Live Trading Bot Strategy In Python

This time, finally, we delve into the world of live trading bots using Python. In this session, we test a strategy that was previously optimized and backtested, implementing it into a live trading bot connected to the market. This allows us to evaluate its performance under real market conditions, including spreads, commissions, and trading fees.

Our strategy involves detecting price trends using the exponential moving average and choosing entry points using Bollinger bands. These methods were introduced in a previous video and optimized for optimal parameters. The backtest results showed a return of 61% over approximately 35 trading days.

We discuss the Stop Loss (SL), which is defined relative to the Average True Range (ATR), and the Take Profit value, which is also related to the Stop Loss distance. We also highlight that some weeks may yield negative returns, reminding viewers of the inherent risks involved in trading.

We then proceed to walk through the Python code, demonstrating how to run the live test. I encourage viewers to apply this strategy to different assets and share their findings in the comments section.

Stay tuned for more videos on this topic, and until our next meeting, trade safely.

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The code I used in this video for download:
https://drive.google.com/file/d/1zNNP...

The previous video detailing the strategy:
   • Trading with Python: Simple Scalping ...  

#algorithmictrading #tradingbots #algotrading #forex