Search Results for "trading"
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Showing 598 open source projects for "trading"
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Binance Trading Bot
Automated Binance trading bot, trade multiple cryptocurrencies
Automated Binance trading bot. Trade multiple cryptocurrencies. Buy low/sell high with Grid Trading. Integrated with TradingView technical analysis. This bot is using the concept of trailing buy/sell order which allows following the price fall/rise. Trailing Stop Orders About Trailing Stop Orders Concept you can find at Binance Official document. Place orders at a fixed value or percentage when the price changes. -
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Krypto-trading-bot
Self-hosted crypto trading bot, automated high frequency market
K is a family of (very customizable) very low latency market-making trading bots with a fully featured web interface. It can place and cancel orders on one of the several compatible exchanges in less than a few milliseconds per order on a decent machine. If you don't want to configure or hardcode your own trading strategies in your own machine, you can run strategies from someone else at kryll.io (or at any other trading community out there). -
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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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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. -
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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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QuantumBot
Designed to automate trading on the Solana blockchain
QuantumBot is a trading automation tool designed for the Solana blockchain, utilizing platforms like Raydium, MOONSHOT, and PUMP.FUN. Developed by traders for traders, it aims to enhance trading strategies by automating various trading activities, thereby optimizing performance and efficiency. -
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BTC Trading Since 2020
Public BTC trading context since 2020
BTC-Trading-Since-2020 is a cryptocurrency trading analysis project that focuses on evaluating Bitcoin trading strategies using historical data and algorithmic approaches. The repository serves as both a research and experimentation environment, allowing users to explore how different strategies perform under varying market conditions. It includes backtesting capabilities that enable users to simulate trades over historical Bitcoin price data, helping to identify profitable patterns and risk factors. ... -
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NOFX
Open source AI trading OS for autonomous multi-model trading systems
NOFX is an open source AI-powered trading operating system designed to automate financial trading workflows using autonomous AI agents. It acts as an infrastructure layer that transforms market data into AI-driven trade decisions and execution. Instead of requiring users to manually configure machine learning models, data sources, and API integrations, the system allows AI components to perceive market conditions, select models, and perform trading actions automatically. ... -
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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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Ninjabot
A fast cryptocurrency platform for trading bot in Go
A fast cryptocurrency trading bot framework implemented in Go. Ninjabot permits users to create and test custom strategies for spot markets. Ninjabot is an open-source platform that provides tools to implement custom strategies and backtests for trading cryptocurrencies in Go. Ninjabot CLI provides utilities commands to support backtesting and bot development. -
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Superalgos
Free, open-source crypto trading bot, automated bitcoin trading
Free, open-source crypto trading bot, automated bitcoin/cryptocurrency trading software, algorithmic trading bots. Visually design your crypto trading bot, leveraging an integrated charting system, data-mining, backtesting, paper trading, and multi-server crypto bot deployments. Superalgos is not just another open-source project. We are an open and welcoming community nurtured and incentivized with the project's native Superalgos (SA) Token, building an open trading intelligence network. ... -
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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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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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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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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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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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Roboquant
User-friendly and completely free algorithmic trading platform
Roboquant is an open-source algorithmic trading platform written in Kotlin. It is flexible, user-friendly and completely free to use. It is designed for anyone serious about algo-trading. So whether you are a beginning retail trader or an established trading firm, Roboquant can help you to quickly develop robust and fully automated trading strategies. But perhaps most important of all, it is blazingly fast. -
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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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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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Barter
Open-source Rust framework for building event-driven systems
Barter is an open-source, Rust-based ecosystem of libraries for building high-performance, event-driven algorithmic trading systems—covering live trading, paper trading, and backtesting. It is designed for safety, speed, and flexibility in quantitative finance workflows. Use mock MarketStream or Execution components to enable back-testing on a near-identical trading system as live-trading. Centralised cache-friendly state management system with O(1) constant lookups using indexed data structures. ... -
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TradingGoose Studio
Technical analysis + LLM powered trading workflows
...Users can connect their own data providers and define personalized strategies using programmable indicators, making the system highly flexible for different trading styles. A key aspect of the platform is its visual workspace, where charts, widgets, and workflow blocks can be arranged and customized to create an interactive trading environment. -
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GoCryptoTrader
Trading bot and framework supporting multiple exchanges
GoCryptoTrader is a full framework / bot for cryptocurrency trading, written in Go (Golang). It supports multiple exchanges, real-time and historic data, backtesting, handling order books, portfolio management, scripting, and many exchange integration features. It is a trading engine that can be run by users to automate strategies across many exchanges. Licensed under MIT. Support for all exchange fiat and digital currencies, with the ability to individually toggle them on/off. ... -
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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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ta4j
A Java library for technical analysis
...Then we have to build our trading strategy. It is made of two trading rules, one for entry, the other for exit. Ta4j comes with a set of basic trading rules/strategies which can be combined using boolean operators. Trading strategies can be easily compared according to a set of analysis criteria. Ta4j can also be used for live trading with more complicated strategies. -
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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.
