Open Source Python Financial Software
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Python Financial Software
View 8341 business solutionsBrowse free open source Python Financial Software and projects below. Use the toggles on the left to filter open source Python Financial Software by OS, license, language, programming language, and project status.
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Qbot
AI-powered Quantitative Investment Research Platform
Qbot is an open source quantitative research and trading platform that provides a full pipeline from data ingestion and strategy development to backtesting, simulation, and (optionally) live trading. It bundles a lightweight GUI client (built with wxPython) and a modular backend so researchers can iterate on strategies, run batch backtests, and validate ideas in a near-real simulated environment that models latency and slippage. The project places special emphasis on AI-driven strategies — including supervised learning, reinforcement learning and multi-factor models — and offers a “model zoo” and example strategies to help users get started. For evaluation and analysis, Qbot integrates reporting and visualization (tearsheets, metrics) so you can compare performance across runs and inspect trade-level behavior. It supports multiple strategy runtimes and backtesting engines, is organized for extensibility (strategies live in a dedicated folder). -
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FinGPT
Open-Source Financial Large Language Models
FinGPT is an open-source, finance-specialized large language model framework that blends the capabilities of general LLMs with real-time financial data feeds, domain-specific knowledge bases, and task-oriented agents to support market analysis, research automation, and decision support. It extends traditional GPT-style models by connecting them to live or historical financial datasets, news APIs, and economic indicators so that outputs are grounded in relevant and recent market conditions rather than generic knowledge alone. The platform typically includes tools for fine-tuning, context engineering, and prompt templating, enabling users to build specialized assistants for tasks like sentiment analysis, earnings summary generation, risk profiling, trading signal interpretation, and document extraction from financial reports. -
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OpenBB Terminal
Investment research for everyone, anywhere
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. -
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Prophet
Tool for producing high quality forecasts for time series data
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Prophet is used in many applications across Facebook for producing reliable forecasts for planning and goal setting. We’ve found it to perform better than any other approach in the majority of cases. We fit models in Stan so that you get forecasts in just a few seconds. Get a reasonable forecast on messy data with no manual effort. Prophet is robust to outliers, missing data, and dramatic changes in your time series. -
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Intelligent stock analysis system
LLM-driven A/H/US stock intelligent analyzer
Intelligent stock analysis system is a Python-based smart stock analysis system that leverages large language models to automatically analyze selected equities across A-shares, Hong Kong stocks, and U.S. markets. It’s designed to produce a daily “decision dashboard” summarizing key insights such as core conclusions, precise entry/exit points, and checklists for potential trades, combining multi-dimensional technical analysis, market sentiment, chip distribution, and real-time price data. The system supports scheduled execution using GitHub Actions, enabling fully automated daily analysis and multi-channel notifications via platforms like Telegram, Enterprise WeChat, Feishu, email, and push services. Under the hood, it integrates multiple AI models (like Gemini and OpenAI-compatible models) and diverse market data sources (including AkShare, Tushare, and YFinance) to synthesize comprehensive reports. -
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Finance Database
This is a database of 300.000+ symbols containing Equities, ETFs, etc.
