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"text": "We as members, contributors, and leaders pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation.\nWe pledge to act and interact in ways that contribute to an open, welcoming, diverse, inclusive, and healthy community."
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"text": "Our Standards\nExamples of behavior that contributes to a positive environment for our community include:\n\nDemonstrating empathy and kindness toward other people\nBeing respectful of differing opinions, viewpoints, and experiences\nGiving and gracefully accepting constructive feedback\nAccepting responsibility and apologizing to those affected by our mistakes, and learning from the experience\nFocusing on what is best not just for us as individuals, but for the overall community\n\nExamples of unacceptable behavior include:\n\nThe use of sexualized language or imagery, and sexual attention or advances of any kind\nTrolling, insulting or derogatory comments, and personal or political attacks\nPublic or private harassment\nPublishing others’ private information, such as a physical or email address, without their explicit permission\nOther conduct which could reasonably be considered inappropriate in a professional setting"
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"text": "Enforcement Responsibilities\nCommunity leaders are responsible for clarifying and enforcing our standards of acceptable behavior and will take appropriate and fair corrective action in response to any behavior that they deem inappropriate, threatening, offensive, or harmful.\nCommunity leaders have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, and will communicate reasons for moderation decisions when appropriate."
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"text": "Enforcement\nInstances of abusive, harassing, or otherwise unacceptable behavior may be reported to the community leaders responsible for enforcement at awesom3quant@gmail.com. All complaints will be reviewed and investigated promptly and fairly.\nAll community leaders are obligated to respect the privacy and security of the reporter of any incident."
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"text": "Enforcement Guidelines\nCommunity leaders will follow these Community Impact Guidelines in determining the consequences for any action they deem in violation of this Code of Conduct:\n\n1. Correction\nCommunity Impact: Use of inappropriate language or other behavior deemed unprofessional or unwelcome in the community.\nConsequence: A private, written warning from community leaders, providing clarity around the nature of the violation and an explanation of why the behavior was inappropriate. A public apology may be requested.\n\n\n2. Warning\nCommunity Impact: A violation through a single incident or series of actions.\nConsequence: A warning with consequences for continued behavior. No interaction with the people involved, including unsolicited interaction with those enforcing the Code of Conduct, for a specified period of time. This includes avoiding interactions in community spaces as well as external channels like social media. Violating these terms may lead to a temporary or permanent ban.\n\n\n3. Temporary Ban\nCommunity Impact: A serious violation of community standards, including sustained inappropriate behavior.\nConsequence: A temporary ban from any sort of interaction or public communication with the community for a specified period of time. No public or private interaction with the people involved, including unsolicited interaction with those enforcing the Code of Conduct, is allowed during this period. Violating these terms may lead to a permanent ban.\n\n\n4. Permanent Ban\nCommunity Impact: Demonstrating a pattern of violation of community standards, including sustained inappropriate behavior, harassment of an individual, or aggression toward or disparagement of classes of individuals.\nConsequence: A permanent ban from any sort of public interaction within the community."
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"text": "Python\n\nNumerical Libraries & Data Structures\n\nnumpy - NumPy is the fundamental package for scientific computing with Python.\nscipy - SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.\npandas - 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.\nquantdsl - Domain specific language for quantitative analytics in finance and trading.\nstatistics - Builtin Python library for all basic statistical calculations.\nsympy - SymPy is a Python library for symbolic mathematics.\npymc3 - Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano.\n\n\n\nFinancial Instruments and Pricing\n\nPyQL - QuantLib’s Python port.\npyfin - Basic options pricing in Python. ARCHIVED\nvollib - vollib is a python library for calculating option prices, implied volatility and greeks.\nQuantPy - A framework for quantitative finance In python.\nFinance-Python - Python tools for Finance.\nffn - A financial function library for Python.\npynance - Lightweight Python library for assembling and analysing financial data.\ntia - Toolkit for integration and analysis.\nhasura/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.\nhasura/base-python-bokeh - Hasura quickstart to visualize data with bokeh library.\npysabr - SABR model Python implementation.\nFinancePy - A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.\ngs-quant - Python toolkit for quantitative finance\nwillowtree - Robust and flexible Python implementation of the willow tree lattice for derivatives pricing.\nfinancial-engineering - Applications of Monte Carlo methods to financial engineering projects, in Python.\noptlib - A library for financial options pricing written in Python.\ntf-quant-finance - High-performance TensorFlow library for quantitative finance.\nQ-Fin - A Python library for mathematical finance.\nQuantsbin - Tools for pricing and plotting of vanilla option prices, greeks and various other analysis around them.\nfinoptions - Complete python implementation of R package fOptions with partial implementation of fExoticOptions for pricing various options.\n\n\n\nIndicators\n\npandas_talib - A Python Pandas implementation of technical analysis indicators.\nfinta - Common financial technical analysis indicators implemented in Pandas.\nTulipy - Financial Technical Analysis Indicator Library (Python bindings for tulipindicators)\nlppls - A Python module for fitting the Log-Periodic Power Law Singularity (LPPLS) model.\n\n\n\nTrading & Backtesting\n\nBlankly - Fully integrated backtesting, paper trading, and live deployment.\nTA-Lib - Python wrapper for TA-Lib (http://ta-lib.org/).\nzipline - Pythonic algorithmic trading library.\nQuantSoftware Toolkit - Python-based open source software framework designed to support portfolio construction and management.\nquantitative - Quantitative finance, and backtesting library.\nanalyzer - Python framework for real-time financial and backtesting trading strategies.\nbt - Flexible Backtesting for Python.\nbacktrader - Python Backtesting library for trading strategies.\npythalesians - Python library to backtest trading strategies, plot charts, seamlessly download market data, analyse market patterns etc.\npybacktest - Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier.\npyalgotrade - Python Algorithmic Trading Library.\ntradingWithPython - A collection of functions and classes for Quantitative trading.\nPandas TA - Pandas TA is an easy to use Python 3 Pandas Extension with 115+ Indicators. Easily build Custom Strategies.\nta - Technical Analysis Library using Pandas (Python)\nalgobroker - This is an execution engine for algo trading.\npysentosa - Python API for sentosa trading system.\nfinmarketpy - Python library for backtesting trading strategies and analyzing financial markets.\nbinary-martingale - Computer program to automatically trade binary options martingale style.\nfooltrader - the project using big-data technology to provide an uniform way to analyze the whole market.\nzvt - 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.\npylivetrader - zipline-compatible live trading library.\npipeline-live - zipline’s pipeline capability with IEX for live trading.\nzipline-extensions - Zipline extensions and adapters for QuantRocket.\nmoonshot - Vectorized backtester and trading engine for QuantRocket based on Pandas.\nPyPortfolioOpt - Financial portfolio optimisation in python, including classical efficient frontier and advanced methods.\nEiten - 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.\nriskparity.py - fast and scalable design of risk parity portfolios with TensorFlow 2.0\nmlfinlab - Implementations regarding “Advances in Financial Machine Learning” by Marcos Lopez de Prado. (Feature Engineering, Financial Data Structures, Meta-Labeling)\npyqstrat - A fast, extensible, transparent python library for backtesting quantitative strategies.\nNowTrade - Python library for backtesting technical/mechanical strategies in the stock and currency markets.\npinkfish - A backtester and spreadsheet library for security analysis.\naat - Async Algorithmic Trading Engine\nBacktesting.py - Backtest trading strategies in Python\ncatalyst - An Algorithmic Trading Library for Crypto-Assets in Python\nquantstats - Portfolio analytics for quants, written in Python\nqtpylib - QTPyLib, Pythonic Algorithmic Trading http://qtpylib.io\nQuantdom - Python-based framework for backtesting trading strategies & analyzing financial markets [GUI :neckbeard:]\nfreqtrade - Free, open source crypto trading bot\nalgorithmic-trading-with-python - Free pandas and scikit-learn resources for trading simulation, backtesting, and machine learning on financial data.\nDeepDow - Portfolio optimization with deep learning\nQlib - 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.\nmachine-learning-for-trading - Code and resources for Machine Learning for Algorithmic Trading\nAlphaPy - Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost\njesse - An advanced crypto trading bot written in Python\nrqalpha - A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities.\nFinRL-Library - A Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020.\nbulbea - Deep Learning based Python Library for Stock Market Prediction and Modelling.\nib_nope - Automated trading system for NOPE strategy over IBKR TWS.\nOctoBot - Open source cryptocurrency trading bot for high frequency, arbitrage, TA and social trading with an advanced web interface.\nbta-lib - Technical Analysis library in pandas for backtesting algotrading and quantitative analysis.\nStock-Prediction-Models - Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations.\nTuneTA - TuneTA optimizes technical indicators using a distance correlation measure to a user defined target feature such as next day return.\nAutoTrader - A Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.\nfast-trade - A library built with backtest portability and performance in mind for backtest trading strategies.\nqf-lib - QF-Lib is a Python library that provides high quality tools for quantitative finance.\ntda-api - Gather data and trade equities, options, and ETFs via TDAmeritrade.\nvectorbt - Find your trading edge, using a powerful toolkit for backtesting, algorithmic trading, and research.\nLean - Lean Algorithmic Trading Engine by QuantConnect (Python, C#).\nfast-trade - Low code backtesting library utilizing pandas and technical analysis indicators.\n\n\n\nRisk Analysis\n\npyfolio - Portfolio and risk analytics in Python.\nempyrical - Common financial risk and performance metrics.\nfecon235 - Computational tools for financial economics include: Gaussian Mixture model of leptokurtotic risk, adaptive Boltzmann portfolios.\nfinance - Financial Risk Calculations. Optimized for ease of use through class construction and operator overload.\nqfrm - Quantitative Financial Risk Management: awesome OOP tools for measuring, managing and visualizing risk of financial instruments and portfolios.\nvisualize-wealth - Portfolio construction and quantitative analysis.\nVisualPortfolio - This tool is used to visualize the perfomance of a portfolio.\nuniversal-portfolios - Collection of algorithms for online portfolio selection.\nFinQuant - A program for financial portfolio management, analysis and optimisation.\nEmpyrial - Portfolio’s risk and performance analytics and returns predictions.\nrisktools - Risk tools for use within the crude and crude products trading space with partial implementation of R’s PerformanceAnalytics.\nRiskfolio-Lib - Portfolio Optimization and Quantitative Strategic Asset Allocation in Python.\n\n\n\nFactor Analysis\n\nalphalens - Performance analysis of predictive alpha factors.\nSpectre - GPU-accelerated Factors analysis library and Backtester\n\n\n\nTime Series\n\nARCH - ARCH models in Python.\nstatsmodels - Python module that allows users to explore data, estimate statistical models, and perform statistical tests.\ndynts - Python package for timeseries analysis and manipulation.\nPyFlux - Python library for timeseries modelling and inference (frequentist and Bayesian) on models.\ntsfresh - Automatic extraction of relevant features from time series.\nhasura/quandl-metabase - Hasura quickstart to visualize Quandl’s timeseries datasets with Metabase.\nFacebook Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.\ntsmoothie - A python library for time-series smoothing and outlier detection in a vectorized way.\npmdarima - A statistical library designed to fill the void in Python’s time series analysis capabilities, including the equivalent of R’s auto.arima function.\ngluon-ts - vProbabilistic time series modeling in Python.\n\n\n\nCalendars\n\nexchange_calendars - Stock Exchange Trading Calendars.\nbizdays - Business days calculations and utilities.\npandas_market_calendars - Exchange calendars to use with pandas for trading applications.\n\n\n\nData Sources\n\nyfinance - Yahoo! Finance market data downloader (+faster Pandas Datareader)\nfindatapy - Python library to download market data via Bloomberg, Quandl, Yahoo etc.\ngooglefinance - Python module to get real-time stock data from Google Finance API.\nyahoo-finance - Python module to get stock data from Yahoo! Finance.\npandas-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.\npandas-finance - High level API for access to and analysis of financial data.\npyhoofinance - Rapidly queries Yahoo Finance for multiple tickers and returns typed data for analysis.\nyfinanceapi - Finance API for Python.\nyql-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).\nystockquote - Retrieve stock quote data from Yahoo Finance.\nwallstreet - Real time stock and option data.\nstock_extractor - General Purpose Stock Extractors from Online Resources.\nStockex - Python wrapper for Yahoo! Finance API.\nfinsymbols - Obtains stock symbols and relating information for SP500, AMEX, NYSE, and NASDAQ.\nFRB - Python Client for FRED® API.\ninquisitor - Python Interface to Econdb.com API.\nyfi - Yahoo! YQL library.\nchinesestockapi - Python API to get Chinese stock price.\nexchange - Get current exchange rate.\nticks - Simple command line tool to get stock ticker data.\npybbg - Python interface to Bloomberg COM APIs.\nccy - Python module for currencies.\ntushare - A utility for crawling historical and Real-time Quotes data of China stocks.\njsm - Get the japanese stock market data.\ncn_stock_src - Utility for retrieving basic China stock data from different sources.\ncoinmarketcap - Python API for coinmarketcap.\nafter-hours - Obtain pre market and after hours stock prices for a given symbol.\nbronto-python - Bronto API Integration for Python.\npytdx - Python Interface for retrieving chinese stock realtime quote data from TongDaXin Nodes.\npdblp - A simple interface to integrate pandas and the Bloomberg Open API.\ntiingo - Python interface for daily composite prices/OHLC/Volume + Real-time News Feeds, powered by the Tiingo Data Platform.\niexfinance - Python Interface for retrieving real-time and historical prices and equities data from The Investor’s Exchange.\npyEX - Python interface to IEX with emphasis on pandas, support for streaming data, premium data, points data (economic, rates, commodities), and technical indicators.\nalpaca-trade-api - Python interface for retrieving real-time and historical prices from Alpaca API as well as trade execution.\nmetatrader5 - API Connector to MetaTrader 5 Terminal\nakshare - AkShare is an elegant and simple financial data interface library for Python, built for human beings! https://akshare.readthedocs.io\nyahooquery - Python interface for retrieving data through unofficial Yahoo Finance API.\ninvestpy - Financial Data Extraction from Investing.com with Python! https://investpy.readthedocs.io/\nyliveticker - Live stream of market data from Yahoo Finance websocket.\nbbgbridge - Easy to use Bloomberg Desktop API wrapper for Python.\nalpha_vantage - A python wrapper for Alpha Vantage API for financial data.\nFinanceDataReader - Open Source Financial data reader for U.S, Korean, Japanese, Chinese, Vietnamese Stocks\npystlouisfed - Python client for Federal Reserve Bank of St. Louis API - FRED, ALFRED, GeoFRED and FRASER.\npython-bcb - Python interface to Brazilian Central Bank web services.\n\n\n\nExcel Integration\n\nxlwings - Make Excel fly with Python.\nopenpyxl - Read/Write Excel 2007 xlsx/xlsm files.\nxlrd - Library for developers to extract data from Microsoft Excel spreadsheet files.\nxlsxwriter - Write files in the Excel 2007+ XLSX file format.\nxlwt - Library to create spreadsheet files compatible with MS Excel 97/2000/XP/2003 XLS files, on any platform.\nDataNitro - DataNitro also offers full-featured Python-Excel integration, including UDFs. Trial downloads are available, but users must purchase a license.\nxlloop - XLLoop is an open source framework for implementing Excel user-defined functions (UDFs) on a centralised server (a function server).\nexpy - 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.\npyxll - PyXLL is an Excel add-in that enables you to extend Excel using nothing but Python code.\n\n\n\nVisualization\n\nD-Tale - Visualizer for pandas dataframes and xarray datasets.\nmplfinance - matplotlib utilities for the visualization, and visual analysis, of financial data.\nfinplot - Performant and effortless finance plotting for Python.\nfinvizfinance - Finviz analysis python library."
