Search Results for "trading"
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Showing 98 open source projects for "trading"
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Vibe-Trading
Vibe-Trading: Your Personal Trading Agent
Vibe-Trading is an AI-powered multi-agent financial workspace that converts natural language inputs into executable trading strategies and market analysis. It allows users to describe investment ideas in plain language, which are then translated into code, backtested, and evaluated across global markets. The platform integrates multiple data sources, including equities, crypto, and derivatives, with automatic fallback mechanisms. -
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Quantitative Trading System
A comprehensive quantitative trading system with AI-powered analysis
Quantitative Trading System is a comprehensive quantitative trading platform that integrates artificial intelligence, financial data analysis, and automated strategy execution within a unified software system. The project is designed to provide an end-to-end infrastructure for building and operating algorithmic trading strategies in financial markets. -
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Hummingbot
Build trading bots that run on any exchange or blockchain
Hummingbot is an open-source project that integrates cryptocurrency trading on both centralized exchanges and decentralized protocols. It allows users to run a client that executes customized, automated trading strategies for cryptocurrencies. Hummingbot is software that helps you build and run automated trading strategies or bots. Its codebase is free and publicly available on Github under the Apache 2.0 open source license. -
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AIQuant
AI-powered platform for quantitative trading
ai_quant_trade is an AI-powered, one-stop open-source platform for quantitative trading—ranging from learning and simulation to actual trading. It consolidates stock trading knowledge, strategy examples, factor discovery, traditional rules-based strategies, various machine learning and deep learning methods, reinforcement learning, graph neural networks, high-frequency trading, C++ deployment, and Jupyter Notebook examples for practical hands-on use. ... -
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OctoBot
Cryptocurrency trading bot for TA, arbitrage and social trading
...You can use an existing setup or try and customize your own until you identify the perfect settings for your trading goals and proceed with real money trading and make real gains. -
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Smart Money Concepts
Discover our Python package designed for algorithmic trading
...These indicators are inspired by ICT trading principles and are used to identify trends, reversals, and potential entry or exit points in financial markets. The system is modular, allowing users to combine different indicators and integrate them into backtesting frameworks or live trading bots. It is particularly useful for traders working in forex, crypto, or equities who rely on price action rather than traditional indicators. -
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AI-Trader
100% Fully-Automated Agent-Native Trading
AI-Trader is an open-source AI-powered quantitative trading framework designed to combine financial analysis, machine learning, and autonomous trading workflows into a unified research platform. The project integrates large language models, financial indicators, market analysis pipelines, and automated decision-making systems to support strategy generation and market prediction tasks. It is built to help researchers and developers experiment with AI-assisted trading strategies using historical and real-time financial data. ... -
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PyBroker
Algorithmic Trading in Python with Machine Learning
Are you looking to enhance your trading strategies with the power of Python and machine learning? Then you need to check out PyBroker! This Python framework is designed for developing algorithmic trading strategies, with a focus on strategies that use machine learning. With PyBroker, you can easily create and fine-tune trading rules, build powerful models, and gain valuable insights into your strategy’s performance. -
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python-binance
Binance Exchange API python implementation for automated trading
...Websocket handling with reconnection and multiplexed connections. Symbol Depth Cache. Historical Kline/Candle fetching function. Withdraw functionality. Deposit addresses. Margin Trading. Futures Trading. Vanilla Options. Support other domains (.us, .jp, etc). The breaking changes include the migration from wapi to sapi endpoints which are related to the wallet endpoints detailed in the Binance Docs. -
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Tauric TradingAgents
Multi-Agents LLM Financial Trading Framework
...The architecture is modular, allowing developers to extend or customize agent behaviors. It is particularly useful for quantitative research and algorithmic trading development. Overall, it provides a flexible platform for building intelligent trading systems powered by AI. -
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KIS Open API
Korea Investment & Securities Open API Github
The open-trading-api repository from Korea Investment & Securities provides sample code and developer resources for interacting with the KIS Developers Open Trading API, which enables programmatic access to financial market data and automated trading functionality. The project is designed primarily for Python developers and AI automation environments that want to build investment applications, algorithmic trading systems, or financial analytics tools using the brokerage’s infrastructure. ... -
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Zipline Reloaded
Zipline, a Pythonic Algorithmic Trading Library
