"Vibe-Trading: Your Personal Trading Agent"
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Python Backtesting library for trading strategies
Open source software that helps you create and deploy high-frequency crypto trading bots
modular quant framework.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Python trading framework with AI agents that actually place the trade. Backtest, paper and live trade on 12 brokers: stocks, options, futures, forex, crypto and prediction markets.
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
Oracle3: open-source trading engine and MCP server for prediction markets. Finds fee-adjusted no-arbitrage violations across related event contracts and trades them live on Kalshi, Polymarket and Solana, or on paper, under pre-trade risk limits. 13 MCP tools, JSON CLI, agent skills, 600+ tests.
AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
Streaming-first technical indicators with a Rust core: native Python, Node.js and WebAssembly bindings plus a C ABI hub for C, C++, C#, Go, Java and R. 514 indicators, O(1) per-tick updates, no system dependencies. Drop-in TA-Lib replacement.
Simple, modern ETH backtesting project using Pandas/Numpy: data prep, MA signals, portfolio simulation, and result visualization.