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"text": "R\n\nNumerical Libraries & Data Structures\n\nxts - 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.\ndata.table - 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.\nsparseEigen - Sparse pricipal component analysis.\nTSdbi - Provides a common interface to time series databases.\ntseries - Time Series Analysis and Computational Finance.\nzoo - S3 Infrastructure for Regular and Irregular Time Series (Z’s Ordered Observations).\ntis - Functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.\ntfplot - Utilities for simple manipulation and quick plotting of time series data.\ntframe - A kernel of functions for programming time series methods in a way that is relatively independently of the representation of time.\n\n\n\nData Sources\n\nIBrokers - Provides native R access to Interactive Brokers Trader Workstation API.\nRblpapi - An R Interface to ‘Bloomberg’ is provided via the ‘Blp API’.\nQuandl - Get Financial Data Directly Into R.\nRbitcoin - Unified markets API interface (bitstamp, kraken, btce, bitmarket).\nGetTDData - Downloads and aggregates data for Brazilian government issued bonds directly from the website of Tesouro Direto.\nGetHFData - Downloads and aggregates high frequency trading data for Brazilian instruments directly from Bovespa ftp site.\nReddit WallstreetBets API - Provides daily top 50 stocks from reddit (subreddit) Wallstreetbets and their sentiments via the API.\ntd - Interfaces the ‘twelvedata’ API for stocks and (digital and standard) currencies.\nrbcb - R interface to Brazilian Central Bank web services.\n\n\n\nFinancial Instruments and Pricing\n\nRQuantLib - RQuantLib connects GNU R with QuantLib.\nquantmod - Quantitative Financial Modelling Framework.\nRmetrics - The premier open source software solution for teaching and training quantitative finance.\n\nfAsianOptions - EBM and Asian Option Valuation.\nfAssets - Analysing and Modelling Financial Assets.\nfBasics - Markets and Basic Statistics.\nfBonds - Bonds and Interest Rate Models.\nfExoticOptions - Exotic Option Valuation.\nfOptions - Pricing and Evaluating Basic Options.\nfPortfolio - Portfolio Selection and Optimization.\n\nportfolio - Analysing equity portfolios.\nsparseIndexTracking - Portfolio design to track an index.\ncovFactorModel - Covariance matrix estimation via factor models.\nriskParityPortfolio - Blazingly fast design of risk parity portfolios.\nsde - Simulation and Inference for Stochastic Differential Equations.\nYieldCurve - Modelling and estimation of the yield curve.\nSmithWilsonYieldCurve - Constructs a yield curve by the Smith-Wilson method from a table of LIBOR and SWAP rates.\nycinterextra - Yield curve or zero-coupon prices interpolation and extrapolation.\nAmericanCallOpt - This package includes pricing function for selected American call options with underlying assets that generate payouts.\nVarSwapPrice - Pricing a variance swap on an equity index.\nRND - Risk Neutral Density Extraction Package.\nLSMonteCarlo - American options pricing with Least Squares Monte Carlo method.\nOptHedging - Estimation of value and hedging strategy of call and put options.\ntvm - Time Value of Money Functions.\nOptionPricing - Option Pricing with Efficient Simulation Algorithms.\ncredule - Credit Default Swap Functions.\nderivmkts - Functions and R Code to Accompany Derivatives Markets.\nFinCal - Package for time value of money calculation, time series analysis and computational finance.\nr-quant - R code for quantitative analysis in finance.\noptions.studies - options trading studies functions for use with options.data package and shiny.\nPortfolioAnalytics - Portfolio Analysis, Including Numerical Methods for Optimizationof Portfolios.\nfmbasics - Financial Market Building Blocks.\nR-fixedincome - Fixed income tools for R.\n\n\n\nTrading\n\nbacktest - Exploring Portfolio-Based Conjectures About Financial Instruments.\npa - Performance Attribution for Equity Portfolios.\nTTR - Technical Trading Rules.\nQuantTools - Enhanced Quantitative Trading Modelling.\nblotter - 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.\n\n\n\nBacktesting\n\nquantstrat - 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.\n\n\n\nRisk Analysis\n\nPerformanceAnalytics - Econometric tools for performance and risk analysis.\n\n\n\nFactor Analysis\n\nFactorAnalytics - 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.\nExpected Returns - Solutions for enhancing portfolio diversification and replications of seminal papers with R, most of which are discussed in one of the best investment references of the recent decade, Expected Returns: An Investors Guide to Harvesting Market Rewards by Antti Ilmanen.\n\n\n\nTime Series\n\ntseries - Time Series Analysis and Computational Finance.\nfGarch - Rmetrics - Autoregressive Conditional Heteroskedastic Modelling.\ntimeSeries - Rmetrics - Financial Time Series Objects.\nrugarch - Univariate GARCH Models.\nrmgarch - Multivariate GARCH Models.\ntidypredict - Run predictions inside the database https://tidypredict.netlify.com/.\ntidyquant - Bringing financial analysis to the tidyverse.\ntimetk - A toolkit for working with time series in R.\ntibbletime - 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.\nmatrixprofile - Time series data mining library built on top of the novel Matrix Profile data structure and algorithms.\ngarchmodels - A parsnip backend for GARCH models.\n\n\n\nCalendars\n\ntimeDate - Chronological and Calendar Objects\nbizdays - Business days calculations and utilities"
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"text": "Julia\n\nQuantLib.jl - Quantlib implementation in pure Julia.\nIto.jl - A Julia package for quantitative finance.\nTALib.jl - A Julia wrapper for TA-Lib.\nMiletus.jl - A financial contract definition, modeling language, and valuation framework.\nTemporal.jl - Flexible and efficient time series class & methods.\nIndicators.jl - Financial market technical analysis & indicators on top of Temporal.\nStrategems.jl - Quantitative systematic trading strategy development and backtesting.\nTimeSeries.jl - Time series toolkit for Julia.\nMarketTechnicals.jl - Technical analysis of financial time series on top of TimeSeries.\nMarketData.jl - Time series market data.\nTimeFrames.jl - A Julia library that defines TimeFrame (essentially for resampling TimeSeries)."
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"text": "JavaScript\n\nfinance.js - A JavaScript library for common financial calculations.\nportfolio-allocation - PortfolioAllocation is a JavaScript library designed to help constructing financial portfolios made of several assets: bonds, commodities, cryptocurrencies, currencies, exchange traded funds (ETFs), mutual funds, stocks…\nGhostfolio - Wealth management software to keep track of financial assets like stocks, ETFs or cryptocurrencies and make solid, data-driven investment decisions.\nIndicatorTS - Indicator is a TypeScript module providing various stock technical analysis indicators, strategies, and a backtest framework for trading.\nccxt - A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges.\n\n\nData Visualization\n\nQUANTAXIS_Webkit - An awesome visualization center based on quantaxis."
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"text": "Scala\n\nQuantScale - Scala Quantitative Finance Library.\nScala Quant - Scala library for working with stock data from IFTTT recipes or Google Finance."
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"text": "Elixir/Erlang\n\nTai - Open Source composable, real time, market data and trade execution toolkit.\nWorkbench - From Idea to Execution - Manage your trading operation across a globally distributed cluster\nProp - An open and opinionated trading platform using productive & familiar open source libraries and tools for strategy research, execution and operation."
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"text": "Golang\n\nKelp - Kelp is an open-source Golang algorithmic cryptocurrency trading bot that runs on centralized exchanges and Stellar DEX (command-line usage and desktop GUI).\nmarketstore - DataFrame Server for Financial Timeseries Data.\nIndicatorGo - IndicatorGo is a Golang module providing various stock technical analysis indicators, strategies, and a backtest framework for trading."
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"text": "CPP\n\nTradeFrame - 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 calculation library."
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"text": "Frameworks\n\nQuantLib - The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance.\n\nJQuantLib - Java port.\nRQuantLib - R port.\nQuantLibAddin - Excel support.\nQuantLibXL - Excel support.\nQLNet - .Net port.\nPyQL - Python port.\nQuantLib.jl - Julia port.\n\nTA-Lib - perform technical analysis of financial market data.\nPortfolio Optimizer - Portfolio Optimizer is a Web API for portfolio analysis and optimization."
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"text": "CSharp\n\nQuantConnect - Lean Engine is an open-source fully managed C# algorithmic trading engine built for desktop and cloud usage.\nStockSharp - Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).\nTDAmeritrade.DotNetCore - Free, open-source .NET Client for the TD Ameritrade Trading Platform. Helps developers integrate TD Ameritrade API into custom trading solutions."
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"text": "Rust\n\nQuantMath - Financial maths library for risk-neutral pricing and risk"
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"text": "Reproducing Works, Training & Books\n\nDerman Papers - Notebooks that replicate original quantitative finance papers from Emanuel Derman.\nML-Quant - Top Quant resources like ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos, and Blogs.\nvolatility-trading - A complete set of volatility estimators based on Euan Sinclair’s Volatility Trading.\nquant - Quantitative Finance and Algorithmic Trading exhaust; mostly ipython notebooks based on Quantopian, Zipline, or Pandas.\nfecon235 - Open source project for software tools in financial economics. Many jupyter notebook to verify theoretical ideas and practical methods interactively.\nQuantitative-Notebooks - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy\nQuantEcon - Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks\nFinanceHub - Resources for Quantitative Finance\nPython_Option_Pricing - An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.\npython-training - J.P. Morgan’s Python training for business analysts and traders.\nStock_Analysis_For_Quant - Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.\nalgorithmic-trading-with-python - Source code for Algorithmic Trading with Python (2020) by Chris Conlan.\nMEDIUM_NoteBook - Repository containing notebooks of cerlymarco’s posts on Medium.\nQuantFinance - Training materials in quantitative finance.\nMarketAnalysis - Implementing many different methods and popular analysis tools in Python.\nIPythonScripts - Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning.\nComputational-Finance-Course - Materials for the course of Computational Finance.\nMachine-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.\nPython-for-Finance-Cookbook - Python for Finance Cookbook, published by Packt.\nmodelos_vol_derivativos - “Modelos de Volatilidade para Derivativos” book’s Jupyter notebooks\nNMOF - 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).\npy4fi2nd - Jupyter Notebooks and code for Python for Finance (2nd ed., O’Reilly) by Yves Hilpisch.\naiif - Jupyter Notebooks and code for the book Artificial Intelligence in Finance (O’Reilly) by Yves Hilpisch.\npy4at - Jupyter Notebooks and code for the book Python for Algorithmic Trading (O’Reilly) by Yves Hilpisch.\ndawp - Jupyter Notebooks and code for Derivatives Analytics with Python (Wiley Finance) by Yves Hilpisch.\ndx - DX Analytics | Financial and Derivatives Analytics with Python.\nQuantFinanceBook - Quantitative Finance book.\nrough_bergomi - A Python implementation of the rough Bergomi model.\nfrh-fx - A python implementation of the fast-reversion Heston model of Mechkov for FX purposes.\nvalue-investing-studies - A collection of data analysis studies that examine the performance and characteristics of value investing over long periods of time.\nmachine-learning-asset-management - Machine Learning in Asset Management (by @firmai).\nDeep-Learning-Machine-Learning-Stock - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.\nTechnical_Analysis_and_Feature_Engineering - Feature Engineering and Feature Importance of Machine Learning in Financial Market."
