Open Source Python Investment Management Software

Fully written in python which is one of the most used programming languages due to its simplified syntax and shallow learning curve. It is the first time in history that users, regardless of their background, can so easily add features to an investment research platform. The MIT Open Source license allows any user to fork the project to either add features to the broader community or create their own customized terminal version. The terminal allows for users to import their own proprietary datasets to use on our econometric menu. In addition, users are allowed to export any type of data to any type of format whether that is raw data in Excel or an image in PNG. This is ideal for finance content creation. Create notebook templates (through papermill) which can be run on different tickers. This level of automation allows to speed up the development of your investment thesis and reduce human error.

Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models, such as financial time series loss model, deep pattern quality assessment model, long and short pattern combination evaluation model, long pattern stop-loss strategy model, short pattern covering strategy model, big data K-line pattern Historical portfolio fitting model, trading position mentality model, dopamine quantification model, inertial residual resistance support model, long-short swap revenge probability model, strong and weak confrontation model, trend angle change rate model, etc.

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. With Qlib, users can easily try their ideas to create better Quant investment strategies. At the module level, Qlib is a platform that consists of above components. The components are designed as loose-coupled modules and each component could be used stand-alone.

TradeMaster is a first-of-its-kind, best-in-class open-source platform for quantitative trading (QT) empowered by reinforcement learning (RL), which covers the full pipeline for the design, implementation, evaluation and deployment of RL-based algorithms. TradeMaster is composed of 6 key modules: 1) multi-modality market data of different financial assets at multiple granularities; 2) whole data preprocessing pipeline; 3) a series of high-fidelity data-driven market simulators for mainstream QT tasks; 4) efficient implementations of over 13 novel RL-based trading algorithms; 5) systematic evaluation toolkits with 6 axes and 17 measures; 6) different interfaces for interdisciplinary users.

QuickFIX is the worlds first Open Source C++ FIX (Financial Information eXchange) engine, helping financial institutions easily integrate with each other. The SVN repository is now locked. Latest code is hosted at github. https://github.com/quickfix/quickfix

Trading system written in Python including Quotes Management, Historical and live data, Import/Export data, Charting, Candlestick, Technical analysis, automated alerts, portfolio management, risk management, currency exchange, and much much more ...

A portfolio tracking, analytics, accounting and tax reporting application that respects your privacy

Cryptocheck monitors balances of your cryptocurrency addresses and raises an alert in case of any change detected. It connects to known block explorer API services to verify balances. It is useful for long-term investors with multiple different cryptocurrencies in their portfolio. You no longer need to access all your wallets with passwords to simply just check that your money are still there. Cryptocheck also provides a simple profit calculation and history charts mapping your portfolio history. And there is also a server node available! It continuously monitors balances, records history data and sends all the data to your Cryptocheck desktop application. Supported cryptocurrencies: https://sourceforge.net/p/cryptocheck/wiki/Home/#supported-cryptocurrencies For more details about Cryptocheck and how to use it, see wiki: https://sourceforge.net/p/cryptocheck/wiki I am open to add other cryptocurrencies on your request.

ManagerSheet is a one-page investment portfolio report, that analyses and presents an investment portfolio with respect to: - Performance - Investment style - Risk More information on the report concept and instructions on how to create one's own portfolio reports can be found at the ManagerSheet Web Site under the "Documentation" section. Please note that the project is in alpha stage.

QuotesViewer is a graphical tool giving you easy and fast access to quotes of all shares on the Euronext stock exchange. Quotes information can be searched and sorted on different criteria, ie. market, ISIN code, mnemonic, name, price, volume.

Trading Monkey allows you to download stock quotes from different sources, maintain database of stock quotes history and run back tests of different stock trading strategies.

Avidus is a financial charting, technical analysis, and trading strategy platform.

Cashderivatives.org Pricing Calculator (CDPC) is a calculator for financial instruments. The project is now discontinued. The project had reached alpha development status, when it was decided to not continue with the project.

A Python script to gather DOW Jones trend data from generationaldynamics.com, and parse the data into a csv file so that it can be easily charted.

Analyze, winning percentage, back test and estimate the maximum rate of return from the historical prices of an equity stock listed in NSE, India between any two selected dates for more than 20 years. INVESTOCK program is used to get the historical prices of an Indian share listed in National Stock Exchange( NSE), India between any two selected dates. All the shares listed in National Stock Exchange (NSE), India can be analyzed. Interactive graphs will be displayed for the analyzed data and it can be downloaded in any desired formats. Predict the winning percentage of an equity. All the analyzed data can be saved in .CSV file format for further analysis. Maximum Profit & Loss of an equity can be estimated between the selected dates. Designed by Dr. M Kanagasabapathy Coded in Python Project Homepage: https://www.enote.page/ Twitter handle: @nifty_analyst This is the basic version and for advanced options & analyses, please write to me.

IbPy is a port of the API provided by Interactive Brokers (http://www.interactivebrokers.com/) to the Python language.

A collection of portfolio management components. Sharpe Model for selection of an initial portfolio is already implemented. A genetic algorithms package, also written in java, is used for the search of the best portfolio variants.

Web-based Stock Market application

Mibian Lib is an open source options pricing library in python

ProfitPy is a set of libraries and tools for the development, testing, and execution of automated trading systems.

This project aims to provide a user friendly interface to the historical stock data available from Bovespa (Brazil's main stock exchange), enabling users to easily check quotes for specific stocks at a chosen date.

Get the information of the Chinese ShangHai & ShenZhen A Quote market, and Forex data, and World Index.

SX watchdog states for Stock Exchange Watchdog. It helps to easillly follow the stock exchange. It's a Python program, able to save data in files and to generate HTML reports over a specific period.

ShareWatch - a client/server utility that keeps you up to date with share prices; uses free data (across multiple exchanges); provides a stock ticker and wxHTML window to display prices; chart downloading; platform independence. (Python/wxPython/SOAP)

The purpose of this program is to prove that given a finite number of Monkeys and a finite amount of time one monkey will be able to make more money off the stock market than any human being. Checkout our web site for an uncorrupted download.