Projects sharing features with Gekko

StockSharp is an algorithmic trading platform and quantitative framework used for developing and deploying trading robots across stock, forex, and cryptocurrency markets. It functions as a multi-asset trading gateway and a dedicated development environment for building, debugging, and scheduling automated strategies. The platform includes a visual strategy workflow editor that maps logic blocks to executable code and a simulation engine that replays historical tick data to validate trading logic. It utilizes a plugin-based broker integration system to normalize diverse exchange protocols into

Hummingbot is an open-source framework designed for building, backtesting, and deploying autonomous trading agents and algorithmic strategies across centralized and decentralized cryptocurrency exchanges. It provides a modular environment where users can orchestrate containerized bots to execute complex market-making, grid trading, and arbitrage operations. The platform distinguishes itself through a skill-based architecture that integrates large language models, enabling users to monitor market conditions and control trading operations via natural language commands. It features a unified con

XChange is a cryptocurrency exchange integration library and API wrapper that provides a unified interface for connecting to multiple cryptocurrency exchanges. It serves as a multi-exchange trading interface and a market data streamer, normalizing raw data from various providers into standardized data objects. The project distinguishes itself through an adapter-based normalization system and a reactive WebSocket streaming model designed to receive real-time price and volume updates while minimizing thread usage. It includes a dedicated authentication handler for managing API keys, request non

OctoBot is an open-source automated trading platform that connects to over 15 cryptocurrency exchanges, enabling users to deploy grid, dollar-cost averaging, market-making, and AI-driven trading strategies. It functions as a unified multi-exchange trading platform, a TradingView alert executor, and a crypto trading bot, all within a single system. The platform is built on an event-driven trading loop with a plugin-based strategy engine, an exchange-agnostic connector layer, and a cloud-synced profile store for multi-device consistency. What distinguishes OctoBot is its integration of large la

This project is an algorithmic trading engine designed for the automated execution of cryptocurrency strategies. It provides a modular execution core that connects to multiple centralized and decentralized exchanges, allowing users to deploy rule-based trading logic across various spot and futures markets. The platform serves as a comprehensive environment for the entire trading lifecycle, from initial strategy development to live market operations. What distinguishes this platform is its integrated suite for quantitative analysis and predictive modeling. It features a robust backtesting engi

Easyquant is a quantitative trading framework and event-driven engine designed for executing automated trading strategies and managing real-time market data across multiple accounts. It includes an algorithmic strategy engine and a market data integration layer to process stock quotes and order book data from external providers. The system features a trading backtesting simulator that uses market time simulation to verify strategy behavior under specific timestamps. It supports dynamic strategy deployment via a hot-reloading module system, allowing trading logic to be updated and injected int

Superalgos is a cryptocurrency algorithmic trading platform used for designing, backtesting, and deploying automated trading bots. It centers on a visual strategy designer that allows users to create indicators and trading logic through a graphical interface instead of writing manual code. The platform features a token-gated signal network that enables a decentralized marketplace for broadcasting and monetizing trading intelligence. Access to these signals and predictions is managed via digital tokens and reputation scores, while a distributed trading infrastructure allows users to coordinate

NoFx is an autonomous trading platform designed to orchestrate financial workflows through artificial intelligence and multi-asset exchange connectivity. It functions as a comprehensive infrastructure for executing automated trading strategies, integrating language models for market analysis, and managing secure interactions across both centralized and decentralized financial platforms. The platform distinguishes itself through a multi-model strategy ensembling approach, which runs several artificial intelligence models in parallel to evaluate and select the most effective trading decisions b

VeighNa is an event-driven, modular platform designed for the development, backtesting, and execution of automated financial trading strategies. It provides a comprehensive suite of tools that includes a centralized trading terminal for monitoring portfolios and market conditions, alongside a robust algorithmic trading engine that manages real-time data processing and order execution. The platform distinguishes itself through a highly decoupled architecture that isolates algorithmic logic from market connectivity, allowing for independent strategy development and testing. It utilizes a dynami

