🚀Calculating CPR Levels on a Chart using Python Backtesting Libraries 🚀
I've been working on calculating CPR (Central Pivot Range) levels using a backtesting library, and it's been quite a learning experience! 📝 CPR is a great tool to analyze potential support and resistance levels, helping traders better understand market trends and reversals. However, setting it up with a backtesting library presented some challenges, especially when it came to accurate level plotting and configuring the chart for optimal insights. If you’re also exploring this, here’s a quick breakdown of the steps and some tips that might help: Define CPR Levels: To calculate CPR, you need to define the Central Pivot (CP), Top Central Pivot (TCP), and Bottom Central Pivot (BCP). This usually involves the day’s high, low, and close. Set Up Backtesting Charting: Use libraries like Backtrader or TA-Lib to plot CPR on historical data for better backtesting. Implement Visualization: Adding CPR levels directly on the price chart helps in visualizing key support/resistance zones. I'm still fine-tuning this setup, and any suggestions from the community would be appreciated! Drop a comment if you're familiar with these calculations or if you'd like to collaborate on this!