Open-source alternatives to Crypto Trading Bot

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

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

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

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

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

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

TradeMaster is a reinforcement learning trading framework and algorithmic trading simulator designed for designing and testing quantitative trading strategies. The system provides a platform for developing reinforcement learning agents, managing quantitative portfolios, and optimizing trade execution using financial market data. The project features specialized components for multi-modality data preprocessing, a high-fidelity market environment simulation for strategy backtesting, and a quantitative portfolio manager for capital reallocation across multiple assets. It includes a trade executi

Zenbot is an automated cryptocurrency trading bot designed to execute trades on exchanges based on technical analysis and predefined risk parameters. It functions as a technical analysis engine that processes market data through mathematical indicators to generate actionable trade signals. The system includes a genetic algorithm strategy optimizer to automatically discover the most profitable parameter configurations. It provides multiple simulation environments, including a trading strategy backtester for replaying historical data and a paper trading simulator for testing strategies against

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

tqsdk-python is a quantitative trading SDK and framework designed for developing automated strategies for futures, options, and stocks using Python. It functions as an algorithmic trading engine and financial market data API, providing the tools necessary to backtest strategies, analyze historical data, and execute live trades across multiple brokerage accounts. The project distinguishes itself through a specialized option analytics library that calculates Greeks, implied volatility, and volatility surfaces using the Black-Scholes model. It further supports complex order execution patterns, s

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

This is a library of cryptocurrency trading algorithms and technical analysis strategies designed for use with the Freqtrade trading bot. The project provides a collection of pre-defined rules and mathematical indicators used to automate the buying and selling of digital assets. The repository focuses on algorithmic trading strategies and bot-driven asset management to remove manual execution from cryptocurrency trades. It enables quantitative trading analysis by allowing the development and testing of rule-based logic against historical market data. The system utilizes class-based strategy

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

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

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

Backtrader is a Python framework designed for the development, backtesting, and live execution of algorithmic trading strategies. It provides a comprehensive environment for quantitative finance, allowing users to simulate trading logic against historical market data or connect directly to brokerage platforms for automated real-time trading. The project distinguishes itself through a unified event-driven architecture that treats backtesting and live trading with the same API. This consistency is supported by a flexible data-feed abstraction layer that normalizes diverse financial sources, ena

This project is a Python wrapper for the Lightweight Charts library, designed to render interactive, browser-based financial visualizations. It serves as a framework for building custom financial dashboards and interfaces that integrate live market feeds and historical data series. The library enables the construction of complex layouts by combining multi-pane charts, watchlists, and order entry tables into a single unified workspace. It supports real-time market monitoring by streaming live tick or bar data directly into active visualizations, allowing for incremental updates without requiri

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

LoopBack Next is a Node.js API framework used for building REST and multi-protocol APIs. It functions as an OpenAPI server implementation that can either generate machine-readable specifications from code or produce implementation controllers and models from existing specifications. The framework distinguishes itself through a central dependency injection container and a repository-pattern data access layer. This architecture decouples application logic from component construction and persistent storage, allowing for a pluggable system where data sources and business logic are isolated throug

This project is a high-performance C++ trading engine designed for automated cryptocurrency market making and high-frequency trading. It functions as a liquidity provision tool that executes rapid order adjustments and quote placements to capture the bid-ask spread. The system utilizes a fair-value pricing model to estimate target asset prices based on real-time exchange data. It features a self-hosted trading dashboard that provides a web interface for monitoring portfolio holdings, visualizing market metrics, and manually controlling automated trading instances. The software includes capab

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

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

This library provides a unified interface for interacting with hundreds of global cryptocurrency exchanges. It serves as a standardized framework for building automated trading systems, allowing developers to fetch real-time market data, manage account balances, and execute orders across multiple financial platforms through a single, predictable set of methods. The project distinguishes itself by abstracting the complexities of diverse exchange-specific application programming interfaces into a consistent internal schema. It includes a modular authentication layer that automatically handles c

Nest is a server-side framework for building scalable and maintainable enterprise-grade applications using TypeScript. It provides a modular architecture that organizes code into encapsulated, reusable modules, utilizing a dependency injection container to manage object lifecycles and resolve component dependencies through declarative metadata. The framework distinguishes itself through a platform-agnostic abstraction layer that decouples core logic from underlying HTTP servers, allowing for flexible implementation choices. It employs a middleware-based request pipeline that processes traffic

Parse Server is a backend-as-a-service solution and Node.js framework that provides a ready-to-use REST and GraphQL API for mobile and web applications. It functions as a core backend infrastructure for managing database schemas, user authentication, and API routing. The system distinguishes itself with a real-time data engine that pushes database updates to clients via WebSockets and a GraphQL server that automatically generates schemas based on application data models. It also features an adapter-based storage layer that abstracts interactions with various cloud and local backends. The pla

Hapi is a configuration-driven web framework for building secure and scalable HTTP servers and APIs on the Node.js runtime. It functions as a REST API development framework and an enterprise server implementation focused on stability, security, and comprehensive input validation. The framework is built around a plugin-based architecture, allowing core functionality and custom logic to be organized into modular, registerable plugins. It serves as an HTTP request lifecycle manager, enabling the interception and modification of requests through pre-handlers and extensions before they reach the f