Search Results for "python ai ide"

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. Stock trading strategies: large models,...

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. The project places special emphasis on AI-driven strategies —...

...Inspired by CCXT for cryptocurrency exchanges, PMXT standardizes market data, trading operations, and event structures for platforms like Polymarket, Kalshi, Limitless, Smarkets, and more. The framework simplifies working with prediction markets by normalizing differences in APIs, formats, and conventions across providers. PMXT supports both Python and TypeScript SDKs, making it easy for developers to build trading bots, analytics tools, and AI-powered market applications. It also includes MCP support for AI agents, enabling integration with tools like Claude, Cursor, and other MCP-compatible environments. With support for unified order placement, market discovery, and migration tools for Dome API users, PMXT streamlines development in the growing prediction markets ecosystem.

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. This helps to address the parity challenge of keeping the Python research/backtest environment, consistent with the production live trading environment. NautilusTraders design, architecture and implementation philosophy holds software correctness and safety at the highest level, with the aim of supporting Python native, mission-critical, trading system backtesting and live deployment workloads.