- [scipy](https://www.scipy.org) - SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.
- [pandas](https://pandas.pydata.org) - 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.
- [quantdsl](https://github.com/johnbywater/quantdsl) - Domain specific language for quantitative analytics in finance and trading.
- [statistics](https://docs.python.org/3/library/statistics.html) - Builtin Python library for all basic statistical calculations.
- [sympy](https://www.sympy.org/) - SymPy is a Python library for symbolic mathematics.
- [pymc3](https://docs.pymc.io/) - Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano.
- [QuantPy](https://github.com/jsmidt/QuantPy) - A framework for quantitative finance In python.
- [Finance-Python](https://github.com/alpha-miner/Finance-Python) - Python tools for Finance.
- [ffn](https://github.com/pmorissette/ffn) - A financial function library for Python.
- [pynance](https://pynance.net) - PyNance is open-source software for retrieving, analysing and visualizing data from stock and derivatives markets.
- [tia](https://github.com/bpsmith/tia) - Toolkit for integration and analysis.
- [hasura/base-python-dash](https://platform.hasura.io/hub/projects/hasura/base-python-dash) - Hasura quickstart to deploy Dash framework. Written on top of Flask, Plotly.js, and React.js, Dash is ideal for building data visualization apps with highly custom user interfaces in pure Python.
- [hasura/base-python-bokeh](https://platform.hasura.io/hub/projects/hasura/base-python-bokeh) - Hasura quickstart to visualize data with bokeh library.
- [pysabr](https://github.com/ynouri/pysabr) - SABR model Python implementation.
- [FinancePy](https://github.com/domokane/FinancePy) - A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
- [willowtree](https://github.com/federicomariamassari/willowtree) - Robust and flexible Python implementation of the willow tree lattice for derivatives pricing.
- [financial-engineering](https://github.com/federicomariamassari/financial-engineering) - Applications of Monte Carlo methods to financial engineering projects, in Python.
- [optlib](https://github.com/dbrojas/optlib) - A library for financial options pricing written in Python.
- [QuantSoftware Toolkit](https://github.com/QuantSoftware/QuantSoftwareToolkit) - Python-based open source software framework designed to support portfolio construction and management.
- [quantitative](https://github.com/jeffrey-liang/quantitative) - Quantitative finance, and backtesting library.
- [analyzer](https://github.com/llazzaro/analyzer) - Python framework for real-time financial and backtesting trading strategies.
- [bt](https://github.com/pmorissette/bt) - Flexible Backtesting for Python.
- [backtrader](https://github.com/backtrader/backtrader) - Python Backtesting library for trading strategies.
- [Pandas TA](https://github.com/twopirllc/pandas-ta) - Pandas TA is an easy to use Python 3 Pandas Extension with 115+ Indicators. Easily build Custom Strategies.
- [zvt](https://github.com/zvtvz/zvt) - the project using sql,pandas to provide an uniform and extendable way to record data,computing factors,select securites, backtesting,realtime trading and it could show all of them in clearly charts in realtime.
- [PyPortfolioOpt](https://github.com/robertmartin8/PyPortfolioOpt) - Financial portfolio optimisation in python, including classical efficient frontier and advanced methods.
- [pyqstrat](https://github.com/abbass2/pyqstrat) - A fast, extensible, transparent python library for backtesting quantitative strategies.
- [NowTrade](https://github.com/edouardpoitras/NowTrade) - Python library for backtesting technical/mechanical strategies in the stock and currency markets.
- [pinkfish](https://github.com/fja05680/pinkfish) - A backtester and spreadsheet library for security analysis.
- [algorithmic-trading-with-python](https://github.com/chrisconlan/algorithmic-trading-with-python) - Free `pandas` and `scikit-learn` resources for trading simulation, backtesting, and machine learning on financial data.
- [Qlib](https://github.com/microsoft/qlib) - 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) - Code and resources for Machine Learning for Algorithmic Trading
- [FinRL-Library](https://github.com/AI4Finance-LLC/FinRL-Library) - A Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020.
- [OctoBot](https://github.com/Drakkar-Software/OctoBot) - Open source cryptocurrency trading bot for high frequency, arbitrage, TA and social trading with an advanced web interface.
- [finance](https://pypi.org/project/finance/) - Financial Risk Calculations. Optimized for ease of use through class construction and operator overload.
- [qfrm](https://pypi.org/project/qfrm/) - Quantitative Financial Risk Management: awesome OOP tools for measuring, managing and visualizing risk of financial instruments and portfolios.
- [visualize-wealth](https://github.com/benjaminmgross/visualize-wealth) - Portfolio construction and quantitative analysis.
- [VisualPortfolio](https://github.com/wegamekinglc/VisualPortfolio) - This tool is used to visualize the perfomance of a portfolio.