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"text": "project\nsection\nlast_commit\nurl\ndescription\ngithub\ncran\nrepo\n\n\n\n\nnumpy\nPython > Numerical Libraries & Data Structures\n\nhttps://www.numpy.org\nNumPy is the fundamental package for scientific computing with Python.\nFalse\nFalse\n\n\n\nscipy\nPython > Numerical Libraries & Data Structures\n\nhttps://www.scipy.org\nSciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.\nFalse\nFalse\n\n\n\npandas\nPython > Numerical Libraries & Data Structures\n\nhttps://pandas.pydata.org\npandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.\nFalse\nFalse\n\n\n\nquantdsl\nPython > Numerical Libraries & Data Structures\n2017-10-26\nhttps://github.com/johnbywater/quantdsl\nDomain specific language for quantitative analytics in finance and trading.\nTrue\nFalse\njohnbywater/quantdsl\n\n\nstatistics\nPython > Numerical Libraries & Data Structures\n\nhttps://docs.python.org/3/library/statistics.html\nBuiltin Python library for all basic statistical calculations.\nFalse\nFalse\n\n\n\nsympy\nPython > Numerical Libraries & Data Structures\n\nhttps://www.sympy.org/\nSymPy is a Python library for symbolic mathematics.\nFalse\nFalse\n\n\n\npymc3\nPython > Numerical Libraries & Data Structures\n\nhttps://docs.pymc.io/\nProbabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano.\nFalse\nFalse\n\n\n\nPyQL\nPython > Financial Instruments and Pricing\n2022-05-17\nhttps://github.com/enthought/pyql\nQuantLib’s Python port.\nTrue\nFalse\nenthought/pyql\n\n\npyfin\nPython > Financial Instruments and Pricing\n2014-12-03\nhttps://github.com/opendoor-labs/pyfin\nBasic options pricing in Python. [ARCHIVED]\nTrue\nFalse\nopendoor-labs/pyfin\n\n\nvollib\nPython > Financial Instruments and Pricing\n2016-05-17\nhttps://github.com/vollib/vollib\nvollib is a python library for calculating option prices, implied volatility and greeks.\nTrue\nFalse\nvollib/vollib\n\n\nQuantPy\nPython > Financial Instruments and Pricing\n2017-11-28\nhttps://github.com/jsmidt/QuantPy\nA framework for quantitative finance In python.\nTrue\nFalse\njsmidt/QuantPy\n\n\nFinance-Python\nPython > Financial Instruments and Pricing\n2021-12-26\nhttps://github.com/alpha-miner/Finance-Python\nPython tools for Finance.\nTrue\nFalse\nalpha-miner/Finance-Python\n\n\nffn\nPython > Financial Instruments and Pricing\n2022-06-01\nhttps://github.com/pmorissette/ffn\nA financial function library for Python.\nTrue\nFalse\npmorissette/ffn\n\n\npynance\nPython > Financial Instruments and Pricing\n2021-02-03\nhttps://github.com/GriffinAustin/pynance\nLightweight Python library for assembling and analysing financial data.\nTrue\nFalse\nGriffinAustin/pynance\n\n\ntia\nPython > Financial Instruments and Pricing\n2017-06-05\nhttps://github.com/bpsmith/tia\nToolkit for integration and analysis.\nTrue\nFalse\nbpsmith/tia\n\n\nhasura/base-python-dash\nPython > Financial Instruments and Pricing\n\nhttps://platform.hasura.io/hub/projects/hasura/base-python-dash\nHasura 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.\nFalse\nFalse\n\n\n\nhasura/base-python-bokeh\nPython > Financial Instruments and Pricing\n\nhttps://platform.hasura.io/hub/projects/hasura/base-python-bokeh\nHasura quickstart to visualize data with bokeh library.\nFalse\nFalse\n\n\n\npysabr\nPython > Financial Instruments and Pricing\n2022-04-21\nhttps://github.com/ynouri/pysabr\nSABR model Python implementation.\nTrue\nFalse\nynouri/pysabr\n\n\nFinancePy\nPython > Financial Instruments and Pricing\n2022-03-20\nhttps://github.com/domokane/FinancePy\nA Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.\nTrue\nFalse\ndomokane/FinancePy\n\n\ngs-quant\nPython > Financial Instruments and Pricing\n2022-05-31\nhttps://github.com/goldmansachs/gs-quant\nPython toolkit for quantitative finance\nTrue\nFalse\ngoldmansachs/gs-quant\n\n\nwillowtree\nPython > Financial Instruments and Pricing\n2018-07-14\nhttps://github.com/federicomariamassari/willowtree\nRobust and flexible Python implementation of the willow tree lattice for derivatives pricing.\nTrue\nFalse\nfedericomariamassari/willowtree\n\n\nfinancial-engineering\nPython > Financial Instruments and Pricing\n2017-11-20\nhttps://github.com/federicomariamassari/financial-engineering\nApplications of Monte Carlo methods to financial engineering projects, in Python.\nTrue\nFalse\nfedericomariamassari/financial-engineering\n\n\noptlib\nPython > Financial Instruments and Pricing\n2021-06-16\nhttps://github.com/dbrojas/optlib\nA library for financial options pricing written in Python.\nTrue\nFalse\ndbrojas/optlib\n\n\ntf-quant-finance\nPython > Financial Instruments and Pricing\n2022-05-31\nhttps://github.com/google/tf-quant-finance\nHigh-performance TensorFlow library for quantitative finance.\nTrue\nFalse\ngoogle/tf-quant-finance\n\n\nQ-Fin\nPython > Financial Instruments and Pricing\n2021-06-07\nhttps://github.com/RomanMichaelPaolucci/Q-Fin\nA Python library for mathematical finance.\nTrue\nFalse\nRomanMichaelPaolucci/Q-Fin\n\n\nQuantsbin\nPython > Financial Instruments and Pricing\n2021-05-23\nhttps://github.com/quantsbin/Quantsbin\nTools for pricing and plotting of vanilla option prices, greeks and various other analysis around them.\nTrue\nFalse\nquantsbin/Quantsbin\n\n\nfinoptions\nPython > Financial Instruments and Pricing\n2021-12-28\nhttps://github.com/bbcho/finoptions-dev\nComplete python implementation of R package fOptions with partial implementation of fExoticOptions for pricing various options.\nTrue\nFalse\nbbcho/finoptions-dev\n\n\npandas_talib\nPython > Indicators\n2018-05-30\nhttps://github.com/femtotrader/pandas_talib\nA Python Pandas implementation of technical analysis indicators.\nTrue\nFalse\nfemtotrader/pandas_talib\n\n\nfinta\nPython > Indicators\n2021-10-19\nhttps://github.com/peerchemist/finta\nCommon financial technical analysis indicators implemented in Pandas.\nTrue\nFalse\npeerchemist/finta\n\n\nTulipy\nPython > Indicators\n2019-04-11\nhttps://github.com/cirla/tulipy\nFinancial Technical Analysis Indicator Library (Python bindings for tulipindicators)\nTrue\nFalse\ncirla/tulipy\n\n\nlppls\nPython > Indicators\n2022-05-29\nhttps://github.com/Boulder-Investment-Technologies/lppls\nA Python module for fitting the Log-Periodic Power Law Singularity (LPPLS) model.\nTrue\nFalse\nBoulder-Investment-Technologies/lppls\n\n\nBlankly\nPython > Trading & Backtesting\n2022-05-03\nhttps://github.com/Blankly-Finance/Blankly\nFully integrated backtesting, paper trading, and live deployment.\nTrue\nFalse\nBlankly-Finance/Blankly\n\n\nTA-Lib\nPython > Trading & Backtesting\n2022-05-27\nhttps://github.com/mrjbq7/ta-lib\nPython wrapper for TA-Lib (http://ta-lib.org/).\nTrue\nFalse\nmrjbq7/ta-lib\n\n\nzipline\nPython > Trading & Backtesting\n2020-10-14\nhttps://github.com/quantopian/zipline\nPythonic algorithmic trading library.\nTrue\nFalse\nquantopian/zipline\n\n\nQuantSoftware Toolkit\nPython > Trading & Backtesting\n2016-10-07\nhttps://github.com/QuantSoftware/QuantSoftwareToolkit\nPython-based open source software framework designed to support portfolio construction and management.\nTrue\nFalse\nQuantSoftware/QuantSoftwareToolkit\n\n\nquantitative\nPython > Trading & Backtesting\n2019-03-03\nhttps://github.com/jeffrey-liang/quantitative\nQuantitative finance, and backtesting library.\nTrue\nFalse\njeffrey-liang/quantitative\n\n\nanalyzer\nPython > Trading & Backtesting\n2015-12-22\nhttps://github.com/llazzaro/analyzer\nPython framework for real-time financial and backtesting trading strategies.\nTrue\nFalse\nllazzaro/analyzer\n\n\nbt\nPython > Trading & Backtesting\n2022-05-26\nhttps://github.com/pmorissette/bt\nFlexible Backtesting for Python.\nTrue\nFalse\npmorissette/bt\n\n\nbacktrader\nPython > Trading & Backtesting\n2021-07-17\nhttps://github.com/backtrader/backtrader\nPython Backtesting library for trading strategies.\nTrue\nFalse\nbacktrader/backtrader\n\n\npythalesians\nPython > Trading & Backtesting\n2016-09-23\nhttps://github.com/thalesians/pythalesians\nPython library to backtest trading strategies, plot charts, seamlessly download market data, analyse market patterns etc.\nTrue\nFalse\nthalesians/pythalesians\n\n\npybacktest\nPython > Trading & Backtesting\n2019-09-09\nhttps://github.com/ematvey/pybacktest\nVectorized backtesting framework in Python / pandas, designed to make your backtesting easier.\nTrue\nFalse\nematvey/pybacktest\n\n\npyalgotrade\nPython > Trading & Backtesting\n2018-08-21\nhttps://github.com/gbeced/pyalgotrade\nPython Algorithmic Trading Library.\nTrue\nFalse\ngbeced/pyalgotrade\n\n\ntradingWithPython\nPython > Trading & Backtesting\n\nhttps://pypi.org/project/tradingWithPython/\nA collection of functions and classes for Quantitative trading.\nFalse\nFalse\n\n\n\nPandas TA\nPython > Trading & Backtesting\n2022-01-31\nhttps://github.com/twopirllc/pandas-ta\nPandas TA is an easy to use Python 3 Pandas Extension with 115+ Indicators. Easily build Custom Strategies.\nTrue\nFalse\ntwopirllc/pandas-ta\n\n\nta\nPython > Trading & Backtesting\n2022-04-24\nhttps://github.com/bukosabino/ta\nTechnical Analysis Library using Pandas (Python)\nTrue\nFalse\nbukosabino/ta\n\n\nalgobroker\nPython > Trading & Backtesting\n2016-03-31\nhttps://github.com/joequant/algobroker\nThis is an execution engine for algo trading.\nTrue\nFalse\njoequant/algobroker\n\n\npysentosa\nPython > Trading & Backtesting\n\nhttps://pypi.org/project/pysentosa/\nPython API for sentosa trading system.\nFalse\nFalse\n\n\n\nfinmarketpy\nPython > Trading & Backtesting\n2022-04-05\nhttps://github.com/cuemacro/finmarketpy\nPython library for backtesting trading strategies and analyzing financial markets.\nTrue\nFalse\ncuemacro/finmarketpy\n\n\nbinary-martingale\nPython > Trading & Backtesting\n2017-10-16\nhttps://github.com/metaperl/binary-martingale\nComputer program to automatically trade binary options martingale style.\nTrue\nFalse\nmetaperl/binary-martingale\n\n\nfooltrader\nPython > Trading & Backtesting\n2020-07-19\nhttps://github.com/foolcage/fooltrader\nthe project using big-data technology to provide an uniform way to analyze the whole market.\nTrue\nFalse\nfoolcage/fooltrader\n\n\nzvt\nPython > Trading & Backtesting\n2022-05-27\nhttps://github.com/zvtvz/zvt\nthe 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.\nTrue\nFalse\nzvtvz/zvt\n\n\npylivetrader\nPython > Trading & Backtesting\n2022-04-11\nhttps://github.com/alpacahq/pylivetrader\nzipline-compatible live trading library.\nTrue\nFalse\nalpacahq/pylivetrader\n\n\npipeline-live\nPython > Trading & Backtesting\n2022-04-11\nhttps://github.com/alpacahq/pipeline-live\nzipline’s pipeline capability with IEX for live trading.\nTrue\nFalse\nalpacahq/pipeline-live\n\n\nzipline-extensions\nPython > Trading & Backtesting\n2018-09-17\nhttps://github.com/quantrocket-llc/zipline-extensions\nZipline extensions and adapters for QuantRocket.