121 Open source projects that are alternatives of or similar to Quantlib

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

Open source analytics and market risk library from OpenGamma

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

Application of machine learning to the Coinbase (GDAX) orderbook

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

Algorithmic trading strategies

Using python and scikit-learn to make stock predictions

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

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.

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。

Quantitative Finance tools

A curated list of awesome algorithmic trading frameworks, libraries, software and resources

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

Master repository for the pandas-ml modules

Slide show presentations regarding data driven investing.

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

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

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

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

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

Quantitative systematic trading strategy development and backtesting in Julia

Introducing neural networks to predict stock prices

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

Technical Indicators implemented in Python using Pandas

Python driver for MarketStore

Use unsupervised and supervised learning to predict stocks

Collection of notebooks about quantitative finance, with interactive python code.

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

A framework for systemic risk valuation and analysis.

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

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.

(no longer maintained) A simple yet robust (stock+options) API client for Robinhood

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

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

Determine optimal rebalancing of a passive stock portfolio.

Source code for my personal blog

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

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.

Performance tear sheets and backtest analysis for Moonshot

Deep learning for forecasting company fundamental data

Notebooks based on financial machine learning.

Quantitative finance research tools in Python

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

modular quant framework.

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

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

Backtesting for sleepless cryptocurrency markets

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

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

Quantitative Interview Preparation Guide, updated version here ==>

Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).

Vectorized backtester and trading engine for QuantRocket

Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

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

QTPyLib, Pythonic Algorithmic Trading

An open source library for portfolio optimisation

The foundational library of the Morpheus data science framework

QuantLib wrappers to other languages

A curated list of practical financial machine learning tools and applications.

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