FinRL is a reinforcement learning framework designed for the development, training, and backtesting of automated trading strategies. It functions as a quantitative finance toolkit that integrates deep learning algorithms with financial market simulations to address complex portfolio management and asset allocation tasks. The platform provides an end-to-end pipeline for transforming raw market data into actionable trading models. The project distinguishes itself through a layered, modular architecture that separates data processing, environment simulation, and agent training. This design allow

Nautilus Trader is a high-performance algorithmic trading framework built in Rust, designed for the development, backtesting, and live execution of automated trading strategies. It provides a comprehensive platform for managing multi-asset portfolios and interacting with diverse financial markets through a standardized connectivity suite. The system is engineered to handle high-frequency data processing and complex order execution while maintaining precise numerical accuracy across various asset classes. The framework distinguishes itself through an architecture centered on deterministic even

Jesse is a Python algorithmic trading framework used for developing, backtesting, and executing quantitative trading strategies. It functions as a trading strategy backtester and a machine learning trading platform, providing an environment to train predictive models on historical market data and deploy them into live strategies. The framework features a standardized crypto exchange connectivity layer that allows for the execution of automated spot and futures trades across multiple cryptocurrency exchanges via an exchange-agnostic interface. It includes a quantitative risk analysis toolset t

This software is an automated trading tool designed for the Binance cryptocurrency exchange. It functions as a program for executing high-frequency market orders and managing trade exits based on real-time exchange data and price volatility. The bot distinguishes itself through its ability to monitor exchange listings in real time, allowing it to detect and act upon newly released digital assets as they appear. It incorporates stateful trailing stop logic to dynamically adjust exit thresholds, providing automated risk management to protect capital during periods of high market volatility. Th

pyalgotrade is a Python algorithmic trading library designed for developing, backtesting, and executing automated trading strategies. It provides a comprehensive framework for financial strategy backtesting, a technical analysis library for computing mathematical indicators, and connectors for cryptocurrency exchange integration. The project distinguishes itself by supporting sentiment-based trading through the integration of real-time social media feeds and keyword streams. It features a quantitative trading visualization tool for plotting price action and portfolio equity curves, along with

This project is an automated cryptocurrency trading platform for the Binance exchange. It functions as a technical analysis trading tool and grid trader, executing strategies and managing assets without manual intervention. The platform is distinguished by its multi-service containerized architecture, which orchestrates a listener, cache, and database. It utilizes a secure web dashboard for monitoring active trades and adjusting bot parameters, protected by password and token-based authentication. The system covers a broad range of trading capabilities, including grid and trailing order auto

Binance Connector Python is a client library that provides programmatic access to the Binance cryptocurrency exchange, enabling automated trading and asset management across spot, margin, futures, and options markets. The library wraps the exchange's REST and WebSocket APIs into a Python interface with type-hinted methods, HMAC and RSA authentication, and a unified request-response pipeline for consistent error handling and rate limiting. The connector supports a broad range of exchange operations beyond core trading, including sub-account management, wallet operations, and algorithmic order

python-binance is a Python client library that provides programmatic access to the Binance cryptocurrency exchange through both REST and WebSocket APIs. It serves as a comprehensive toolkit for automated trading, account management, and market data retrieval, enabling developers to build trading bots, portfolio management tools, and data analysis applications that interact directly with the exchange. The library distinguishes itself through a dual-client architecture that separates synchronous REST calls from persistent WebSocket streams, allowing concurrent execution without blocking. It inc

Hikyuu is a quantitative trading framework designed for developing, backtesting, and executing systematic trading strategies. It functions as a high-speed system that combines a financial time-series library, a multi-factor analysis tool, and a quantitative backtesting engine to support comprehensive trading research. The framework is distinguished by its high-speed computing core, which utilizes multi-threaded execution to process large volumes of market data for technical indicator generation. It supports a modular strategy composition model where signal, risk, and fund management component

