In this video, we explore automating multi-asset trading in Python and show how to test and optimize a trading strategy across different assets. Using Python, we backtest strategies on major forex pairs and gold to improve win rates and overall returns. We cover setting up a trailing stop on the daily time frame to maximize profits, using moving averages to identify trends, and leveraging Bollinger Bands for entry signals.
Follow us as we code the strategy in Python, automate the backtesting process, and optimize the parameters efficiently. This video provides a comprehensive guide to automating multi-asset trading and makes it easier for you to implement and improve your own trading strategies.

This approach to automating multi-asset trading in Python provides valuable insights and practical steps to improve trading strategies and backtests across different markets.

°°° Discount vouchers for my courses in Algorithmic Trading and Python:
Algorithmic Trading: https://bit.ly/CouponAlgorithmicTrading
Data analysis with Numpy and Pandas: https://bit.ly/CouponDataAnalysis
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Example of a live trading bot:
https://youtu.be/bZhtvvFm17A

To re-run the tests with your own data, you can download the Python code from the following link:
https://drive.google.com/file/d/11LkTVPQVK14dAbwKQq0HCRnGb46jYbZ8/view?usp=sharing

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