\nTrue\nFalse\nquantrocket-llc/zipline-extensions\n\n\nmoonshot\nPython > Trading & Backtesting\n2022-05-25\nhttps://github.com/quantrocket-llc/moonshot\nVectorized backtester and trading engine for QuantRocket based on Pandas.\nTrue\nFalse\nquantrocket-llc/moonshot\n\n\nPyPortfolioOpt\nPython > Trading & Backtesting\n2022-05-22\nhttps://github.com/robertmartin8/PyPortfolioOpt\nFinancial portfolio optimisation in python, including classical efficient frontier and advanced methods.\nTrue\nFalse\nrobertmartin8/PyPortfolioOpt\n\n\nEiten\nPython > Trading & Backtesting\n2020-09-21\nhttps://github.com/tradytics/eiten\nEiten 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.\nTrue\nFalse\ntradytics/eiten\n\n\nriskparity.py\nPython > Trading & Backtesting\n2022-05-31\nhttps://github.com/dppalomar/riskparity.py\nfast and scalable design of risk parity portfolios with TensorFlow 2.0\nTrue\nFalse\ndppalomar/riskparity.py\n\n\nmlfinlab\nPython > Trading & Backtesting\n2021-12-01\nhttps://github.com/hudson-and-thames/mlfinlab\nImplementations regarding “Advances in Financial Machine Learning” by Marcos Lopez de Prado. (Feature Engineering, Financial Data Structures, Meta-Labeling)\nTrue\nFalse\nhudson-and-thames/mlfinlab\n\n\npyqstrat\nPython > Trading & Backtesting\n2022-01-08\nhttps://github.com/abbass2/pyqstrat\nA fast, extensible, transparent python library for backtesting quantitative strategies.\nTrue\nFalse\nabbass2/pyqstrat\n\n\nNowTrade\nPython > Trading & Backtesting\n2017-02-07\nhttps://github.com/edouardpoitras/NowTrade\nPython library for backtesting technical/mechanical strategies in the stock and currency markets.\nTrue\nFalse\nedouardpoitras/NowTrade\n\n\npinkfish\nPython > Trading & Backtesting\n2022-05-28\nhttps://github.com/fja05680/pinkfish\nA backtester and spreadsheet library for security analysis.\nTrue\nFalse\nfja05680/pinkfish\n\n\naat\nPython > Trading & Backtesting\n2022-03-27\nhttps://github.com/timkpaine/aat\nAsync Algorithmic Trading Engine\nTrue\nFalse\ntimkpaine/aat\n\n\nBacktesting.py\nPython > Trading & Backtesting\n\nhttps://kernc.github.io/backtesting.py/\nBacktest trading strategies in Python\nFalse\nFalse\n\n\n\ncatalyst\nPython > Trading & Backtesting\n2021-09-22\nhttps://github.com/enigmampc/catalyst\nAn Algorithmic Trading Library for Crypto-Assets in Python\nTrue\nFalse\nenigmampc/catalyst\n\n\nquantstats\nPython > Trading & Backtesting\n2022-05-02\nhttps://github.com/ranaroussi/quantstats\nPortfolio analytics for quants, written in Python\nTrue\nFalse\nranaroussi/quantstats\n\n\nqtpylib\nPython > Trading & Backtesting\n2021-03-24\nhttps://github.com/ranaroussi/qtpylib\nQTPyLib, Pythonic Algorithmic Trading http://qtpylib.io\nTrue\nFalse\nranaroussi/qtpylib\n\n\nQuantdom\nPython > Trading & Backtesting\n2019-03-12\nhttps://github.com/constverum/Quantdom\nPython-based framework for backtesting trading strategies & analyzing financial markets [GUI :neckbeard:]\nTrue\nFalse\nconstverum/Quantdom\n\n\nfreqtrade\nPython > Trading & Backtesting\n2022-05-31\nhttps://github.com/freqtrade/freqtrade\nFree, open source crypto trading bot\nTrue\nFalse\nfreqtrade/freqtrade\n\n\nalgorithmic-trading-with-python\nPython > Trading & Backtesting\n2021-06-01\nhttps://github.com/chrisconlan/algorithmic-trading-with-python\nFree pandas and scikit-learn resources for trading simulation, backtesting, and machine learning on financial data.\nTrue\nFalse\nchrisconlan/algorithmic-trading-with-python\n\n\nDeepDow\nPython > Trading & Backtesting\n2022-04-21\nhttps://github.com/jankrepl/deepdow\nPortfolio optimization with deep learning\nTrue\nFalse\njankrepl/deepdow\n\n\nQlib\nPython > Trading & Backtesting\n2022-05-31\nhttps://github.com/microsoft/qlib\nAn 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.\nTrue\nFalse\nmicrosoft/qlib\n\n\nmachine-learning-for-trading\nPython > Trading & Backtesting\n2022-04-29\nhttps://github.com/stefan-jansen/machine-learning-for-trading\nCode and resources for Machine Learning for Algorithmic Trading\nTrue\nFalse\nstefan-jansen/machine-learning-for-trading\n\n\nAlphaPy\nPython > Trading & Backtesting\n2022-04-23\nhttps://github.com/ScottfreeLLC/AlphaPy\nAutomated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost\nTrue\nFalse\nScottfreeLLC/AlphaPy\n\n\njesse\nPython > Trading & Backtesting\n2022-05-23\nhttps://github.com/jesse-ai/jesse\nAn advanced crypto trading bot written in Python\nTrue\nFalse\njesse-ai/jesse\n\n\nrqalpha\nPython > Trading & Backtesting\n2022-05-16\nhttps://github.com/ricequant/rqalpha\nA extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities.\nTrue\nFalse\nricequant/rqalpha\n\n\nFinRL-Library\nPython > Trading & Backtesting\n2022-06-04\nhttps://github.com/AI4Finance-LLC/FinRL-Library\nA Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020.\nTrue\nFalse\nAI4Finance-LLC/FinRL-Library\n\n\nbulbea\nPython > Trading & Backtesting\n2017-03-19\nhttps://github.com/achillesrasquinha/bulbea\nDeep Learning based Python Library for Stock Market Prediction and Modelling.\nTrue\nFalse\nachillesrasquinha/bulbea\n\n\nib_nope\nPython > Trading & Backtesting\n2021-04-22\nhttps://github.com/ajhpark/ib_nope\nAutomated trading system for NOPE strategy over IBKR TWS.\nTrue\nFalse\najhpark/ib_nope\n\n\nOctoBot\nPython > Trading & Backtesting\n2022-06-01\nhttps://github.com/Drakkar-Software/OctoBot\nOpen source cryptocurrency trading bot for high frequency, arbitrage, TA and social trading with an advanced web interface.\nTrue\nFalse\nDrakkar-Software/OctoBot\n\n\nbta-lib\nPython > Trading & Backtesting\n2020-03-11\nhttps://github.com/mementum/bta-lib\nTechnical Analysis library in pandas for backtesting algotrading and quantitative analysis.\nTrue\nFalse\nmementum/bta-lib\n\n\nStock-Prediction-Models\nPython > Trading & Backtesting\n2021-01-05\nhttps://github.com/huseinzol05/Stock-Prediction-Models\nGathers machine learning and deep learning models for Stock forecasting including trading bots and simulations.\nTrue\nFalse\nhuseinzol05/Stock-Prediction-Models\n\n\nTuneTA\nPython > Trading & Backtesting\n2022-05-23\nhttps://github.com/jmrichardson/tuneta\nTuneTA optimizes technical indicators using a distance correlation measure to a user defined target feature such as next day return.\nTrue\nFalse\njmrichardson/tuneta\n\n\nAutoTrader\nPython > Trading & Backtesting\n2022-06-02\nhttps://github.com/kieran-mackle/AutoTrader\nA Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.\nTrue\nFalse\nkieran-mackle/AutoTrader\n\n\nfast-trade\nPython > Trading & Backtesting\n2022-05-01\nhttps://github.com/jrmeier/fast-trade\nA library built with backtest portability and performance in mind for backtest trading strategies.\nTrue\nFalse\njrmeier/fast-trade\n\n\nqf-lib\nPython > Trading & Backtesting\n2022-04-11\nhttps://github.com/quarkfin/qf-lib\nQF-Lib is a Python library that provides high quality tools for quantitative finance.\nTrue\nFalse\nquarkfin/qf-lib\n\n\ntda-api\nPython > Trading & Backtesting\n2022-06-03\nhttps://github.com/alexgolec/tda-api\nGather data and trade equities, options, and ETFs via TDAmeritrade.\nTrue\nFalse\nalexgolec/tda-api\n\n\nvectorbt\nPython > Trading & Backtesting\n2022-05-21\nhttps://github.com/polakowo/vectorbt\nFind your trading edge, using a powerful toolkit for backtesting, algorithmic trading, and research.\nTrue\nFalse\npolakowo/vectorbt\n\n\nLean\nPython > Trading & Backtesting\n2022-06-03\nhttps://github.com/QuantConnect/Lean\nLean Algorithmic Trading Engine by QuantConnect (Python, C#).\nTrue\nFalse\nQuantConnect/Lean\n\n\nfast-trade\nPython > Trading & Backtesting\n2022-05-01\nhttps://github.com/jrmeier/fast-trade\nLow code backtesting library utilizing pandas and technical analysis indicators.\nTrue\nFalse\njrmeier/fast-trade\n\n\npyfolio\nPython > Risk Analysis\n2020-02-28\nhttps://github.com/quantopian/pyfolio\nPortfolio and risk analytics in Python.\nTrue\nFalse\nquantopian/pyfolio\n\n\nempyrical\nPython > Risk Analysis\n2020-10-14\nhttps://github.com/quantopian/empyrical\nCommon financial risk and performance metrics.\nTrue\nFalse\nquantopian/empyrical\n\n\nfecon235\nPython > Risk Analysis\n2018-12-03\nhttps://github.com/rsvp/fecon235\nComputational tools for financial economics include: Gaussian Mixture model of leptokurtotic risk, adaptive Boltzmann portfolios.\nTrue\nFalse\nrsvp/fecon235\n\n\nfinance\nPython > Risk Analysis\n\nhttps://pypi.org/project/finance/\nFinancial Risk Calculations. Optimized for ease of use through class construction and operator overload.\nFalse\nFalse\n\n\n\nqfrm\nPython > Risk Analysis\n\nhttps://pypi.org/project/qfrm/\nQuantitative Financial Risk Management: awesome OOP tools for measuring, managing and visualizing risk of financial instruments and portfolios.\nFalse\nFalse\n\n\n\nvisualize-wealth\nPython > Risk Analysis\n2015-06-10\nhttps://github.com/benjaminmgross/visualize-wealth\nPortfolio construction and quantitative analysis.\nTrue\nFalse\nbenjaminmgross/visualize-wealth\n\n\nVisualPortfolio\nPython > Risk Analysis\n2017-02-28\nhttps://github.com/wegamekinglc/VisualPortfolio\nThis tool is used to visualize the perfomance of a portfolio.\nTrue\nFalse\nwegamekinglc/VisualPortfolio\n\n\nuniversal-portfolios\nPython > Risk Analysis\n2021-12-22\nhttps://github.com/Marigold/universal-portfolios\nCollection of algorithms for online portfolio selection.\nTrue\nFalse\nMarigold/universal-portfolios\n\n\nFinQuant\nPython > Risk Analysis\n2020-05-03\nhttps://github.com/fmilthaler/FinQuant\nA program for financial portfolio management, analysis and optimisation.\nTrue\nFalse\nfmilthaler/FinQuant\n\n\nEmpyrial\nPython > Risk Analysis\n2022-05-22\nhttps://github.com/ssantoshp/Empyrial\nPortfolio’s risk and performance analytics and returns predictions.\nTrue\nFalse\nssantoshp/Empyrial\n\n\nrisktools\nPython > Risk Analysis\n2022-01-16\nhttps://github.com/bbcho/risktools-dev\nRisk tools for use within the crude and crude products trading space with partial implementation of R’s PerformanceAnalytics.\nTrue\nFalse\nbbcho/risktools-dev\n\n\nRiskfolio-Lib\nPython > Risk Analysis\n2022-05-22\nhttps://github.com/dcajasn/Riskfolio-Lib\nPortfolio Optimization and Quantitative Strategic Asset Allocation in Python.\nTrue\nFalse\ndcajasn/Riskfolio-Lib\n\n\nalphalens\nPython > Factor Analysis\n2020-04-27\nhttps://github.com/quantopian/alphalens\nPerformance analysis of predictive alpha factors.\nTrue\nFalse\nquantopian/alphalens\n\n\nSpectre\nPython > Factor Analysis\n2021-01-02\nhttps://github.com/Heerozh/spectre\nGPU-accelerated Factors analysis library and Backtester\nTrue\nFalse\nHeerozh/spectre\n\n\nARCH\nPython > Time Series\n2022-04-28\nhttps://github.com/bashtage/arch\nARCH models in Python.\nTrue\nFalse\nbashtage/arch\n\n\nstatsmodels\nPython > Time Series\n\nhttp://statsmodels.sourceforge.net\nPython module that allows users to explore data, estimate statistical models, and perform statistical tests.