Search Results for "research"
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Showing 19 open source projects for "research"
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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. -
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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. ... -
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Claude for Financial Services
Reference agents, skills, and data for the financial-services
...Its architecture emphasizes modularity, enabling firms to customize workflows and extend functionality for proprietary use cases. Overall, the project serves as a foundation for building AI-enhanced financial research and decision-support systems. -
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ValueCell
Community-driven, multi-agent platform for financial applications
ValueCell is a community-driven multi-agent AI platform focused on financial research, analysis, and decision-making that lets users leverage multiple specialized AI agents for tasks like data retrieval, investment research, strategy execution, and market tracking. The system brings together a suite of collaborative agents—such as research agents that gather and interpret fundamentals, strategy agents that implement trading logic, and news agents that deliver personalized updates—to help users make more informed financial decisions across stocks, crypto, and other markets. ... -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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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... -
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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. ... -
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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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AI Hedge Fund
An AI Hedge Fund Team
...Its structure is educational: intended more as a proof-of-concept than a ready-to-use financial product, giving learners insight into the mechanics of quantitative finance automation. The project underlines AI’s potential in investment strategies but also carries disclaimers that it is for research and not financial advice. The implementation is designed so developers can study the pipeline end-to-end: from data ingestion through modeling to simulated portfolio management. -
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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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NautilusTrader
A high-performance algorithmic trading platform
...The platform is 'AI-first', designed to develop and deploy algorithmic trading strategies within a highly performant and robust Python native environment. This helps to address the parity challenge of keeping the Python research/backtest environment, consistent with the production live trading environment. NautilusTraders design, architecture and implementation philosophy holds software correctness and safety at the highest level, with the aim of supporting Python native, mission-critical, trading system backtesting and live deployment workloads. -
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AutoHedge
Build your autonomous hedge fund in minutes
...It also emphasizes modularity, enabling developers to customize strategies, risk parameters, and decision logic. AutoHedge is particularly useful for experimentation and research in algorithmic trading and financial automation. Overall, it represents an attempt to bring agent-based intelligence into portfolio management and risk mitigation workflows. -
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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. ... -
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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...
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Tushare
TuShare is a utility for crawling historical data of China stocks
...It allows users to retrieve real-time and historical market data, financial reports, index data, and macroeconomic indicators. Tushare is widely used in quantitative trading, data analysis, and academic research. It supports both free and premium data tiers via Tushare Pro, which requires an API token. -
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This project provides a Fortran90 library and a python module for singular spectrum analyses such as PCA/EOF or MSSA. It is intended for people interested, for example, in analysing climate or financial variability.
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The csvdatamix project aims to randomize CSV input data files in order to conceal the original state of the data. Similar to data masking or data transformation. Also has mapping abilities to translate back to the original state of the data.
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Narya is a forum/incubator software, based on a Python/Zope/MySQL platform. Emphasis on graphics support and collaboration for space and technology development. Compare PHP/MySQL forums.
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The main purpose of "python2xlw" is to create an Excel-compatible file which can be sent to users via the web as an excel application. The motivation is mainly to support the display of XY Scatter plots and tabular numerical data(eg engineering data)
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NovaGrid is a light spreadsheet made with Python / Tkinter, based on Tktable. The objective of this project is to have a light spreasheet python object which can be used into larger projects. The code is totaly written in Python (actualy 2.2.2).
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