-Code) - Repo for code examples in Quantitative Finance with Python by Chris Kelliher
- [Quant-Finance-With-Python-Code](https://github.com/lingyixu/Quant-Finance-With-Python-Code) - Repo for code examples in Quantitative Finance with Python by Chris Kelliher.
- [QuantFinanceTraining](https://github.com/JoaoJungblut/QuantFinanceTraining) - This repository contains codes that were executed during my training in the CQF (Certificate in Quantitative Finance). The codes are organized by class, facilitating navigation and reference.
- [Statistical-Learning-based-Portfolio-Optimization](https://github.com/YannickKae/Statistical-Learning-based-Portfolio-Optimization) - This R Shiny App utilizes the Hierarchical Equal Risk Contribution (HERC) approach, a modern portfolio optimization method developed by Raffinot (2018).
- [book_irds3](https://github.com/attack68/book_irds3) - Code repository for Pricing and Trading Interest Rate Derivatives.
@@ -559,7 +559,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [RoughVolatilityWorkshop](https://github.com/jgatheral/RoughVolatilityWorkshop) - 2024 QuantMind's Rough Volatility Workshop lectures.
- [AFML](https://github.com/boyboi86/AFML) - All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.
- [AlgoTradingLib](https://github.com/usdaud/algotradinglib.github.io) - A catalog of algorithmic trading libraries, frameworks, strategies, and educational materials.
- [Portfolio Optimization Book](https://portfoliooptimizationbook.com/) - Prof. Daniel Palomar's Portfolio Optimization Book. [GitHub](https://github.com/dppalomar/pob)
- [Portfolio Optimization Book](https://portfoliooptimizationbook.com/) - Prof. Daniel Palomar's Portfolio Optimization Book. [GitHub](https://github.com/dppalomar/pob).
## Commercial & Proprietary Services