Python Trading Algorithm Development

I’m building a fully automated trading system in Python that can execute both day-trading and swing-trading strategies on live equity and forex markets. The core objectives are:

• Real-time data ingestion from a broker/API, with latency low enough for intraday decision making
• Strategy engine that supports separate rule sets for day trades and multi-day swing positions
• Robust risk-management layer (position sizing, stop-loss, take-profit, max draw-down guardrails)
• Integrated backtesting module so I can validate ideas on historical data before going live
• Clean, well-commented codebase that I can extend, plus simple configuration files for tweaking parameters without rewriting code

I’m comfortable providing API keys and sample datasets; you just need to wire them into the solution. Preferred stack is Python 3.x with libraries such as pandas, NumPy, TA-Lib/ta, backtrader (or another reliable framework) and WebSocket handling for streaming quotes.

Deliverables are the complete source code, setup instructions, and a short video or written walkthrough showing the algorithm running in both backtest and paper-trade modes. If anything is unclear, let’s clarify early so the first milestone already compiles and connects to live data.