Gann DJI Mass Pressure Index 2023

8시간 전

This indicator is based on W.D. Gann's theory of market cycles and mass pressure analysis. Gann believed that historical price movements repeat over time due to natural, economic, and psychological forces. The Mass Pressure Index identifies and visualizes these cyclical patterns to forecast potential market movements, analyzing past Dow Jones Industrial Average (DJI) data.

Note: TradingView does not support future forecasts in scripts. This tool is intended for proof of concept and back-testing. For full access to Mass Pressure Index data from 1960 to 2040, please contact [e-mail]

Overview of Gann Theory: W.D. Gann, a legendary trader, proposed that market movements follow specific cycles influenced by timeframes, with the "Master Time Cycle" (60 years) being most significant. Prices often repeat patterns tied to past decades, offering forecasting opportunities.

Cycle Construction:

• 60-Year Cycle: The primary "Master Time Cycle."
  
• 60/20 Cycle: Blends 60-year and 20-year patterns for refined insights.
  
• 60/40/20 Cycle: Incorporates 60, 40, and 20-year trends for medium-term analysis.
  
• 60/30/20/10 Cycle: Adds shorter cycles for detailed behavior.
  
• 80/60/20/10 Cycle: Extends the analysis to even longer-term patterns.
  

Usage: The indicator is tailored for the DJI and related tickers, identifying major yearly swing highs, lows, and pivots. The plotted lines represent adjusted YTD performance for each cycle. By observing convergence or divergence in these cycles, traders can anticipate potential market shifts.

Important Notes:

• Educational purposes only; not financial advice.
  
• Suitable for retrospective analysis and forward-looking insights.
  
• Interpretation should be combined with other tools for robust analysis.
  

Disclaimer: This script is for informational and educational purposes only and should not be considered financial or investment advice. Trading carries significant risk. Conduct thorough analysis and consult with licensed professionals before trading. The author is not liable for any losses incurred. Past performance is not indicative of future results.