Strong Support and Resistance Levels Detection With Python For FOREX And Stocks Trading Algorithms
Welcome to this video where we delve into a straightforward yet powerful method for identifying key levels in trading—specifically, robust support and resistance levels. This video tutorial provides an in-depth exploration of how historical data can be leveraged to detect these critical levels, giving you insights into potential price bounces and breaks.
📊 Methodology Overview:
We’ll kick things off by loading our data and identifying fractals or pivot candles. These are candles that stand out by being higher or lower than their neighboring candles. The video visually guides you through recognizing these pivot candles marked with purple points on a graph.
📈 Plotting Levels:
Following the pivot candle identification, we move on to plotting support and resistance levels. The video demonstrates how to count the number of times the price has bounced on each of these levels, enabling the assignment of a strength score. Remember, we focus on assigning scores to zones rather than exact levels, a key concept we’ll automate in the coding segment.
📊 Scoring and Analysis:
Assigning strength scores to support and resistance levels is crucial. The video explains the process, discussing the option to split resistance and support scores or keep them merged for a comprehensive mixed score.
🔍 Future Trading Considerations:
Understanding that past performance can indicate future behavior, the video emphasizes the significance of these identified levels for future trading decisions. If a level has shown strong support or resistance in the past, it’s likely to exhibit similar behavior in the future.
🐍 Python Code Walkthrough:
The latter part of the video delves into the Python code, providing a detailed walkthrough and discussing some insightful results derived from applying this simple yet effective approach.
👍 Support and Interact:
Don’t forget to support the channel by liking, commenting, and sharing your ideas. Feel free to join our community and drop your comments, suggestions, or questions below.
📈 Trade Safe, Code with Confidence:
As we conclude, remember to trade safe, enjoy your coding journey, and stay tuned for more content. Until next time!
🚀 Code Download: If you’re keen on the coding aspect, the code for this technique is available for download in the link below. Feel free to grab it for your practice and experiments:
https://drive.google.com/file/d/1ATNIwG-gYUHs3BfHrsyfeS7ctTxBGW1t/view?usp=sharing
The data file:
https://drive.google.com/file/d/1qIkiEcCIO_5irTBGpWl96ftBtViWXVvm/view?usp=sharing
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