Zipline Reloaded is a maintained Python library for event-driven backtesting of algorithmic trading strategies. It continues the original Zipline project after Quantopian ended operations. Developers write trading algorithms while the engine simulates orders, market events, portfolio changes, and strategy performance over historical data. Common statistics such as moving averages and linear regression are available within algorithm workflows. -
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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. ... -
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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. ... -
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Freqtrade
Free, open source crypto trading bot
Freqtrade is a free and open-source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or WebUI. It contains backtesting, plotting, and money management tools as well as strategy optimization by machine learning. Always start by running a trading bot in Dry-run and do not engage money before you understand how it works and what profit/loss you should expect. -
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Nothing Ever Happens
Focused async Python bot for Polymarket
...Its core concept is based on statistical observations that a majority of prediction market outcomes resolve negatively, and it attempts to exploit this base-rate bias through systematic participation rather than predictive modeling. The bot includes a safety-oriented design with explicit environment variable requirements to enable live trading, ensuring that users consciously opt into real financial risk, along with a paper trading mode for testing without capital exposure. -
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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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PowerTrader_AI
Fully automated crypto trading powered by a custom price prediction AI
PowerTrader_AI is a fully open-source, automated cryptocurrency trading bot that combines a custom price prediction AI with a structured and tiered dollar-cost averaging (DCA) strategy to make real trading decisions on behalf of users. It continuously analyzes market data to forecast high and low price levels across multiple timeframes, using those predictions to determine when to open, scale into, or close positions automatically, which aims to take emotion out of trading and enforce discipline. ... -
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Polymarket Data
Polymarket Data Retriever that fetches, processes, and structures data
Polymarket Data is a comprehensive data engineering pipeline designed to collect, process, and structure trading activity from the Polymarket prediction market ecosystem into analyzable datasets. The system operates as a multi-stage pipeline that integrates data from both off-chain APIs and on-chain event sources, enabling users to reconstruct full trading activity including markets, order events, and executed trades. It begins by fetching market metadata such as questions, outcomes, and trading volumes, then proceeds to scrape order-filled events from a GraphQL-based subgraph, and finally transforms these raw events into structured trade-level records with calculated prices and directions. ... -
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TradingAgents
Chinese Financial Trading Framework Based on Multi-Agent LLM
TradingAgents-CN is a Chinese-enhanced, multi-agent LLM framework aimed at building financial analysis and trading-oriented workflows, with an emphasis on collaboration between specialized agents rather than a single monolithic prompt. It organizes market-related tasks into roles and stages so different agents can contribute research, reasoning, aggregation, and decision support in a structured pipeline. The project is oriented toward practical usage, including a stack that can be run in a modern development environment and commonly paired with containerized backends, configuration files, and service components. ... -
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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. -
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Sov.ai
A curated list of practical financial machine learning tools and apps
Financial Machine Learning is a curated directory of practical tools, repositories, datasets, papers, and educational resources for quantitative finance. It organizes material across trading, forecasting, portfolio construction, risk, alternative data, and financial machine learning techniques. Dedicated sections cover supervised and unsupervised learning, deep learning, reinforcement learning, natural language processing, and time-series analysis. Entries include descriptions, popularity data, maintenance indicators, and editorial ratings to help readers compare resources. ... -
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LlamaIndex
Central interface to connect your LLM's with external data
...These indices help to abstract away common boilerplate and pain points for in-context learning. Dealing with prompt limitations (e.g. 4096 tokens for Davinci) when the context is too big. Offers you a comprehensive toolset, trading off cost and performance. -
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AI Hedge Fund
An AI Hedge Fund Team
This repository demonstrates how to build a simplified, automated hedge fund strategy powered by AI/ML. It integrates financial data collection, preprocessing, feature engineering, and predictive modeling to simulate decision-making in trading. The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. 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. ... -
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easyquant
Stock quantification framework to support market acquisition
Trading support includes several Chinese broker clients and Xueqiu simulated portfolios. Strategies inherit from a common template and receive events containing current market information and account access. The repository includes example strategies, custom engines, account configuration files, logging, timers, and testing material.