\nFalse\nFalse\n\n\n\ndynts\nPython > Time Series\n2016-11-02\nhttps://github.com/quantmind/dynts\nPython package for timeseries analysis and manipulation.\nTrue\nFalse\nquantmind/dynts\n\n\nPyFlux\nPython > Time Series\n2018-12-16\nhttps://github.com/RJT1990/pyflux\nPython library for timeseries modelling and inference (frequentist and Bayesian) on models.\nTrue\nFalse\nRJT1990/pyflux\n\n\ntsfresh\nPython > Time Series\n2021-12-21\nhttps://github.com/blue-yonder/tsfresh\nAutomatic extraction of relevant features from time series.\nTrue\nFalse\nblue-yonder/tsfresh\n\n\nhasura/quandl-metabase\nPython > Time Series\n\nhttps://platform.hasura.io/hub/projects/anirudhm/quandl-metabase-time-series\nHasura quickstart to visualize Quandl’s timeseries datasets with Metabase.\nFalse\nFalse\n\n\n\nFacebook Prophet\nPython > Time Series\n2022-05-25\nhttps://github.com/facebook/prophet\nTool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.\nTrue\nFalse\nfacebook/prophet\n\n\ntsmoothie\nPython > Time Series\n2021-08-25\nhttps://github.com/cerlymarco/tsmoothie\nA python library for time-series smoothing and outlier detection in a vectorized way.\nTrue\nFalse\ncerlymarco/tsmoothie\n\n\npmdarima\nPython > Time Series\n2022-06-01\nhttps://github.com/alkaline-ml/pmdarima\nA statistical library designed to fill the void in Python’s time series analysis capabilities, including the equivalent of R’s auto.arima function.\nTrue\nFalse\nalkaline-ml/pmdarima\n\n\ngluon-ts\nPython > Time Series\n2022-06-03\nhttps://github.com/awslabs/gluon-ts\nvProbabilistic time series modeling in Python.\nTrue\nFalse\nawslabs/gluon-ts\n\n\nexchange_calendars\nPython > Calendars\n2022-06-01\nhttps://github.com/gerrymanoim/exchange_calendars\nStock Exchange Trading Calendars.\nTrue\nFalse\ngerrymanoim/exchange_calendars\n\n\nbizdays\nPython > Calendars\n2022-01-20\nhttps://github.com/wilsonfreitas/python-bizdays\nBusiness days calculations and utilities.\nTrue\nFalse\nwilsonfreitas/python-bizdays\n\n\npandas_market_calendars\nPython > Calendars\n2022-05-28\nhttps://github.com/rsheftel/pandas_market_calendars\nExchange calendars to use with pandas for trading applications.\nTrue\nFalse\nrsheftel/pandas_market_calendars\n\n\nyfinance\nPython > Data Sources\n2022-01-30\nhttps://github.com/ranaroussi/yfinance\nYahoo! Finance market data downloader (+faster Pandas Datareader)\nTrue\nFalse\nranaroussi/yfinance\n\n\nfindatapy\nPython > Data Sources\n2022-05-20\nhttps://github.com/cuemacro/findatapy\nPython library to download market data via Bloomberg, Quandl, Yahoo etc.\nTrue\nFalse\ncuemacro/findatapy\n\n\ngooglefinance\nPython > Data Sources\n2018-09-23\nhttps://github.com/hongtaocai/googlefinance\nPython module to get real-time stock data from Google Finance API.\nTrue\nFalse\nhongtaocai/googlefinance\n\n\nyahoo-finance\nPython > Data Sources\n2021-12-15\nhttps://github.com/lukaszbanasiak/yahoo-finance\nPython module to get stock data from Yahoo! Finance.\nTrue\nFalse\nlukaszbanasiak/yahoo-finance\n\n\npandas-datareader\nPython > Data Sources\n2022-03-16\nhttps://github.com/pydata/pandas-datareader\nPython 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.\nTrue\nFalse\npydata/pandas-datareader\n\n\npandas-finance\nPython > Data Sources\n2021-08-08\nhttps://github.com/davidastephens/pandas-finance\nHigh level API for access to and analysis of financial data.\nTrue\nFalse\ndavidastephens/pandas-finance\n\n\npyhoofinance\nPython > Data Sources\n2016-10-07\nhttps://github.com/innes213/pyhoofinance\nRapidly queries Yahoo Finance for multiple tickers and returns typed data for analysis.\nTrue\nFalse\ninnes213/pyhoofinance\n\n\nyfinanceapi\nPython > Data Sources\n2020-05-26\nhttps://github.com/Karthik005/yfinanceapi\nFinance API for Python.\nTrue\nFalse\nKarthik005/yfinanceapi\n\n\nyql-finance\nPython > Data Sources\n2015-08-29\nhttps://github.com/slawek87/yql-finance\nyql-finance is simple and fast. API returns stock closing prices for current period of time and current stock ticker (i.e. APPL, GOOGL).\nTrue\nFalse\nslawek87/yql-finance\n\n\nystockquote\nPython > Data Sources\n2017-03-10\nhttps://github.com/cgoldberg/ystockquote\nRetrieve stock quote data from Yahoo Finance.\nTrue\nFalse\ncgoldberg/ystockquote\n\n\nwallstreet\nPython > Data Sources\n2022-02-12\nhttps://github.com/mcdallas/wallstreet\nReal time stock and option data.\nTrue\nFalse\nmcdallas/wallstreet\n\n\nstock_extractor\nPython > Data Sources\n2016-09-10\nhttps://github.com/ZachLiuGIS/stock_extractor\nGeneral Purpose Stock Extractors from Online Resources.\nTrue\nFalse\nZachLiuGIS/stock_extractor\n\n\nStockex\nPython > Data Sources\n2021-09-15\nhttps://github.com/cttn/Stockex\nPython wrapper for Yahoo! Finance API.\nTrue\nFalse\ncttn/Stockex\n\n\nfinsymbols\nPython > Data Sources\n2017-07-23\nhttps://github.com/skillachie/finsymbols\nObtains stock symbols and relating information for SP500, AMEX, NYSE, and NASDAQ.\nTrue\nFalse\nskillachie/finsymbols\n\n\nFRB\nPython > Data Sources\n2018-12-22\nhttps://github.com/avelkoski/FRB\nPython Client for FRED® API.\nTrue\nFalse\navelkoski/FRB\n\n\ninquisitor\nPython > Data Sources\n2019-10-10\nhttps://github.com/econdb/inquisitor\nPython Interface to Econdb.com API.\nTrue\nFalse\necondb/inquisitor\n\n\nyfi\nPython > Data Sources\n2016-02-12\nhttps://github.com/nickelkr/yfi\nYahoo! YQL library.\nTrue\nFalse\nnickelkr/yfi\n\n\nchinesestockapi\nPython > Data Sources\n\nhttps://pypi.org/project/chinesestockapi/\nPython API to get Chinese stock price.\nFalse\nFalse\n\n\n\nexchange\nPython > Data Sources\n2015-07-07\nhttps://github.com/akarat/exchange\nGet current exchange rate.\nTrue\nFalse\nakarat/exchange\n\n\nticks\nPython > Data Sources\n2016-01-08\nhttps://github.com/jamescnowell/ticks\nSimple command line tool to get stock ticker data.\nTrue\nFalse\njamescnowell/ticks\n\n\npybbg\nPython > Data Sources\n2015-01-20\nhttps://github.com/bpsmith/pybbg\nPython interface to Bloomberg COM APIs.\nTrue\nFalse\nbpsmith/pybbg\n\n\nccy\nPython > Data Sources\n2021-01-09\nhttps://github.com/lsbardel/ccy\nPython module for currencies.\nTrue\nFalse\nlsbardel/ccy\n\n\ntushare\nPython > Data Sources\n\nhttps://pypi.org/project/tushare/\nA utility for crawling historical and Real-time Quotes data of China stocks.\nFalse\nFalse\n\n\n\njsm\nPython > Data Sources\n\nhttps://pypi.org/project/jsm/\nGet the japanese stock market data.\nFalse\nFalse\n\n\n\ncn_stock_src\nPython > Data Sources\n2016-02-29\nhttps://github.com/jealous/cn_stock_src\nUtility for retrieving basic China stock data from different sources.\nTrue\nFalse\njealous/cn_stock_src\n\n\ncoinmarketcap\nPython > Data Sources\n2021-02-12\nhttps://github.com/barnumbirr/coinmarketcap\nPython API for coinmarketcap.\nTrue\nFalse\nbarnumbirr/coinmarketcap\n\n\nafter-hours\nPython > Data Sources\n2020-06-22\nhttps://github.com/datawrestler/after-hours\nObtain pre market and after hours stock prices for a given symbol.\nTrue\nFalse\ndatawrestler/after-hours\n\n\nbronto-python\nPython > Data Sources\n\nhttps://pypi.org/project/bronto-python/\nBronto API Integration for Python.\nFalse\nFalse\n\n\n\npytdx\nPython > Data Sources\n2020-04-15\nhttps://github.com/rainx/pytdx\nPython Interface for retrieving chinese stock realtime quote data from TongDaXin Nodes.\nTrue\nFalse\nrainx/pytdx\n\n\npdblp\nPython > Data Sources\n2022-05-28\nhttps://github.com/matthewgilbert/pdblp\nA simple interface to integrate pandas and the Bloomberg Open API.\nTrue\nFalse\nmatthewgilbert/pdblp\n\n\ntiingo\nPython > Data Sources\n2022-05-21\nhttps://github.com/hydrosquall/tiingo-python\nPython interface for daily composite prices/OHLC/Volume + Real-time News Feeds, powered by the Tiingo Data Platform.\nTrue\nFalse\nhydrosquall/tiingo-python\n\n\niexfinance\nPython > Data Sources\n2021-01-02\nhttps://github.com/addisonlynch/iexfinance\nPython Interface for retrieving real-time and historical prices and equities data from The Investor’s Exchange.\nTrue\nFalse\naddisonlynch/iexfinance\n\n\npyEX\nPython > Data Sources\n2022-06-03\nhttps://github.com/timkpaine/pyEX\nPython interface to IEX with emphasis on pandas, support for streaming data, premium data, points data (economic, rates, commodities), and technical indicators.\nTrue\nFalse\ntimkpaine/pyEX\n\n\nalpaca-trade-api\nPython > Data Sources\n2022-06-02\nhttps://github.com/alpacahq/alpaca-trade-api-python\nPython interface for retrieving real-time and historical prices from Alpaca API as well as trade execution.\nTrue\nFalse\nalpacahq/alpaca-trade-api-python\n\n\nmetatrader5\nPython > Data Sources\n\nhttps://pypi.org/project/MetaTrader5/\nAPI Connector to MetaTrader 5 Terminal\nFalse\nFalse\n\n\n\nakshare\nPython > Data Sources\n2022-06-04\nhttps://github.com/jindaxiang/akshare\nAkShare is an elegant and simple financial data interface library for Python, built for human beings! https://akshare.readthedocs.io\nTrue\nFalse\njindaxiang/akshare\n\n\nyahooquery\nPython > Data Sources\n2021-02-26\nhttps://github.com/dpguthrie/yahooquery\nPython interface for retrieving data through unofficial Yahoo Finance API.\nTrue\nFalse\ndpguthrie/yahooquery\n\n\ninvestpy\nPython > Data Sources\n2022-03-28\nhttps://github.com/alvarobartt/investpy\nFinancial Data Extraction from Investing.com with Python! https://investpy.readthedocs.io/\nTrue\nFalse\nalvarobartt/investpy\n\n\nyliveticker\nPython > Data Sources\n2021-04-29\nhttps://github.com/yahoofinancelive/yliveticker\nLive stream of market data from Yahoo Finance websocket.\nTrue\nFalse\nyahoofinancelive/yliveticker\n\n\nbbgbridge\nPython > Data Sources\n2020-01-07\nhttps://github.com/ran404/bbgbridge\nEasy to use Bloomberg Desktop API wrapper for Python.\nTrue\nFalse\nran404/bbgbridge\n\n\nalpha_vantage\nPython > Data Sources\n2021-06-14\nhttps://github.com/RomelTorres/alpha_vantage\nA python wrapper for Alpha Vantage API for financial data.\nTrue\nFalse\nRomelTorres/alpha_vantage\n\n\nFinanceDataReader\nPython > Data Sources\n2022-03-28\nhttps://github.com/FinanceData/FinanceDataReader\nOpen Source Financial data reader for U.S, Korean, Japanese, Chinese, Vietnamese Stocks\nTrue\nFalse\nFinanceData/FinanceDataReader\n\n\npystlouisfed\nPython > Data Sources\n2022-02-23\nhttps://github.com/TomasKoutek/pystlouisfed\nPython client for Federal Reserve Bank of St. Louis API - FRED, ALFRED, GeoFRED and FRASER.\nTrue\nFalse\nTomasKoutek/pystlouisfed\n\n\npython-bcb\nPython > Data Sources\n2022-04-01\nhttps://github.com/wilsonfreitas/python-bcb\nPython interface to Brazilian Central Bank web services.\nTrue\nFalse\nwilsonfreitas/python-bcb\n\n\nxlwings\nPython > Excel Integration\n\nhttps://www.xlwings.org/\nMake Excel fly with Python.\nFalse\nFalse\n\n\n\nopenpyxl\nPython > Excel Integration\n\nhttps://openpyxl.readthedocs.io/en/latest/\nRead/Write Excel 2007 xlsx/xlsm files.