This project is a quantitative trading platform and algorithmic trading bot designed for market data aggregation, strategy backtesting, and trade execution. It functions as a comprehensive system for collecting financial data via APIs and web sources, simulating investment strategies against historical records, and programmatically managing investment positions through brokerage interfaces. The platform distinguishes itself through institutional sentiment analysis and market intelligence tools. It monitors institutional fund activity, tracks corporate actions like equity pledges, and crawls f

zvt is a quantitative trading framework designed for building, backtesting, and executing algorithmic trading strategies. It functions as a modular system that integrates a financial data pipeline for market data collection, an algorithmic backtesting engine for strategy evaluation, and an event-driven trading system to automate market executions. The project distinguishes itself through a hybrid approach to signal management, using a dynamic tagging system that combines automated quantitative logic with human intervention. It includes a quantitative analysis dashboard for visualizing researc

Backtrader is a Python backtesting framework and algorithmic trading platform. It provides a toolkit for developing automated trading rules and simulating investment strategies using historical financial time-series data. The system functions as a quantitative analysis tool, combining a simulation engine for testing trading rules with a financial data visualizer that generates price action charts. It allows for the calculation of technical indicators and the evaluation of portfolio performance through risk-adjusted returns. The platform covers live trading integration via brokerage APIs and

pybroker is a Python algorithmic trading framework and quantitative technical analysis library designed for developing, testing, and optimizing trading strategies using historical market data. It functions as a trading strategy backtester and a financial performance evaluator, providing a structured environment to simulate trading rules and analyze their statistical reliability. The framework distinguishes itself through a market data integration layer that handles the fetching and caching of historical price data from external providers. It incorporates an event-driven backtesting engine and

Valuecell is an artificial intelligence financial trading platform and market analysis engine. It functions as a multi-exchange trading bot and financial data orchestrator, designed to analyze market data and execute automated trades across global financial exchanges. The system utilizes a modular agent plugin framework that allows for the integration of third-party tools and agents through a shared community registry. It incorporates a retrieval-augmented generation approach to analyze fundamental financial documents and historical patterns, grounding AI responses in factual data. The platf

Lean is an algorithmic trading engine and quantitative finance platform designed for the development, backtesting, and live execution of automated trading strategies. It provides a comprehensive framework for processing time-series market data, managing multi-asset portfolios, and conducting quantitative research across diverse financial markets. The platform distinguishes itself through a modular, event-driven architecture that decouples strategy logic from data ingestion and brokerage connectivity. By utilizing standardized interfaces for data providers and brokerage abstractions, it enable

Stock is an algorithmic trading framework designed for the development, backtesting, and execution of automated investment strategies. It provides a comprehensive environment for quantitative market analysis, enabling users to build systems that connect to brokerage interfaces for order placement based on predefined technical rules. The platform distinguishes itself through integrated data acquisition and analysis capabilities, including a financial data collection engine that utilizes proxy rotation and session persistence to maintain stable connectivity and bypass rate limits. It supports h

This project is a Python quantitative trading framework and library designed for developing, backtesting, and deploying automated financial strategies. It serves as both an algorithmic trading backtester for evaluating historical performance and an event-driven trading engine for executing trades based on quantitative rules. The framework functions as an educational toolkit, providing guided lessons and resources for quantitative finance learning and the application of mathematical models to market data. The system provides capabilities for algorithmic trading automation and financial strate

QuantMuse is an algorithmic trading platform and quantitative trading framework that integrates large language models with mathematical analysis to automate market insights and trading strategies. It functions as a system for building, backtesting, and executing strategies using both historical and real-time market data. The framework is distinguished by its use of large language models for financial analysis and sentiment extraction from news and social media. It utilizes autonomous agents with chain-of-thought reasoning to generate market intelligence and strategic reports, while employing