QuantTrader Pro V2.1 Professional Quantitative Trading System

Problem

Local quantitative workflows often split indicators, backtesting, and simulated trading across separate scripts. Real data sources add setup friction, while dependency and permission errors make debugging noisy. This skill bundles those capabilities into a locally launched system: it starts with mock data to validate the flow, then connects real market feeds.

How It Works

• Market data and indicators: multi-period K-line charts with MA, MACD, RSI, and KDJ; also includes market breadth, northbound flows, and Dragon-Tiger list data for context.
• Strategy and backtesting: built-in moving-average, MACD, and RSI strategies with custom parameters; backtests produce reports, and a REST API supports secondary development.
• Trading and risk: simulated buying, selling, and position management, with position sizing, stop-loss/take-profit rules, P&L tracking, and equity curves.
• Data source switching: supports RQData, jqdatasdk, and Tushare, or runs with mock data without dependencies; data calls are isolated in child processes and reconnect automatically.
  Start with mock data to verify strategy logic, then configure real sources. Because market feeds vary by permissions, field definitions, and latency, backtest results should be treated as research references rather than live trading performance.