Top 122 quantitative-finance open source projects

Datasets, tools and more from Darwinex Labs - Prop Investing Arm & Quant Team @ Darwinex

A stock backtesting engine written in modern Java. And a pairs trading (cointegration) strategy implementation using a bayesian kalman filter model

An application that allows you to design and test your own stock trading algorithms in an attempt to beat the market.

ezIBpy, a Pythonic Client for Interactive Brokers API

High-performance TensorFlow library for quantitative finance.

The QuantLib C++ library

An open source library for portfolio optimisation

Quantitative finance research tools in Python

The foundational library of the Morpheus data science framework

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

Here you can find all the quantitative finance algorithms that I've worked on and refined over the past year!

Quantitative Interview Preparation Guide, updated version here ==>

QuantLib wrappers to other languages

quantitative security portfolio analysis. The analysis pipeline including data storage abstraction, alpha calculation, ML based alpha combining and portfolio calculation.

Slide show presentations regarding data driven investing.

Stock indicator technical analysis library package for .NET. Send in historical price quotes and get back desired technical indicators. Nothing more. It can be used in any market analysis software using standard OHLCV price quotes for equities, commodities, forex, cryptocurrencies, and others. We had private trading algorithms, machine learning, and charting systems in mind when originally creating this community library. Current indicators include: Accumulation/Distribution Line (ADL), Aroon Oscillator, Arnaud Legoux Moving Average (ALMA), Average Directional Index (ADX), Average True Range (ATR), Awesome Oscillator (AO), Balance of Power (BOP), Beta Coefficient, Bollinger Bands®, Chaikin Money Flow (CMF), Chaikin Oscillator, Chandelier Exit, Choppiness Index (CHOP), Commodity Channel Index (CCI), ConnorsRSI, Correlation Coefficient, Donchian Channels, Double Exponential Moving Average (DEMA), Elder-ray Index, Exponential Moving Average (EMA), Force Index, Fractal Chaos Bands (FCB), Gator Oscillator, Heikin-Ashi, Hull Moving Average (HMA), Ichimoku Cloud, Kaufman's Adaptive Moving Average (KAMA), KDJ Index, Keltner Channels, Momentum Oscillator, Money Flow Index (MFI), MESA Adaptive Moving Averages (MAMA), Moving Average Convergence/Divergence (MACD), Moving Average Envelopes, On-balance Volume (OBV), Parabolic SAR (stop and reverse), Percentage Volume Oscillator (PVO), Pivot Points and Rolling Pivot Points, Price Channels, Price (Comparative) Relative Strength (PRS), Price Momentum Oscillator (PMO), Rate of Change (ROC), Relative Strength Index (RSI), R-Squared (Coefficient of Determination), Simple Moving Average (SMA), Slope and Linear Regression, Smoothed Moving Average (SMMA), Standard Deviation, Stoller Average Range Channel (STARC) Bands, Stochastic Oscillator, Stochastic RSI, SuperTrend, Tillson T3 Moving Average, Triple Exponential Moving Average (TEMA), Triple EMA Oscillator (TRIX), True Strength Index (TSI), Ulcer Index, Ultimate Oscillator, Volume Simple Moving Average, Volume Weighted Average Price (VWAP), Vortex Indicator (VI), Weighted Moving Average (WMA), Williams %R, Williams Alligator, Williams Fractal, and Zig Zag.

Powerful financial charting library based on R's Quantmod | http://py-quantmod.readthedocs.io/en/latest/

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

Guia de ejemplos didácticos en python temática finanzas bolsa trading argentina usa

Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD

A grid trading strategy and trading-bot for Binance Exchange. 币安交易所的网格交易

The Open-Source Backtesting Engine/ Market Simulator by Bertram Solutions.

(no longer maintained) A simple yet robust (stock+options) API client for Robinhood

Algorithmic trading strategies

Source code for my personal blog

A list of online resources for quantitative modeling, trading, portfolio management

Deep learning for forecasting company fundamental data

🐗 🐻 Deep Learning based Python Library for Stock Market Prediction and Modelling

modular quant framework.

Quantitative systematic trading strategy development and backtesting in Julia

Codera Quant is a Java framework for algorithmic trading strategies development, execution and backtesting via Interactive Brokers TWS API or other brokers API

算法交易系统，支持CTP、XTP、模拟交易及行情网关、回测。不断迭代更新中。

Vectorized backtester and trading engine for QuantRocket

Python driver for MarketStore

QTPyLib, Pythonic Algorithmic Trading

Quantitative Analysis Research see more at https://teddykoker.com

Use unsupervised and supervised learning to predict stocks

Quantitative Finance tools

A framework for systemic risk valuation and analysis.

Application of machine learning to the Coinbase (GDAX) orderbook

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

Master repository for the pandas-ml modules

Courses, Articles and many more which can help beginners or professionals.

This is a library to use with Robinhood Financial App. It currently supports trading crypto-currencies, options, and stocks. In addition, it can be used to get real time ticker information, assess the performance of your portfolio, and can also get tax documents, total dividends paid, and more. More info at

Determine optimal rebalancing of a passive stock portfolio.

Deep Hedging Demo - An Example of Using Machine Learning for Derivative Pricing.

🔬 A curated list of awesome machine learning strategies & tools in financial market.

Using python and scikit-learn to make stock predictions

Performance tear sheets and backtest analysis for Moonshot

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

Notebooks based on financial machine learning.

Open source analytics and market risk library from OpenGamma

Python wrapper for TA-Lib (http://ta-lib.org/).

⚠️ Deprecrated in favor of https://github.com/piquette/finance-go

Different Types of Stock Analysis in Python, R, Matlab, Excel, Power BI

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.

Backtesting for sleepless cryptocurrency markets

Introducing neural networks to predict stock prices

fastquant — Backtest and optimize your trading strategies with only 3 lines of code!

Python-based framework for backtesting trading strategies & analyzing financial markets [GUI ]