- [Facebook Prophet](https://github.com/facebook/prophet) - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
- [googlefinance](https://github.com/hongtaocai/googlefinance) - Python module to get real-time stock data from Google Finance API.
- [yahoo-finance](https://github.com/lukaszbanasiak/yahoo-finance) - Python module to get stock data from Yahoo! Finance.
- [pandas-datareader](https://github.com/pydata/pandas-datareader) - Python module to get data from various sources (Google Finance, Yahoo Finance, FRED, OECD, Fama/French, World Bank, Eurostat...) into Pandas datastructures such as DataFrame, Panel with a caching mechanism.
- [pandas-finance](https://github.com/davidastephens/pandas-finance) - High level API for access to and analysis of financial data.
- [pyhoofinance](https://github.com/innes213/pyhoofinance) - Rapidly queries Yahoo Finance for multiple tickers and returns typed data for analysis.
- [yfinanceapi](https://github.com/Karthik005/yfinanceapi) - Finance API for Python.
- [yql-finance](https://github.com/slawek87/yql-finance) - yql-finance is simple and fast. API returns stock closing prices for current period of time and current stock ticker (i.e. APPL, GOOGL).
- [ystockquote](https://github.com/cgoldberg/ystockquote) - Retrieve stock quote data from Yahoo Finance.
- [wallstreet](https://github.com/mcdallas/wallstreet) - Real time stock and option data.
- [stock_extractor](https://github.com/ZachLiuGIS/stock_extractor) - General Purpose Stock Extractors from Online Resources.
- [Stockex](https://github.com/cttn/Stockex) - Python wrapper for Yahoo! Finance API.
- [finsymbols](https://github.com/skillachie/finsymbols) - Obtains stock symbols and relating information for SP500, AMEX, NYSE, and NASDAQ.
- [FRB](https://github.com/avelkoski/FRB) - Python Client for FRED® API.
- [inquisitor](https://github.com/econdb/inquisitor) - Python Interface to Econdb.com API.
- [chinesestockapi](https://pypi.org/project/chinesestockapi/) - Python API to get Chinese stock price.
- [exchange](https://github.com/akarat/exchange) - Get current exchange rate.
- [ticks](https://github.com/jamescnowell/ticks) - Simple command line tool to get stock ticker data.
- [pybbg](https://github.com/bpsmith/pybbg) - Python interface to Bloomberg COM APIs.
- [ccy](https://github.com/lsbardel/ccy) - Python module for currencies.
- [tushare](https://pypi.org/project/tushare/) - A utility for crawling historical and Real-time Quotes data of China stocks.
- [jsm](https://pypi.org/project/jsm/) - Get the japanese stock market data.
- [cn_stock_src](https://github.com/jealous/cn_stock_src) - Utility for retrieving basic China stock data from different sources.
- [coinmarketcap](https://github.com/barnumbirr/coinmarketcap) - Python API for coinmarketcap.
- [after-hours](https://github.com/datawrestler/after-hours) - Obtain pre market and after hours stock prices for a given symbol.
- [bronto-python](https://pypi.org/project/bronto-python/) - Bronto API Integration for Python.
- [pytdx](https://github.com/rainx/pytdx) - Python Interface for retrieving chinese stock realtime quote data from TongDaXin Nodes.
- [pdblp](https://github.com/matthewgilbert/pdblp) - A simple interface to integrate pandas and the Bloomberg Open API.
- [tiingo](https://github.com/hydrosquall/tiingo-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 Interface for retrieving real-time and historical prices and equities data from The Investor's Exchange.
- [pyEX](https://github.com/timkpaine/pyEX) - 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 interface for retrieving real-time and historical prices from Alpaca API as well as trade execution.
- [akshare](https://github.com/jindaxiang/akshare) - AkShare is an elegant and simple financial data interface library for Python, built for human beings! <https://akshare.readthedocs.io>
- [xlwt](https://github.com/python-excel/xlwt) - Library to create spreadsheet files compatible with MS Excel 97/2000/XP/2003 XLS files, on any platform.
- [DataNitro](https://datanitro.com/) - DataNitro also offers full-featured Python-Excel integration, including UDFs. Trial downloads are available, but users must purchase a license.
- [xlloop](http://xlloop.sourceforge.net) - XLLoop is an open source framework for implementing Excel user-defined functions (UDFs) on a centralised server (a function server).
- [expy](http://www.bnikolic.co.uk/expy/expy.html) - 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) - PyXLL is an Excel add-in that enables you to extend Excel using nothing but Python code.
- [xts](https://cran.r-project.org/web/packages/xts/index.html) - 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://cran.r-project.org/web/packages/data.table/index.html) - 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.
- [TSdbi](http://tsdbi.r-forge.r-project.org/) - Provides a common interface to time series databases.
- [tseries](https://cran.r-project.org/web/packages/tseries/index.html) - Time Series Analysis and Computational Finance.
