Related Projects

PyAlgoTrade - Python Algorithmic Trading Library

  •    Python

PyAlgoTrade is a Python Algorithmic Trading Library with focus on backtesting and support for paper-trading and live-trading. Let’s say you have an idea for a trading strategy and you’d like to evaluate it with historical data and see how it behaves. PyAlgoTrade allows you to do so with minimal effort.

TechAn - Technical Analysis Library for Golang

  •    Go

TechAn is a technical analysis library for Go! It provides a suite of tools and frameworks to analyze financial data and make trading decisions. Techan is heavily influenced by the great ta4j. It provides Basic and advanced technical analysis indicators, Profit and trade analysis and Strategy building.

Ta4j - Technical Analysis for Java

  •    Java

Ta4j is an open source Java library for technical analysis. It provides the basic components for creation, evaluation and execution of trading strategies. It is a powerful engine for building custom trading strategies. It supports more than 130 technical indicators (Aroon, ATR, moving averages, parabolic SAR, RSI, etc.).

Zipline - A Pythonic Algorithmic Trading Library

  •    Python

Zipline is a Pythonic algorithmic trading library. It is an event-driven system that supports both backtesting and live-trading. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies.Note: Installing Zipline via pip is slightly more involved than the average Python package. Simply running pip install zipline will likely fail if you've never installed any scientific Python packages before.


CCXT - A JavaScript / Python / PHP cryptocurrency trading library with support for more than 100 bitcoin/altcoin exchanges

  •    Javascript

CCXT – CryptoCurrency eXchange Trading Library. A JavaScript / Python / PHP library for cryptocurrency trading and e-commerce with support for many bitcoin/ether/altcoin exchange markets and merchant APIs. The CCXT library is used to connect and trade with cryptocurrency / altcoin exchanges and payment processing services worldwide. It provides quick access to market data for storage, analysis, visualization, indicator development, algorithmic trading, strategy backtesting, bot programming, webshop integration and related software engineering.

NowTrade - Algorithmic trading library with a focus on creating powerful strategies

  •    Python

NowTrade is an algorithmic trading library with a focus on creating powerful strategies using easily-readable and simple Python code. With the help of NowTrade, full blown stock/currency trading strategies, harnessing the power of machine learning, can be implemented with few lines of code. NowTrade strategies are not event driven like most other algorithmic trading libraries available. The strategies are implemented in a sequential manner (one line at a time) without worrying about events, callbacks, or object overloading.

Gekko-Strategies - Strategies to Gekko trading bot with backtests results and some useful tools.

  •    Javascript

Gekko Trading Bot. Repository of strategies which I found at Git and Google, orginal source is in README or .js file. Strategies was backtested, results are in backtest_database.csv file. I used ForksScraper and Gekko BacktestTool to create content of this repository.

TA-Lib- Technical Analysis Library

  •    Java

Technical analysis library with indicators like ADX, MACD, RSI, Stochastic, TRIX... This is not an end-user GUI trading or charting application. It is instead targeted to application developers using either Excel, .NET, Mono, Java, Perl, Python or C/C++.

Clairvoyant - Software designed to identify and monitor social/historical cues for short term stock movement

  •    Python

Using stock historical data, train a supervised learning algorithm with any combination of financial indicators. Rapidly backtest your model for accuracy and simulate investment portfolio performance.During the testing period, the model signals to buy or sell based on its prediction for price movement the following day. By putting your trading algorithm aside and testing for signal accuracy alone, you can rapidly build and test more reliable models.

Marketstore - DataFrame Server for Financial Timeseries Data

  •    Go

MarketStore is a database server optimized for financial timeseries data. You can think of it as an extensible DataFrame service that is accessible from anywhere in your system, at higher scalability. It is designed from the ground up to address scalability issues around handling large amounts of financial market data used in algorithmic trading backtesting, charting, and analyzing price history with data spanning many years, including tick-level for the all US equities or the exploding crypto currencies space. If you are struggling with managing lots of HDF5 files, this is perfect solution to your problem.

