Search Results for "data visualization, research"
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Showing 45 open source projects for "data visualization, research"
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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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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. ... -
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Dexter
An autonomous agent for deep financial research
Dexter is an autonomous agent tailored for deep financial research: you pose complex financial questions (for example, about a company’s revenue growth or financial ratios) and Dexter breaks them down into structured research tasks, fetches relevant real-time data (e.g. income statements, cash flows), performs analysis, and returns data-backed answers. It uses a multi-agent architecture with components such as a planning agent (to decompose queries), an action agent (to run tasks & fetch data), and self-validation mechanisms: after getting results, Dexter checks its own outputs and refines them until it is confident about its answer. ... -
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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. ... -
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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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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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Flowsurface
A native desktop charting platform for crypto markets
Flowsurface is a powerful open-source desktop charting platform tailored for crypto markets, built primarily in Rust with a focus on real-time data visualization and market microstructure analysis. Instead of traditional price charts alone, Flowsurface emphasizes order flow and liquidity visualization through advanced chart types like historical DOM heatmaps, footprint charts, and depth ladder displays. This enables traders and analysts to understand actual executed trades, liquidity distribution, and tempo changes that often precede significant market movements. ... -
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Fincept Terminal
FinceptTerminal is a modern finance application
Fincept Terminal is an open-source financial intelligence platform aimed at bringing powerful market analysis and investment research tools to a broad audience without the prohibitive cost of proprietary terminals. The project provides both command-line and graphical interfaces that let users access real-time market data, economic indicators, and advanced analytics directly from a unified terminal environment, supporting stocks, forex, commodities, and more. Its architecture integrates Python, TypeScript, Rust, and React, reflecting both a robust data processing backend and a modern desktop UI experience. ... -
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Claude for Financial Services
Reference agents, skills, and data for the financial-services
Claude for Financial Services is an open-source collection of AI agents, plugins, and workflow templates designed to transform Claude into a specialized assistant for financial services professionals. The project targets domains such as investment banking, equity research, private equity, and wealth management by providing reusable prompts, structured workflows, and domain-specific analytical skills. It supports deployment either as Claude Cowork plugins or through the Claude Managed Agents API, allowing organizations to integrate the same logic into internal systems and automation pipelines. The repository includes tools for competitive analysis, financial modeling, market research, data-pack generation, and strategic synthesis. ... -
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AI Hedge Fund
An AI Hedge Fund Team
...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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NautilusTrader
A high-performance algorithmic trading platform
NautilusTrader is an open-source, high-performance, production-grade algorithmic trading platform, provides quantitative traders with the ability to backtest portfolios of automated trading strategies on historical data with an event-driven engine, and also deploy those same strategies live, with no code changes. 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. ... -
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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... -
13
AutoHedge
Build your autonomous hedge fund in minutes
...It is built around the concept of algorithmic hedging, where strategies are executed programmatically rather than manually, enabling faster and more consistent responses to market changes. The system supports integration with financial data sources, allowing it to process real-time or historical data for analysis and strategy execution. 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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Kalshi Trading Bot CLI
AI-native CLI for trading Kalshi prediction markets
Kalshi Trading Bot CLI is an AI-driven command-line tool designed to automate trading strategies on Kalshi prediction markets by combining quantitative modeling with real-time market data. It operates by conducting deep research on events, generating independent probability estimates, and comparing those estimates against current market prices to identify trading opportunities. The system incorporates advanced decision-making logic, including Kelly criterion-based position sizing and a structured multi-step risk evaluation process before executing trades. ... -
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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. ... -
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Apache OpenOffice
The free and Open Source productivity suite
Free alternative for Office productivity tools: Apache OpenOffice - formerly known as OpenOffice.org - is an open-source office productivity software suite containing word processor, spreadsheet, presentation, graphics, formula editor, and database management applications. OpenOffice is available in many languages, works on all common computers, stores data in ODF - the international open standard format - and is able to read and write files in other formats, included the format used by the... -
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AptiStockX
AptiStockX is a local-first desktop stock charting software
AptiStockX is a local-first desktop stock charting and portfolio research application for Windows, macOS, and Linux. It is the modern continuation of AptiStock, first released in 2005. AptiStockX focuses on native desktop charting, local chart files, local workspaces, watchlists, downloaded market data, provider-separated data workflows, technical indicators, drawing tools, multi-monitor charting, and optional AI-assisted chart review. -
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ezBookkeeping
A lightweight personal finance app hosted by yourself.
ezBookkeeping is a lightweight, self-hosted personal finance app with a user-friendly interface and powerful bookkeeping features. It helps you record daily transactions, import data from various sources, and quickly search and filter your bills. You can analyze historical data using built-in charts or perform custom queries with your own chart dimensions to better understand spending patterns and financial trends. ezBookkeeping is easy to deploy, and you can start it with just one single... -
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ThinkValue
Analyze stocks clearly without spending hours modeling
ThinkValue helps you analyze US stocks with clear DCF valuation models and SEC-sourced financial data. Build single or multi-stage valuations, run reverse DCFs, and test scenarios with sensitivity analysis. Use structured SEC financials via a free API, generate automated spreadsheets, and access research and KPIs on the web platform. Start free with no login or upgrade for versioned API access and integration support. -
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...Its editing AKP data is very fast 6. Creating a new window is also very fast 7. Friends who need to perform APH analysis can download this AHP Khaskia software 8. User-friendly interface 9. Step-by-step wizard 10. Wide range of features 11. Free to use
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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,... -
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TradingGym
Trading backtesting environment for training reinforcement learning
TradingGym is a toolkit (in Python) for creating trading and backtesting environments, especially for reinforcement learning agents, but also for simpler rule-based algorithms. It follows a design inspired by OpenAI Gym, offering various environments, data formats (tick data and OHLC), and tools to simulate trading with costs, position limits, observation windows etc. Licensed under MIT. This training environment was originally designed for tickdata, but also supports OHLC data format. WIP.... -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. 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. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
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pair-trading-view
Pair Trading View - .NET application for visual analysis of synthetic
Pair Trading View - .NET application for visual analysis of synthetic financial instruments based on statistical models. https://github.com/dv-lebedev/pair-trading-view Look for binaries in "pair-trading-view\PairTradingView.WinFormsApp\bin\Debug" folder. -
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FiMaLib
a financial math library and financial market data database
This project should combine a financial mathematics library with an underlying financial market database (and a set of other tools), which could be used by financial institutions for their financial market data needs as well as by students for research works.