\nFalse\nFalse\n\n\n\nxlrd\nPython > Excel Integration\n2021-08-19\nhttps://github.com/python-excel/xlrd\nLibrary for developers to extract data from Microsoft Excel spreadsheet files.\nTrue\nFalse\npython-excel/xlrd\n\n\nxlsxwriter\nPython > Excel Integration\n\nhttps://xlsxwriter.readthedocs.io/\nWrite files in the Excel 2007+ XLSX file format.\nFalse\nFalse\n\n\n\nxlwt\nPython > Excel Integration\n2018-09-16\nhttps://github.com/python-excel/xlwt\nLibrary to create spreadsheet files compatible with MS Excel 97/2000/XP/2003 XLS files, on any platform.\nTrue\nFalse\npython-excel/xlwt\n\n\nDataNitro\nPython > Excel Integration\n\nhttps://datanitro.com/\nDataNitro also offers full-featured Python-Excel integration, including UDFs. Trial downloads are available, but users must purchase a license.\nFalse\nFalse\n\n\n\nxlloop\nPython > Excel Integration\n\nhttp://xlloop.sourceforge.net\nXLLoop is an open source framework for implementing Excel user-defined functions (UDFs) on a centralised server (a function server).\nFalse\nFalse\n\n\n\nexpy\nPython > Excel Integration\n\nhttp://www.bnikolic.co.uk/expy/expy.html\nThe 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.\nFalse\nFalse\n\n\n\npyxll\nPython > Excel Integration\n\nhttps://www.pyxll.com\nPyXLL is an Excel add-in that enables you to extend Excel using nothing but Python code.\nFalse\nFalse\n\n\n\nD-Tale\nPython > Visualization\n2022-05-29\nhttps://github.com/man-group/dtale\nVisualizer for pandas dataframes and xarray datasets.\nTrue\nFalse\nman-group/dtale\n\n\nmplfinance\nPython > Visualization\n2022-05-25\nhttps://github.com/matplotlib/mplfinance\nmatplotlib utilities for the visualization, and visual analysis, of financial data.\nTrue\nFalse\nmatplotlib/mplfinance\n\n\nfinplot\nPython > Visualization\n2022-05-23\nhttps://github.com/highfestiva/finplot\nPerformant and effortless finance plotting for Python.\nTrue\nFalse\nhighfestiva/finplot\n\n\nfinvizfinance\nPython > Visualization\n2022-05-07\nhttps://github.com/lit26/finvizfinance\nFinviz analysis python library.\nTrue\nFalse\nlit26/finvizfinance\n\n\nxts\nR > Numerical Libraries & Data Structures\n2022-05-23\nhttps://github.com/joshuaulrich/xts\neXtensible 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.\nTrue\nFalse\njoshuaulrich/xts\n\n\ndata.table\nR > Numerical Libraries & Data Structures\n2022-03-16\nhttps://github.com/Rdatatable/data.table\nExtension 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.\nTrue\nFalse\nRdatatable/data.table\n\n\nsparseEigen\nR > Numerical Libraries & Data Structures\n2018-12-22\nhttps://github.com/dppalomar/sparseEigen\nSparse pricipal component analysis.\nTrue\nFalse\ndppalomar/sparseEigen\n\n\nTSdbi\nR > Numerical Libraries & Data Structures\n\nhttp://tsdbi.r-forge.r-project.org/\nProvides a common interface to time series databases.\nFalse\nFalse\n\n\n\ntseries\nR > Numerical Libraries & Data Structures\n\nhttps://cran.r-project.org/web/packages/tseries/index.html\nTime Series Analysis and Computational Finance.\nFalse\nTrue\n\n\n\nzoo\nR > Numerical Libraries & Data Structures\n\nhttps://cran.r-project.org/web/packages/zoo/index.html\nS3 Infrastructure for Regular and Irregular Time Series (Z’s Ordered Observations).\nFalse\nTrue\n\n\n\ntis\nR > Numerical Libraries & Data Structures\n\nhttps://cran.r-project.org/web/packages/tis/index.html\nFunctions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.\nFalse\nTrue\n\n\n\ntfplot\nR > Numerical Libraries & Data Structures\n\nhttps://cran.r-project.org/web/packages/tfplot/index.html\nUtilities for simple manipulation and quick plotting of time series data.\nFalse\nTrue\n\n\n\ntframe\nR > Numerical Libraries & Data Structures\n\nhttps://cran.r-project.org/web/packages/tframe/index.html\nA kernel of functions for programming time series methods in a way that is relatively independently of the representation of time.\nFalse\nTrue\n\n\n\nIBrokers\nR > Data Sources\n\nhttps://cran.r-project.org/web/packages/IBrokers/index.html\nProvides native R access to Interactive Brokers Trader Workstation API.\nFalse\nTrue\n\n\n\nRblpapi\nR > Data Sources\n2022-02-23\nhttps://github.com/Rblp/Rblpapi\nAn R Interface to ‘Bloomberg’ is provided via the ‘Blp API’.\nTrue\nFalse\nRblp/Rblpapi\n\n\nQuandl\nR > Data Sources\n\nhttps://www.quandl.com/tools/r\nGet Financial Data Directly Into R.\nFalse\nFalse\n\n\n\nRbitcoin\nR > Data Sources\n2016-10-25\nhttps://github.com/jangorecki/Rbitcoin\nUnified markets API interface (bitstamp, kraken, btce, bitmarket).\nTrue\nFalse\njangorecki/Rbitcoin\n\n\nGetTDData\nR > Data Sources\n2022-05-11\nhttps://github.com/msperlin/GetTDData\nDownloads and aggregates data for Brazilian government issued bonds directly from the website of Tesouro Direto.\nTrue\nFalse\nmsperlin/GetTDData\n\n\nGetHFData\nR > Data Sources\n2020-06-30\nhttps://github.com/msperlin/GetHFData\nDownloads and aggregates high frequency trading data for Brazilian instruments directly from Bovespa ftp site.\nTrue\nFalse\nmsperlin/GetHFData\n\n\nReddit WallstreetBets API\nR > Data Sources\n\nhttps://dashboard.nbshare.io/apps/reddit/api/\nProvides daily top 50 stocks from reddit (subreddit) Wallstreetbets and their sentiments via the API.\nFalse\nFalse\n\n\n\ntd\nR > Data Sources\n2022-02-03\nhttps://github.com/eddelbuettel/td\nInterfaces the ‘twelvedata’ API for stocks and (digital and standard) currencies.\nTrue\nFalse\neddelbuettel/td\n\n\nrbcb\nR > Data Sources\n2022-05-17\nhttps://github.com/wilsonfreitas/rbcb\nR interface to Brazilian Central Bank web services.\nTrue\nFalse\nwilsonfreitas/rbcb\n\n\nRQuantLib\nR > Financial Instruments and Pricing\n\nhttp://dirk.eddelbuettel.com/code/rquantlib.html\nRQuantLib connects GNU R with QuantLib.\nFalse\nFalse\n\n\n\nquantmod\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/quantmod/index.html\nQuantitative Financial Modelling Framework.\nFalse\nTrue\n\n\n\nRmetrics\nR > Financial Instruments and Pricing\n\nhttps://www.rmetrics.org\nThe premier open source software solution for teaching and training quantitative finance.\nFalse\nFalse\n\n\n\nfAsianOptions\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/fAsianOptions/index.html\nEBM and Asian Option Valuation.\nFalse\nTrue\n\n\n\nfAssets\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/fAssets/index.html\nAnalysing and Modelling Financial Assets.\nFalse\nTrue\n\n\n\nfBasics\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/fBasics/index.html\nMarkets and Basic Statistics.\nFalse\nTrue\n\n\n\nfBonds\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/fBonds/index.html\nBonds and Interest Rate Models.\nFalse\nTrue\n\n\n\nfExoticOptions\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/fExoticOptions/index.html\nExotic Option Valuation.\nFalse\nTrue\n\n\n\nfOptions\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/fOptions/index.html\nPricing and Evaluating Basic Options.\nFalse\nTrue\n\n\n\nfPortfolio\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/fPortfolio/index.html\nPortfolio Selection and Optimization.\nFalse\nTrue\n\n\n\nportfolio\nR > Financial Instruments and Pricing\n2021-07-09\nhttps://github.com/dgerlanc/portfolio\nAnalysing equity portfolios.\nTrue\nFalse\ndgerlanc/portfolio\n\n\nsparseIndexTracking\nR > Financial Instruments and Pricing\n2019-06-13\nhttps://github.com/dppalomar/sparseIndexTracking\nPortfolio design to track an index.\nTrue\nFalse\ndppalomar/sparseIndexTracking\n\n\ncovFactorModel\nR > Financial Instruments and Pricing\n2019-03-25\nhttps://github.com/dppalomar/covFactorModel\nCovariance matrix estimation via factor models.\nTrue\nFalse\ndppalomar/covFactorModel\n\n\nriskParityPortfolio\nR > Financial Instruments and Pricing\n2022-02-10\nhttps://github.com/dppalomar/riskParityPortfolio\nBlazingly fast design of risk parity portfolios.\nTrue\nFalse\ndppalomar/riskParityPortfolio\n\n\nsde\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/sde/index.html\nSimulation and Inference for Stochastic Differential Equations.\nFalse\nTrue\n\n\n\nYieldCurve\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/YieldCurve/index.html\nModelling and estimation of the yield curve.\nFalse\nTrue\n\n\n\nSmithWilsonYieldCurve\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/SmithWilsonYieldCurve/index.html\nConstructs a yield curve by the Smith-Wilson method from a table of LIBOR and SWAP rates.\nFalse\nTrue\n\n\n\nycinterextra\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/ycinterextra/index.html\nYield curve or zero-coupon prices interpolation and extrapolation.\nFalse\nTrue\n\n\n\nAmericanCallOpt\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/AmericanCallOpt/index.html\nThis package includes pricing function for selected American call options with underlying assets that generate payouts.\nFalse\nTrue\n\n\n\nVarSwapPrice\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/VarSwapPrice/index.html\nPricing a variance swap on an equity index.\nFalse\nTrue\n\n\n\nRND\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/RND/index.html\nRisk Neutral Density Extraction Package.\nFalse\nTrue\n\n\n\nLSMonteCarlo\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/LSMonteCarlo/index.html\nAmerican options pricing with Least Squares Monte Carlo method.\nFalse\nTrue\n\n\n\nOptHedging\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/OptHedging/index.html\nEstimation of value and hedging strategy of call and put options.\nFalse\nTrue\n\n\n\ntvm\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/tvm/index.html\nTime Value of Money Functions.\nFalse\nTrue\n\n\n\nOptionPricing\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/OptionPricing/index.html\nOption Pricing with Efficient Simulation Algorithms.\nFalse\nTrue\n\n\n\ncredule\nR > Financial Instruments and Pricing\n2015-08-05\nhttps://github.com/blenezet/credule\nCredit Default Swap Functions.\nTrue\nFalse\nblenezet/credule\n\n\nderivmkts\nR > Financial Instruments and Pricing\n\nhttps://cran.r-project.org/web/packages/derivmkts/index.html\nFunctions and R Code to Accompany Derivatives Markets.\nFalse\nTrue\n\n\n\nFinCal\nR > Financial Instruments and Pricing\n2017-04-12\nhttps://github.com/felixfan/FinCal\nPackage for time value of money calculation, time series analysis and computational finance.\nTrue\nFalse\nfelixfan/FinCal\n\n\nr-quant\nR > Financial Instruments and Pricing\n2014-02-19\nhttps://github.com/artyyouth/r-quant\nR code for quantitative analysis in finance.\nTrue\nFalse\nartyyouth/r-quant\n\n\noptions.studies\nR > Financial Instruments and Pricing\n2015-12-17\nhttps://github.com/taylorizing/options.studies\noptions trading studies functions for use with options.data package and shiny.\nTrue\nFalse\ntaylorizing/options.studies\n\n\nPortfolioAnalytics\nR > Financial Instruments and Pricing\n2021-05-09\nhttps://github.com/braverock/PortfolioAnalytics\nPortfolio Analysis, Including Numerical Methods for Optimizationof Portfolios.