- [zoo](https://cran.r-project.org/web/packages/zoo/index.html) - S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations).
- [tis](https://cran.r-project.org/web/packages/tis/index.html) - Functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.
- [tfplot](https://cran.r-project.org/web/packages/tfplot/index.html) - Utilities for simple manipulation and quick plotting of time series data.
- [tframe](https://cran.r-project.org/web/packages/tframe/index.html) - A kernel of functions for programming time series methods in a way that is relatively independently of the representation of time.
### Data Sources
- [IBrokers](https://cran.r-project.org/web/packages/IBrokers/index.html) - Provides native R access to Interactive Brokers Trader Workstation API.
- [Rblpapi](https://cran.r-project.org/web/packages/Rblpapi/index.html) - An R Interface to 'Bloomberg' is provided via the 'Blp API'.
- [Quandl](https://www.quandl.com/tools/r) - Get Financial Data Directly Into R.
- [GetTDData](https://cran.r-project.org/web/packages/GetTDData/index.html) - Downloads and aggregates data for Brazilian government issued bonds directly from the website of Tesouro Direto.
- [GetHFData](https://cran.r-project.org/web/packages/GetHFData/index.html) - Downloads and aggregates high frequency trading data for Brazilian instruments directly from Bovespa ftp site.
- [Reddit WallstreetBets API](https://dashboard.nbshare.io/apps/reddit/api/) - Provides daily top 50 stocks from reddit (subreddit) Wallstreetbets and their sentiments via the API
- [portfolioSim](https://cran.r-project.org/web/packages/portfolioSim/index.html) - Framework for simulating equity portfolio strategies.
- [sparseIndexTracking](https://github.com/dppalomar/sparseIndexTracking) - Portfolio design to track an index.
- [covFactorModel](https://github.com/dppalomar/covFactorModel) - Covariance matrix estimation via factor models.
- [riskParityPortfolio](https://github.com/dppalomar/riskParityPortfolio) - Blazingly fast design of risk parity portfolios.
- [sde](https://cran.r-project.org/web/packages/sde/index.html) - Simulation and Inference for Stochastic Differential Equations.
- [YieldCurve](https://cran.r-project.org/web/packages/YieldCurve/index.html) - Modelling and estimation of the yield curve.
- [SmithWilsonYieldCurve](https://cran.r-project.org/web/packages/SmithWilsonYieldCurve/index.html) - Constructs a yield curve by the Smith-Wilson method from a table of LIBOR and SWAP rates.
- [ycinterextra](https://cran.r-project.org/web/packages/ycinterextra/index.html) - Yield curve or zero-coupon prices interpolation and extrapolation.
- [AmericanCallOpt](https://cran.r-project.org/web/packages/AmericanCallOpt/index.html) - This package includes pricing function for selected American call options with underlying assets that generate payouts.
- [VarSwapPrice](https://cran.r-project.org/web/packages/VarSwapPrice/index.html) - Pricing a variance swap on an equity index.
- [RND](https://cran.r-project.org/web/packages/RND/index.html) - Risk Neutral Density Extraction Package.
- [LSMonteCarlo](https://cran.r-project.org/web/packages/LSMonteCarlo/index.html) - American options pricing with Least Squares Monte Carlo method.
- [OptHedging](https://cran.r-project.org/web/packages/OptHedging/index.html) - Estimation of value and hedging strategy of call and put options.
- [tvm](https://cran.r-project.org/web/packages/tvm/index.html) - Time Value of Money Functions.
- [OptionPricing](https://cran.r-project.org/web/packages/OptionPricing/index.html) - Option Pricing with Efficient Simulation Algorithms.
- [PerformanceAnalytics](https://cran.r-project.org/web/packages/PerformanceAnalytics/index.html) - Econometric tools for performance and risk analysis.
- [tibbletime](https://github.com/business-science/tibbletime) - Built on top of the tidyverse, tibbletime is an extension that allows for the creation of time aware tibbles through the setting of a time index.
- [matrixprofile](https://github.com/matrix-profile-foundation/matrixprofile) - Time series data mining library built on top of the novel Matrix Profile data structure and algorithms.
- [Workbench](https://github.com/fremantle-industries/workbench) - From Idea to Execution - Manage your trading operation across a globally distributed cluster
- [Kelp](https://github.com/stellar/kelp) - Kelp is an open-source Golang algorithmic cryptocurrency trading bot that runs on centralized exchanges and Stellar DEX (command-line usage and desktop GUI).
- [QuantConnect](https://github.com/QuantConnect/Lean) - Lean Engine is an open-source fully managed C# algorithmic trading engine built for desktop and cloud usage.
- [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.
- [FinanceHub](https://github.com/Finance-Hub/FinanceHub) - Resources for Quantitative Finance
- [Python_Option_Pricing](https://github.com/dedwards25/Python_Option_Pricing) - An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.