As a private investor, the sheer amount of information that can be found on the internet is rather daunting. Trying to understand what type of companies or ETFs are available is incredibly challenging with there being millions of companies and derivatives available on the market. Sure, the most traded companies and ETFs can quickly be found simply because they are known to the public (for example, Microsoft, Tesla, S&P500 ETF or an All-World ETF). However, what else is out there is often unknown. This database tries to solve that. It features 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets. It, therefore, allows you to obtain a broad overview of sectors, industries, types of investments and much more. The aim of this database is explicitly not to provide up-to-date fundamentals or stock data as those can be obtained with ease (with the help of this database) by using yfinance, FundamentalAnalysis or ThePassiveInvestor. -
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Odoo
Open-source business management software
Odoo 18 is a comprehensive open-source business management software that offers a suite of integrated applications to streamline various organizational processes. Designed for flexibility and scalability, it provides tools for managing functions like sales, inventory, accounting, human resources, and customer relationships. Odoo's modular structure allows businesses to adopt only the features they need while maintaining the option to expand functionality as they grow. The open-source version is community-driven, making it cost-effective and continuously improving through global developer contributions. Its user-friendly interface and robust customization options make it a popular choice for small to medium-sized businesses seeking an adaptable and efficient ERP solution. -
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AutoTrader
A Python-based development platform for automated trading systems
AutoTrader is a Python-based platform—now archived—designed to facilitate the full lifecycle of automated trading systems. It provides tools for backtesting, strategy optimization, visualization, and live trading integration. A feature-rich trading simulator, supporting backtesting and paper trading. The 'virtual broker' allows you to test your strategies in a risk-free, simulated environment before going live. Capable of simulating multiple order types, stop-losse,s and take-profits, cross-exchange arbitrage and portfolio strategies, AutoTrader has more than enough to build a profitable trading system. -
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QuantDinger
AI-driven, local-first quantitative trading platform for research
QuantDinger is a local-first, open-source quantitative trading platform designed to bring AI-assisted analysis, strategy development, backtesting, and live execution into a self-hosted workspace where data and API credentials remain under your control. Unlike cloud-locked quant services, it lets users run the entire trading workflow on their own infrastructure using Docker, with a PostgreSQL database backend, a Python backend API, and a web frontend UI that supports visualization and strategy management. Traders and researchers can develop custom strategies in Python, run historical backtests, analyze performance, and connect to supported exchanges for live trading, making it suitable for equities, crypto, forex, and futures markets in a local environment. QuantDinger also incorporates optional AI features via external APIs, assisting in tasks like strategy ideation or interpreting market indicators, but strategy logic remains inspectable and transparent in code. -
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Yahoo! Finance market data downloader
Yahoo! Finance market data downloader
Ever since Yahoo! finance decommissioned their historical data API, many programs that relied on it to stop working. yfinance aims to solve this problem by offering a reliable, threaded, and Pythonic way to download historical market data from Yahoo! finance. yfinance aimed to offer a temporary fix to the problem by scraping the data from Yahoo! Finance and returning a the data in the same format as pandas_datareader's get_data_yahoo(), thus keeping the code changes in existing software to a minimum. The latest version of yfinance is a complete re-write of the libray, offering a reliable method of downloading historical market data from Yahoo! Finance, up to 1 minute granularity, with a more Pythonic way. The Ticker() module allows you get market and metadata for security, using a Pythonic way. -
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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
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A quantitative finance C++ library for modeling, pricing, trading, and risk management in real-life. A cross-platform free/open-source tool for derivatives and financial engineering.
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Awesome-Quant
A curated list of insanely awesome libraries, packages and resources
awesome-quant is a curated list (“awesome list”) of libraries, packages, articles, and resources for quantitative finance (“quants”). It includes tools, frameworks, research papers, blogs, datasets, etc. It aims to help people working in algorithmic trading, quant investing, financial engineering, etc., find useful open source or educational resources. Licensed under typical “awesome” list standards. -
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Optopsy
A nimble options backtesting library for Python
Optopsy is a Python-based, nimble backtesting and statistics library focused on evaluating options trading strategies like calls, puts, straddles, spreads, and more, using pandas-driven analysis. The csv_data() function is a convenience function. Under the hood it uses Panda's read_csv() function to do the import. There are other parameters that can help with loading the csv data, consult the code/future documentation to see how to use them. Optopsy is a small simple library that offloads the heavy work of backtesting option strategies, the API is designed to be simple and easy to implement into your regular Panda's data analysis workflow. As such, we just need to call the long_calls() function to have Optopsy generate all combinations of a simple long call strategy for the specified time period and return a DataFrame. Here we also use Panda's round() function afterwards to return statistics within two decimal places. -
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PyTorch Forecasting
Time series forecasting with PyTorch
PyTorch Forecasting aims to ease state-of-the-art time series forecasting with neural networks for both real-world cases and research alike. The goal is to provide a high-level API with maximum flexibility for professionals and reasonable defaults for beginners. A time series dataset class that abstracts handling variable transformations, missing values, randomized subsampling, multiple history lengths, etc. A base model class that provides basic training of time series models along with logging in tensorboard and generic visualizations such actual vs predictions and dependency plots. Multiple neural network architectures for timeseries forecasting that have been enhanced for real-world deployment and come with in-built interpretation capabilities. The package is built on PyTorch Lightning to allow training on CPUs, single and multiple GPUs out-of-the-box. -
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Qlib
Qlib is an AI-oriented quantitative investment platform
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. -
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Tally
Let agents classify your bank transactions
Tally is an open-source, AI-assisted tool designed to automate the classification of personal financial transactions, helping users turn raw bank data into meaningful categories without manual tagging. At its core, Tally pairs a local rule engine with large language models so that an AI assistant (like Claude Code, Copilot, or any CLI agent) interprets, suggests, and categorizes expenses, savings, subscriptions, and income events based on your own rules and behavior. It generates human-readable reports and can produce HTML, JSON, or Markdown outputs to suit dashboards or personal finance workflows. The project emphasizes transparency, allowing users to see why a particular transaction was classified a certain way and to refine rules over time. While it’s tailored toward developers and advanced users, it also includes an interactive command-line experience for initializing budgets, generating charts, and diving deep into spending patterns. -
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alpha_vantage
A python wrapper for Alpha Vantage API for financial data.