\nTrue\nFalse\nbraverock/PortfolioAnalytics\n\n\nfmbasics\nR > Financial Instruments and Pricing\n2019-12-03\nhttps://github.com/imanuelcostigan/fmbasics\nFinancial Market Building Blocks.\nTrue\nFalse\nimanuelcostigan/fmbasics\n\n\nR-fixedincome\nR > Financial Instruments and Pricing\n2022-05-11\nhttps://github.com/wilsonfreitas/R-fixedincome\nFixed income tools for R.\nTrue\nFalse\nwilsonfreitas/R-fixedincome\n\n\nbacktest\nR > Trading\n\nhttps://cran.r-project.org/web/packages/backtest/index.html\nExploring Portfolio-Based Conjectures About Financial Instruments.\nFalse\nTrue\n\n\n\npa\nR > Trading\n\nhttps://cran.r-project.org/web/packages/pa/index.html\nPerformance Attribution for Equity Portfolios.\nFalse\nTrue\n\n\n\nTTR\nR > Trading\n2022-05-22\nhttps://github.com/joshuaulrich/TTR\nTechnical Trading Rules.\nTrue\nFalse\njoshuaulrich/TTR\n\n\nQuantTools\nR > Trading\n\nhttps://quanttools.bitbucket.io/_site/index.html\nEnhanced Quantitative Trading Modelling.\nFalse\nFalse\n\n\n\nblotter\nR > Trading\n2022-04-04\nhttps://github.com/braverock/blotter\nTransaction 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.\nTrue\nFalse\nbraverock/blotter\n\n\nquantstrat\nR > Backtesting\n2021-03-05\nhttps://github.com/braverock/quantstrat\nTransaction-oriented infrastructure for constructing trading systems and simulation. Provides support for multi-asset class and multi-currency portfolios for backtesting and other financial research.\nTrue\nFalse\nbraverock/quantstrat\n\n\nPerformanceAnalytics\nR > Risk Analysis\n2022-01-07\nhttps://github.com/braverock/PerformanceAnalytics\nEconometric tools for performance and risk analysis.\nTrue\nFalse\nbraverock/PerformanceAnalytics\n\n\nFactorAnalytics\nR > Factor Analysis\n2022-03-26\nhttps://github.com/braverock/FactorAnalytics\nThe 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.\nTrue\nFalse\nbraverock/FactorAnalytics\n\n\nExpected Returns\nR > Factor Analysis\n2022-03-27\nhttps://github.com/JustinMShea/ExpectedReturns\nSolutions for enhancing portfolio diversification and replications of seminal papers with R, most of which are discussed in one of the best investment references of the recent decade, Expected Returns: An Investors Guide to Harvesting Market Rewards by Antti Ilmanen.\nTrue\nFalse\nJustinMShea/ExpectedReturns\n\n\ntseries\nR > Time Series\n\nhttps://cran.r-project.org/web/packages/tseries/index.html\nTime Series Analysis and Computational Finance.\nFalse\nTrue\n\n\n\nfGarch\nR > Time Series\n\nhttps://cran.r-project.org/web/packages/fGarch/index.html\nRmetrics - Autoregressive Conditional Heteroskedastic Modelling.\nFalse\nTrue\n\n\n\ntimeSeries\nR > Time Series\n\nhttps://cran.r-project.org/web/packages/timeSeries/index.html\nRmetrics - Financial Time Series Objects.\nFalse\nTrue\n\n\n\nrugarch\nR > Time Series\n2022-04-19\nhttps://github.com/alexiosg/rugarch\nUnivariate GARCH Models.\nTrue\nFalse\nalexiosg/rugarch\n\n\nrmgarch\nR > Time Series\n2022-03-05\nhttps://github.com/alexiosg/rmgarch\nMultivariate GARCH Models.\nTrue\nFalse\nalexiosg/rmgarch\n\n\ntidypredict\nR > Time Series\n2021-09-28\nhttps://github.com/edgararuiz/tidypredict\nRun predictions inside the database https://tidypredict.netlify.com/.\nTrue\nFalse\nedgararuiz/tidypredict\n\n\ntidyquant\nR > Time Series\n2022-05-20\nhttps://github.com/business-science/tidyquant\nBringing financial analysis to the tidyverse.\nTrue\nFalse\nbusiness-science/tidyquant\n\n\ntimetk\nR > Time Series\n2022-05-31\nhttps://github.com/business-science/timetk\nA toolkit for working with time series in R.\nTrue\nFalse\nbusiness-science/timetk\n\n\ntibbletime\nR > Time Series\n2021-02-18\nhttps://github.com/business-science/tibbletime\nBuilt 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.\nTrue\nFalse\nbusiness-science/tibbletime\n\n\nmatrixprofile\nR > Time Series\n2021-06-26\nhttps://github.com/matrix-profile-foundation/matrixprofile\nTime series data mining library built on top of the novel Matrix Profile data structure and algorithms.\nTrue\nFalse\nmatrix-profile-foundation/matrixprofile\n\n\ngarchmodels\nR > Time Series\n2021-08-10\nhttps://github.com/AlbertoAlmuinha/garchmodels\nA parsnip backend for GARCH models.\nTrue\nFalse\nAlbertoAlmuinha/garchmodels\n\n\ntimeDate\nR > Calendars\n\nhttps://cran.r-project.org/web/packages/timeDate/index.html\nChronological and Calendar Objects\nFalse\nTrue\n\n\n\nbizdays\nR > Calendars\n2022-05-10\nhttps://github.com/wilsonfreitas/R-bizdays\nBusiness days calculations and utilities\nTrue\nFalse\nwilsonfreitas/R-bizdays\n\n\nQUANTAXIS\nMatlab > FrameWorks\n2022-05-18\nhttps://github.com/yutiansut/quantaxis\nIntegrated Quantitative Toolbox with Matlab.\nTrue\nFalse\nyutiansut/quantaxis\n\n\nQuantLib.jl\nJulia\n2020-02-18\nhttps://github.com/pazzo83/QuantLib.jl\nQuantlib implementation in pure Julia.\nTrue\nFalse\npazzo83/QuantLib.jl\n\n\nIto.jl\nJulia\n2017-03-21\nhttps://github.com/aviks/Ito.jl\nA Julia package for quantitative finance.\nTrue\nFalse\naviks/Ito.jl\n\n\nTALib.jl\nJulia\n2017-08-22\nhttps://github.com/femtotrader/TALib.jl\nA Julia wrapper for TA-Lib.\nTrue\nFalse\nfemtotrader/TALib.jl\n\n\nMiletus.jl\nJulia\n2021-03-06\nhttps://github.com/JuliaComputing/Miletus.jl\nA financial contract definition, modeling language, and valuation framework.\nTrue\nFalse\nJuliaComputing/Miletus.jl\n\n\nTemporal.jl\nJulia\n2021-12-28\nhttps://github.com/dysonance/Temporal.jl\nFlexible and efficient time series class & methods.\nTrue\nFalse\ndysonance/Temporal.jl\n\n\nIndicators.jl\nJulia\n2021-12-28\nhttps://github.com/dysonance/Indicators.jl\nFinancial market technical analysis & indicators on top of Temporal.\nTrue\nFalse\ndysonance/Indicators.jl\n\n\nStrategems.jl\nJulia\n2021-04-06\nhttps://github.com/dysonance/Strategems.jl\nQuantitative systematic trading strategy development and backtesting.\nTrue\nFalse\ndysonance/Strategems.jl\n\n\nTimeSeries.jl\nJulia\n2022-01-11\nhttps://github.com/JuliaStats/TimeSeries.jl\nTime series toolkit for Julia.\nTrue\nFalse\nJuliaStats/TimeSeries.jl\n\n\nMarketTechnicals.jl\nJulia\n2021-07-12\nhttps://github.com/JuliaQuant/MarketTechnicals.jl\nTechnical analysis of financial time series on top of TimeSeries.\nTrue\nFalse\nJuliaQuant/MarketTechnicals.jl\n\n\nMarketData.jl\nJulia\n2022-04-19\nhttps://github.com/JuliaQuant/MarketData.jl\nTime series market data.\nTrue\nFalse\nJuliaQuant/MarketData.jl\n\n\nTimeFrames.jl\nJulia\n2019-02-16\nhttps://github.com/femtotrader/TimeFrames.jl\nA Julia library that defines TimeFrame (essentially for resampling TimeSeries).\nTrue\nFalse\nfemtotrader/TimeFrames.jl\n\n\nStrata\nJava\n\nhttp://strata.opengamma.io/\nModern open-source analytics and market risk library designed and written in Java.\nFalse\nFalse\n\n\n\nJQuantLib\nJava\n\nhttp://www.jquantlib.org\nJQuantLib is a free, open-source, comprehensive framework for quantitative finance, written in 100% Java.\nFalse\nFalse\n\n\n\nfinmath.net\nJava\n\nhttp://finmath.net\nJava library with algorithms and methodologies related to mathematical finance.\nFalse\nFalse\n\n\n\nquantcomponents\nJava\n2015-10-07\nhttps://github.com/lsgro/quantcomponents\nFree Java components for Quantitative Finance and Algorithmic Trading.\nTrue\nFalse\nlsgro/quantcomponents\n\n\nDRIP\nJava\n\nhttps://lakshmidrip.github.io/DRIP\nFixed Income, Asset Allocation, Transaction Cost Analysis, XVA Metrics Libraries.\nFalse\nFalse\n\n\n\nta4j\nJava\n2021-10-11\nhttps://github.com/ta4j/ta4j\nA Java library for technical analysis.\nTrue\nFalse\nta4j/ta4j\n\n\nfinance.js\nJavaScript\n2018-10-11\nhttps://github.com/ebradyjobory/finance.js\nA JavaScript library for common financial calculations.\nTrue\nFalse\nebradyjobory/finance.js\n\n\nportfolio-allocation\nJavaScript\n2020-10-09\nhttps://github.com/lequant40/portfolio_allocation_js\nPortfolioAllocation is a JavaScript library designed to help constructing financial portfolios made of several assets: bonds, commodities, cryptocurrencies, currencies, exchange traded funds (ETFs), mutual funds, stocks…\nTrue\nFalse\nlequant40/portfolio_allocation_js\n\n\nGhostfolio\nJavaScript\n2022-06-04\nhttps://github.com/ghostfolio/ghostfolio\nWealth management software to keep track of financial assets like stocks, ETFs or cryptocurrencies and make solid, data-driven investment decisions.\nTrue\nFalse\nghostfolio/ghostfolio\n\n\nIndicatorTS\nJavaScript\n2022-06-03\nhttps://github.com/cinar/indicatorts\nIndicator is a TypeScript module providing various stock technical analysis indicators, strategies, and a backtest framework for trading.\nTrue\nFalse\ncinar/indicatorts\n\n\nccxt\nJavaScript\n2022-06-04\nhttps://github.com/ccxt/ccxt\nA JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges.\nTrue\nFalse\nccxt/ccxt\n\n\nQUANTAXIS_Webkit\nJavaScript > Data Visualization\n2017-07-30\nhttps://github.com/yutiansut/QUANTAXIS_Webkit\nAn awesome visualization center based on quantaxis.\nTrue\nFalse\nyutiansut/QUANTAXIS_Webkit\n\n\nquantfin\nHaskell\n2019-04-06\nhttps://github.com/boundedvariation/quantfin\nquant finance in pure haskell.\nTrue\nFalse\nboundedvariation/quantfin\n\n\nhqfl\nHaskell\n2018-10-03\nhttps://github.com/co-category/hqfl\nHaskell Quantitative Finance Library.\nTrue\nFalse\nco-category/hqfl\n\n\nHaxcel\nHaskell\n2020-09-01\nhttps://github.com/MarcusRainbow/Haxcel\nExcel Addin for Haskell.\nTrue\nFalse\nMarcusRainbow/Haxcel\n\n\nFfinar\nHaskell\n2021-11-26\nhttps://github.com/MarcusRainbow/Ffinar\nA financial maths library in Haskell.\nTrue\nFalse\nMarcusRainbow/Ffinar\n\n\nQuantScale\nScala\n2014-01-14\nhttps://github.com/choucrifahed/quantscale\nScala Quantitative Finance Library.\nTrue\nFalse\nchoucrifahed/quantscale\n\n\nScala Quant\nScala\n2017-05-06\nhttps://github.com/frankcash/Scala-Quant\nScala library for working with stock data from IFTTT recipes or Google Finance.\nTrue\nFalse\nfrankcash/Scala-Quant\n\n\nJiji\nRuby\n2019-01-22\nhttps://github.com/unageanu/jiji2\nOpen Source Forex algorithmic trading framework using OANDA REST API.\nTrue\nFalse\nunageanu/jiji2\n\n\nTai\nElixir/Erlang\n2022-06-02\nhttps://github.com/fremantle-capital/tai\nOpen Source composable, real time, market data and trade execution toolkit.\nTrue\nFalse\nfremantle-capital/tai\n\n\nWorkbench\nElixir/Erlang\n2022-06-01\nhttps://github.com/fremantle-industries/workbench\nFrom Idea to Execution - Manage your trading operation across a globally distributed cluster\nTrue\nFalse\nfremantle-industries/workbench\n\n\nProp\nElixir/Erlang\n2022-06-01\nhttps://github.com/fremantle-industries/prop\nAn open and opinionated trading platform using productive & familiar open source libraries and tools for strategy research, execution and operation.