EclipseTrader

  •    Java

Stock exchange analysis system, featuring shares pricing watch, intraday and history charts with technical analysis indicators, level II/market depth view, news watching, automated trading systems, integrated trading. Based on Eclipse RCP framework.

Lean - Lean Algorithmic Trading Engine by QuantConnect (C#, Python, F#)

  •    CSharp

Lean Engine is an open-source fully managed C# algorithmic trading engine built for desktop and cloud usage. It was designed in Mono and operates in Windows, Linux and Mac platforms. Lean drives the web based algorithmic trading platform QuantConnect.Handle all messages from the algorithmic trading engine. Decide what should be sent, and where the messages should go. The result processing system can send messages to a local GUI, or the web interface.

catalyst - An Algorithmic Trading Library for Crypto-Assets in Python

  •    Python

Catalyst is an algorithmic trading library for crypto-assets written in Python. It allows trading strategies to be easily expressed and backtested against historical data (with daily and minute resolution), providing analytics and insights regarding a particular strategy's performance. Catalyst also supports live-trading of crypto-assets starting with four exchanges (Binance, Bitfinex, Bittrex, and Poloniex) with more being added over time. Catalyst empowers users to share and curate data and build profitable, data-driven investment strategies. Please visit catalystcrypto.io to learn more about Catalyst. Catalyst builds on top of the well-established Zipline project. We did our best to minimize structural changes to the general API to maximize compatibility with existing trading algorithms, developer knowledge, and tutorials. Join us on the Catalyst Forum for questions around Catalyst, algorithmic trading and technical support. We also have a Discord group with the #catalyst_dev and #catalyst_setup dedicated channels.

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

  •    CSharp

StockSharp (shortly S#) – are free set of programs for trading at any markets of the world (American, European, Asian, Russian, stocks, futures, options, Bitcoins, forex, etc.). You will be able to trade manually or automated trading (algorithmic trading robots, conventional or HFT).Available connections: FIX/FAST, LMAX, Rithmic, Fusion/Blackwood, Interactive Brokers, OpenECry, Sterling, IQFeed, ITCH, FXCM, QuantHouse, E*Trade, BTCE, BitStamp and many other. Any broker or partner broker (benefits).

bitcoin-trader - :moneybag: Bitcoin trading bot based on a simple exponential moving average (trading via Coinbase)

  •    Python

💰 Bitcoin trading bot based on a simple exponential moving average (trading via Coinbase).I'm trying to write a simple bot that sells bitcoin the moment it makes enough profit to pay for transaction fees, plus a small margin. It will do this thousands of times per day, and hopefully profit in the long run as long as the market is volatile and trending upwards (i.e. as long as not too many people are running bots exactly like this one).

Market Analysis System

  •    Java

System for analysis of financial markets using technical analysis. Includes facilities for stock charting and futures charting, as well as automated generation of trading signals based on user-selected criteria. Operates on both daily and intraday data.

alphalens - Performance analysis of predictive (alpha) stock factors

  •    Jupyter

Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline open source backtesting library, and Pyfolio which provides performance and risk analysis of financial portfolios.Check out the example notebooks for more on how to read and use the factor tear sheet.

Personae - 📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading

  •    Python

Personae is a repo that implements papers proposed methods in Deep Reinforcement Learning & Supervised Learning and applies them to Financial Market. It will start from 2018-08-24 to 2018-09-01 a timestamp that I successfully found a job.

JQuantLib - Comprehensive framework for quantitative finance

  •    Java

JQuantLib is a comprehensive framework for quantitative finance, written in 100% Java. It provides "quants" and Java application developers several mathematical and statistical tools needed for the valuation of shares, options, futures, swaps, and other financial instruments. JQuantLib is based on QuantLib, a well known open-source library for quantitative finance, written in C++. JQuantLib aims to be a complete rewrite of QuantLib, offering features Java developers expect to find. It aims to be fast, correct, strongly typed, well-documented, and user-friendly.