Auto-Detect All Recent Bullish Golden Crosses (Python Trading)

This tutorial demonstrates how to programmatically identify recent "Golden Cross" technical chart patterns in Python for all tickers within the S&P 500 index. I cover how to pull daily stock prices from Google Finance into Python via Google Sheets, how to calculate the 50-day and 200-day simple moving averages using pandas, and how to systematically detect stocks showing bullish crossovers, which are a widely known technical analysis pattern.

The script is fully customizable for different use cases. It's easily adaptable for larger watchlists, automated alerts with Cron jobs, and even algorithmic trading setups.

Important Note: This video is for informational & educational purposes only. It shows how to analyze past, historical stock performance. It is not for investment, trading, financial, or tax advice. Past performance does not equal future performance.

****Beta Test Preview****
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*Full Code*
https://deepcharts.substack.com/p/gol...

*Resources*
Auto-Refreshing S&P 500 Close Price Google Sheet: https://docs.google.com/spreadsheets/...

*Chapters*
0:00 Intro
0:15 What is a Golden Cross in Technical Analysis?
0:35 Workflow
0:50 How to Customize and Extend this Code
1:27 Getting Stock Close Data
2:21 Setting up the Python Environment
2:30 Importing Google Finance Data from Public Google Sheet
3:20 How to Prepare Data and Calculations of Simple Moving Averages (SMA) for Golden Cross crossovers
5:53 How to Identify "Death Crosses"