\nTrue\nFalse\nfremantle-industries/prop\n\n\nKelp\nGolang\n2021-11-26\nhttps://github.com/stellar/kelp\nKelp is an open-source Golang algorithmic cryptocurrency trading bot that runs on centralized exchanges and Stellar DEX (command-line usage and desktop GUI).\nTrue\nFalse\nstellar/kelp\n\n\nmarketstore\nGolang\n2022-06-03\nhttps://github.com/alpacahq/marketstore\nDataFrame Server for Financial Timeseries Data.\nTrue\nFalse\nalpacahq/marketstore\n\n\nIndicatorGo\nGolang\n2022-06-04\nhttps://github.com/cinar/indicator\nIndicatorGo is a Golang module providing various stock technical analysis indicators, strategies, and a backtest framework for trading.\nTrue\nFalse\ncinar/indicator\n\n\nTradeFrame\nCPP\n2022-01-03\nhttps://github.com/rburkholder/trade-frame\nC++ 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 calculation library.\nTrue\nFalse\nrburkholder/trade-frame\n\n\nQuantLib\nFrameworks\n\nhttps://www.quantlib.org\nThe QuantLib project is aimed at providing a comprehensive software framework for quantitative finance.\nFalse\nFalse\n\n\n\nJQuantLib\nFrameworks\n\nhttp://www.jquantlib.org\nJava port.\nFalse\nFalse\n\n\n\nRQuantLib\nFrameworks\n\nhttp://dirk.eddelbuettel.com/code/rquantlib.html\nR port.\nFalse\nFalse\n\n\n\nQuantLibAddin\nFrameworks\n\nhttps://www.quantlib.org/quantlibaddin/\nExcel support.\nFalse\nFalse\n\n\n\nQuantLibXL\nFrameworks\n\nhttps://www.quantlib.org/quantlibxl/\nExcel support.\nFalse\nFalse\n\n\n\nQLNet\nFrameworks\n2022-05-23\nhttps://github.com/amaggiulli/qlnet\n.Net port.\nTrue\nFalse\namaggiulli/qlnet\n\n\nPyQL\nFrameworks\n2022-05-17\nhttps://github.com/enthought/pyql\nPython port.\nTrue\nFalse\nenthought/pyql\n\n\nQuantLib.jl\nFrameworks\n2020-02-18\nhttps://github.com/pazzo83/QuantLib.jl\nJulia port.\nTrue\nFalse\npazzo83/QuantLib.jl\n\n\nTA-Lib\nFrameworks\n\nhttps://ta-lib.org\nperform technical analysis of financial market data.\nFalse\nFalse\n\n\n\nPortfolio Optimizer\nFrameworks\n\nhttps://portfoliooptimizer.io/\nPortfolio Optimizer is a Web API for portfolio analysis and optimization.\nFalse\nFalse\n\n\n\nQuantConnect\nCSharp\n2022-06-03\nhttps://github.com/QuantConnect/Lean\nLean Engine is an open-source fully managed C# algorithmic trading engine built for desktop and cloud usage.\nTrue\nFalse\nQuantConnect/Lean\n\n\nStockSharp\nCSharp\n2022-04-29\nhttps://github.com/StockSharp/StockSharp\nAlgorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).\nTrue\nFalse\nStockSharp/StockSharp\n\n\nTDAmeritrade.DotNetCore\nCSharp\n2021-09-26\nhttps://github.com/NVentimiglia/TDAmeritrade.DotNetCore\nFree, open-source .NET Client for the TD Ameritrade Trading Platform. Helps developers integrate TD Ameritrade API into custom trading solutions.\nTrue\nFalse\nNVentimiglia/TDAmeritrade.DotNetCore\n\n\nQuantMath\nRust\n2020-05-28\nhttps://github.com/MarcusRainbow/QuantMath\nFinancial maths library for risk-neutral pricing and risk\nTrue\nFalse\nMarcusRainbow/QuantMath\n\n\nDerman Papers\nReproducing Works, Training & Books\n2017-10-21\nhttps://github.com/MarcosCarreira/DermanPapers\nNotebooks that replicate original quantitative finance papers from Emanuel Derman.\nTrue\nFalse\nMarcosCarreira/DermanPapers\n\n\nML-Quant\nReproducing Works, Training & Books\n\nhttps://www.ml-quant.com/\nTop Quant resources like ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos, and Blogs.\nFalse\nFalse\n\n\n\nvolatility-trading\nReproducing Works, Training & Books\n2021-11-29\nhttps://github.com/jasonstrimpel/volatility-trading\nA complete set of volatility estimators based on Euan Sinclair’s Volatility Trading.\nTrue\nFalse\njasonstrimpel/volatility-trading\n\n\nquant\nReproducing Works, Training & Books\n2015-07-14\nhttps://github.com/paulperry/quant\nQuantitative Finance and Algorithmic Trading exhaust; mostly ipython notebooks based on Quantopian, Zipline, or Pandas.\nTrue\nFalse\npaulperry/quant\n\n\nfecon235\nReproducing Works, Training & Books\n2018-12-03\nhttps://github.com/rsvp/fecon235\nOpen source project for software tools in financial economics. Many jupyter notebook to verify theoretical ideas and practical methods interactively.\nTrue\nFalse\nrsvp/fecon235\n\n\nQuantitative-Notebooks\nReproducing Works, Training & Books\n2020-07-02\nhttps://github.com/LongOnly/Quantitative-Notebooks\nEducational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy\nTrue\nFalse\nLongOnly/Quantitative-Notebooks\n\n\nQuantEcon\nReproducing Works, Training & Books\n\nhttps://quantecon.org/\nLecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks\nFalse\nFalse\n\n\n\nFinanceHub\nReproducing Works, Training & Books\n2021-05-25\nhttps://github.com/Finance-Hub/FinanceHub\nResources for Quantitative Finance\nTrue\nFalse\nFinance-Hub/FinanceHub\n\n\nPython_Option_Pricing\nReproducing Works, Training & Books\n2017-07-26\nhttps://github.com/dedwards25/Python_Option_Pricing\nAn libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.\nTrue\nFalse\ndedwards25/Python_Option_Pricing\n\n\npython-training\nReproducing Works, Training & Books\n2022-05-06\nhttps://github.com/jpmorganchase/python-training\nJ.P. Morgan’s Python training for business analysts and traders.\nTrue\nFalse\njpmorganchase/python-training\n\n\nStock_Analysis_For_Quant\nReproducing Works, Training & Books\n2022-06-04\nhttps://github.com/LastAncientOne/Stock_Analysis_For_Quant\nDifferent Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.\nTrue\nFalse\nLastAncientOne/Stock_Analysis_For_Quant\n\n\nalgorithmic-trading-with-python\nReproducing Works, Training & Books\n2021-06-01\nhttps://github.com/chrisconlan/algorithmic-trading-with-python\nSource code for Algorithmic Trading with Python (2020) by Chris Conlan.\nTrue\nFalse\nchrisconlan/algorithmic-trading-with-python\n\n\nMEDIUM_NoteBook\nReproducing Works, Training & Books\n2022-05-18\nhttps://github.com/cerlymarco/MEDIUM_NoteBook\nRepository containing notebooks of cerlymarco’s posts on Medium.\nTrue\nFalse\ncerlymarco/MEDIUM_NoteBook\n\n\nQuantFinance\nReproducing Works, Training & Books\n2022-03-12\nhttps://github.com/PythonCharmers/QuantFinance\nTraining materials in quantitative finance.\nTrue\nFalse\nPythonCharmers/QuantFinance\n\n\nMarketAnalysis\nReproducing Works, Training & Books\n2020-08-06\nhttps://github.com/Poseyy/MarketAnalysis\nImplementing many different methods and popular analysis tools in Python.\nTrue\nFalse\nPoseyy/MarketAnalysis\n\n\nIPythonScripts\nReproducing Works, Training & Books\n2018-11-18\nhttps://github.com/mgroncki/IPythonScripts\nTutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning.\nTrue\nFalse\nmgroncki/IPythonScripts\n\n\nComputational-Finance-Course\nReproducing Works, Training & Books\n2021-10-12\nhttps://github.com/LechGrzelak/Computational-Finance-Course\nMaterials for the course of Computational Finance.\nTrue\nFalse\nLechGrzelak/Computational-Finance-Course\n\n\nMachine-Learning-for-Asset-Managers\nReproducing Works, Training & Books\n2021-09-01\nhttps://github.com/emoen/Machine-Learning-for-Asset-Managers\nImplementation 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.\nTrue\nFalse\nemoen/Machine-Learning-for-Asset-Managers\n\n\nPython-for-Finance-Cookbook\nReproducing Works, Training & Books\n2022-05-26\nhttps://github.com/PacktPublishing/Python-for-Finance-Cookbook\nPython for Finance Cookbook, published by Packt.\nTrue\nFalse\nPacktPublishing/Python-for-Finance-Cookbook\n\n\nmodelos_vol_derivativos\nReproducing Works, Training & Books\n2021-09-15\nhttps://github.com/ysaporito/modelos_vol_derivativos\n“Modelos de Volatilidade para Derivativos” book’s Jupyter notebooks\nTrue\nFalse\nysaporito/modelos_vol_derivativos\n\n\nNMOF\nReproducing Works, Training & Books\n2022-05-13\nhttps://github.com/enricoschumann/NMOF\nFunctions, 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).\nTrue\nFalse\nenricoschumann/NMOF\n\n\npy4fi2nd\nReproducing Works, Training & Books\n2021-08-08\nhttps://github.com/yhilpisch/py4fi2nd\nJupyter Notebooks and code for Python for Finance (2nd ed., O’Reilly) by Yves Hilpisch.\nTrue\nFalse\nyhilpisch/py4fi2nd\n\n\naiif\nReproducing Works, Training & Books\n2022-01-19\nhttps://github.com/yhilpisch/aiif\nJupyter Notebooks and code for the book Artificial Intelligence in Finance (O’Reilly) by Yves Hilpisch.\nTrue\nFalse\nyhilpisch/aiif\n\n\npy4at\nReproducing Works, Training & Books\n2021-07-08\nhttps://github.com/yhilpisch/py4at\nJupyter Notebooks and code for the book Python for Algorithmic Trading (O’Reilly) by Yves Hilpisch.\nTrue\nFalse\nyhilpisch/py4at\n\n\ndawp\nReproducing Works, Training & Books\n2021-02-22\nhttps://github.com/yhilpisch/dawp\nJupyter Notebooks and code for Derivatives Analytics with Python (Wiley Finance) by Yves Hilpisch.\nTrue\nFalse\nyhilpisch/dawp\n\n\ndx\nReproducing Works, Training & Books\n2020-12-17\nhttps://github.com/yhilpisch/dx\nDX Analytics\nFinancial and Derivatives Analytics with Python.\nTrue\nFalse\n\n\nQuantFinanceBook\nReproducing Works, Training & Books\n2021-03-10\nhttps://github.com/LechGrzelak/QuantFinanceBook\nQuantitative Finance book.\nTrue\nFalse\nLechGrzelak/QuantFinanceBook\n\n\nrough_bergomi\nReproducing Works, Training & Books\n2018-09-17\nhttps://github.com/ryanmccrickerd/rough_bergomi\nA Python implementation of the rough Bergomi model.\nTrue\nFalse\nryanmccrickerd/rough_bergomi\n\n\nfrh-fx\nReproducing Works, Training & Books\n2018-05-24\nhttps://github.com/ryanmccrickerd/frh-fx\nA python implementation of the fast-reversion Heston model of Mechkov for FX purposes.\nTrue\nFalse\nryanmccrickerd/frh-fx\n\n\nvalue-investing-studies\nReproducing Works, Training & Books\n2021-10-26\nhttps://github.com/euclidjda/value-investing-studies\nA collection of data analysis studies that examine the performance and characteristics of value investing over long periods of time.\nTrue\nFalse\neuclidjda/value-investing-studies\n\n\nmachine-learning-asset-management\nReproducing Works, Training & Books\n2021-12-17\nhttps://github.com/firmai/machine-learning-asset-management\nMachine Learning in Asset Management (by @firmai).\nTrue\nFalse\nfirmai/machine-learning-asset-management\n\n\nDeep-Learning-Machine-Learning-Stock\nReproducing Works, Training & Books\n2022-06-01\nhttps://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock\nDeep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.\nTrue\nFalse\nLastAncientOne/Deep-Learning-Machine-Learning-Stock\n\n\nTechnical_Analysis_and_Feature_Engineering\nReproducing Works, Training & Books\n2021-08-19\nhttps://github.com/jo-cho/Technical_Analysis_and_Feature_Engineering\nFeature Engineering and Feature Importance of Machine Learning in Financial Market.\nTrue\nFalse\njo-cho/Technical_Analysis_and_Feature_Engineering\n\n\nBarter\nRust\n2022-10-18\nhttps://github.com/barter-rs/barter-rs\nOpen-source Rust framework for building event-driven live-trading & backtesting systems\nTrue\nFalse\nbarter-rs/barter-rs"
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