Alpha Vantage delivers a free API for real time financial data and most used finance indicators in a simple json or pandas format. This module implements a python interface to the free API provided by Alpha Vantage. You can have a look at all the API calls available in their API documentation. For code-less access to the APIs, you may also consider the official Google Sheet Add-on or the Microsoft Excel Add-on by Alpha Vantage. To get data from the API, simply import the library and call the object with your API key. Next, get ready for some awesome, free, realtime finance data. Your API key may also be stored in the environment variable ALPHAVANTAGE_API_KEY. The library supports giving its results as json dictionaries (default), pandas dataframe (if installed) or csv, simply pass the parameter output_format='pandas' to change the format of the output for all the API calls in the given class. -
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OpenMoneyBox
Budget management
OpenMoneyBox is an application designed to manage small personal budgets in the easiest way. Check the homepage to download apps/packages for additional Operating Systems. -
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rotki
A portfolio tracking, analytics, accounting and tax reporting app
A portfolio tracking, analytics, accounting and tax reporting application that respects your privacy -
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Financial Calculator
Windows 11 only — includes 16 sections with text and visual reports.
Take control of your finances with Financial Calculator 7.9, a professional yet easy-to-use desktop tool built for precise, everyday financial calculations. From planning loans and estimating taxes to generating invoices and creating QR codes, this all-in-one software offers 16 specialized sections that make your daily financial and business tasks faster, clearer, and more accurate. Whether you’re a student, small business owner, or finance professional, Financial Calculator brings professional-grade precision to your desktop—no installation required. Perform calculations for Bank, Barcode, Building, Buy & Sell, Commodity, Dividing Money, Inflation, Interest, Internet Usage, Invoice, Loan, Password, Phone, QR Code, Stock Market, and Tax. Unlock the full version with a small cryptocurrency payment (as low as $0.01). -
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Financial Calculator
Windows 11 only — includes 16 sections with text and visual reports.
Take control of your finances with Financial Calculator 7.9, a professional yet easy-to-use desktop tool built for precise, everyday financial calculations. From planning loans and estimating taxes to generating invoices and creating QR codes, this all-in-one software offers 16 specialized sections that make your daily financial and business tasks faster, clearer, and more accurate. Whether you’re a student, small business owner, or finance professional, Financial Calculator brings professional-grade precision to your desktop—no installation required. Perform calculations for Bank, Barcode, Building, Buy & Sell, Commodity, Dividing Money, Inflation, Interest, Internet Usage, Invoice, Loan, Password, Phone, QR Code, Stock Market, and Tax. Unlock the full version with a small cryptocurrency payment (as low as $0.01). -
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An Excel addin and server framework for implementing remote excel user-defined functions (UDFs). This framework is designed to provide a centralised warehouse of functions for Excel users (eg. within an organisation).
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"Circular Multilateral Barter" (CMB) is aimed at supplying entrepreneurs with a way to exchange goods and services within a p2p-network, without using money, overcoming the "double coincidence of wants" problem, inherent to traditional barter. Most importantly, CMB allows traders to issue their own currencies (called "products"), which others can redeem, trade, or make payments with. One thing that distinguishes CMB from other "credit commons" is that all debts in CMB are user-to-user debts. There is no central administrative authority to decide who deserves to be trusted and who does not. Because of this, CMB can scale-up very well, so that local communities can be seamlessly aggregated into larger ones. Another way of seeing CMB is as a partnership of independent Local Exchange Trading Systems, having a common marketplace for exchanging one LETS-currency for another (via circular trade).
