249 Open source projects that are alternatives of or similar to Qtpylib

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

Quantitative analysis, strategies and backtests

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

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

Detects arbitrage opportunities across 131 cryptocurrency exchanges in 50 countries

Backtest and live trading in Python

Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot

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

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.

A C++ stock market algorithmic trading bot

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

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

Deep Neural Network Trading collection of Tensorflow Jupyter notebooks

A financial trading method using machine learning.

A stream-based approach to algorithmic trading and backtesting in Node.js

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

modular quant framework.

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

Introducing neural networks to predict stock prices

National Stock Exchange (NSE), India based Stock screener program. Supports Live Data, Swing / Momentum Trading, Intraday Trading, Connect to online brokers as Zerodha Kite, Risk Management, Emotion Control, Screening, Strategies, Backtesting, Automatic Stock Downloading after closing, live free day trading data and much more

Cira algorithmic trading made easy. A Façade library for simpler interaction with alpaca-trade-API from Alpaca Markets.

algorithmic trading using machine learning

Some notebooks with powerful trading strategies.

Volatile: your day-to-day trading companion.

A Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.

Common financial technical indicators implemented in Pandas.

PortfolioLab is a python library that enables traders to take advantage of the latest portfolio optimisation algorithms used by professionals in the industry.

Cloud-native Financial Reinforcement Learning

Notebooks based on financial machine learning.

A working example algorithm for scalping strategy trading multiple stocks concurrently using python asyncio

Using python and scikit-learn to make stock predictions

A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine

Use unsupervised and supervised learning to predict stocks

An open source library for portfolio optimisation

Vectorized backtester and trading engine for QuantRocket

ezIBpy, a Pythonic Client for Interactive Brokers API

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

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

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.

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

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

Performance tear sheets and backtest analysis for Moonshot

Algorithmic trading framework for cryptocurrencies.

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

super-monorepo for machine learning and algorithmic trading

51bitquant Python数字货币量化交易视频 CCXT框架 爬取交易所数据 比特币量化交易 交易机器人51bitquant tradingbot cryptocurrency quantitative trading btc trading

Portfolio analytics for quants, written in Python

Find big moving stocks before they move using machine learning and anomaly detection

阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/

Master repository for the pandas-ml modules

Free, open-source crypto trading bot, automated bitcoin / cryptocurrency trading software, algorithmic trading bots. Visually design your crypto trading bot, leveraging an integrated charting system, data-mining, backtesting, paper trading, and multi-server crypto bot deployments.

🔎 📈 🐍 💰 Backtest trading strategies in Python.

Open source analytics and market risk library from OpenGamma

Quantitative Financial Modelling Framework

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

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

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

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