How to Build & Backtest Option Bull Call Spread Trading Algorithm with Python скачать в хорошем качестве

How to Build & Backtest Option Bull Call Spread Trading Algorithm with Python

@MattMacarty #lumibot #optionstrading #algotrading #python #bullcallspread *Automate complex multi-leg options strategies using Python and LumiBot.* In Part 4 of our LumiBot series, we transition from equity trading to automated options strategies. This tutorial focuses on building a Bull Call Spread algorithm for the Gold ETF (GLD). We move beyond simple orders to handle professional-grade requirements: calculating the 3rd Friday expiration, managing multi-leg assets, and benchmarking performance against the S&P 500. ⏱️ Key Technical Milestones 0:00 - Series Introduction & LumiWealth Overview 1:06 - Strategy Concept: The Bull Call Spread Framework 2:50 - Parameter Architecture: Defining Strikes and Spreads 4:34 - *Trading Iteration:* Normalizing dates for options cycles 7:42 - *Asset Definition:* Configuring Long vs. Short calls in LumiBot 9:00 - Multi-Leg Execution: Processing list-based orders 11:00 - Strike Selection: Rounding logic for standardized options 13:05 - *Expiration Engineering:* Calculating the 3rd Friday with the `calendar` module 16:45 - Backtesting: Initial $5 Spread results on GLD 18:50 - Optimization: Increasing spread size for higher volatility capture 19:30 - Final Analysis: Outperforming the SPY benchmark --- 🏛️ Implementation Highlights This strategy demonstrates advanced derivative management in Python: *1. Dynamic Expiration Logic:* Unlike stocks, options require a temporal component. We implement custom logic using Python’s `calendar` module to automatically identify the next 3rd-Friday expiration, ensuring the bot always trades the correct monthly cycle. *2. Multi-Leg Order Management:* Learn how to define separate `Asset` objects for the long and short legs of a vertical spread and execute them as a synchronized strategic unit within the LumiBot lifecycle. *3. Quantitative Analysis:* We utilize *QuantStats* to generate a performance tear sheet, comparing the risk-adjusted returns of our automated spread against a traditional buy-and-hold benchmark. --- 🔗 Professional Resources ✅ *Get the Code (GitHub):* https://github.com/mjmacarty/algorith... ✅ *LumiWealth Programs:* https://lumiwealth.com (Use code **MACARTY20* for 20% off programs. No commission is received.)* ✅ *LumiBot Documentation:* https://lumibot.lumiwealth.com ✅ *Research & Tutorials:* https://alphabench.com ✅ *Series Part 1 (Basics):*    • Build a LIVE Algorithmic Trading Bot with ...   ✅ *Subscribe for more Quant Tutorials:* https://www.youtube.com/subscription_... **Disclaimer: This video is for educational purposes only and does not constitute investment advice. Options trading involves significant risk of loss.** #python #finance #tradingbots #backtesting #quantitativeanalysis #gld