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In this video, we explore a New York session breakout strategy using a multi-timeframe approach with strict entry and exit rules, fully implemented and tested in Python. This session breakout trading strategy was backtested over 9 years of data on both JPY pairs and Gold, showing solid performance and relatively controlled drawdowns especially on JPY, where the method was originally designed to work best. We’ll break down the logic step-by-step: Using the previous daily candle as a directional filter Waiting a few hours into the session to detect the highest/lowest price levels Entering with pending breakout orders Applying a fixed stop loss and closing trades at the end of the session Then we go through the full Python backtest implementation, including the multi-timeframe handling and session-based trade management. This is a simple but powerful example of a multi-timeframe breakout system, combining session timing, price action, and systematic execution. ╔═╦═╦═╦═╦═╦═╦═╦═╦═╦═╦═╦═╦═╦═╦═╦═╦═╦══╦═╦═╦══╦═╦═╦══╦═╦═╦ 🔗 Resources & Links: -------------------------------------- • 📚 My Algorithmic Trading Courses → https://codetradingcafe.com • 📘 My Book: “Algorithmic Trading with Python” → https://a.co/d/6woMBHt • 💻 Free Python Code (GitHub) → https://github.com/ZiadFrancis/MutliTimeframe_NY_Session_Break_Out Happy learning, happy coding ☕ ╚═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩═╩ ⚠️ These videos are educational and focus on algorithmic trading, AI, and Machine Learning, definitely NOT financial advice. If you enjoy algorithmic trading, Python backtesting, and systematic strategies, consider subscribing to CodeTradingCafe. Keywords: NY session breakout strategy, session breakout trading, multi-timeframe breakout system, Python trading backtest, JPY breakout strategy, Gold breakout strategy, algorithmic trading Python, breakout strategy backtest, session trading strategy, forex breakout system
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