Crypto Mean Reversion System (Pullback & Bounce)

Mean Reversion Theory
The indicator operates on the principle that extreme price movements in crypto markets tend to revert toward their mean over time.

Consider this a valuable aid for your dollar-cost averaging strategy, effectively identifying periods ripe for accumulating or divesting from the market.

Research shows that:

• Short-term momentum often persists briefly after surges, but extreme moves trigger mean reversion
  
• Sharp drops exhibit strong bounce patterns, especially after capitulation events
  
• Longer timeframes (7-day) show stronger mean reversion tendencies than shorter ones (1-day)
  
  Timeframe Analysis
  
  1-Day Timeframe
  Pullback probabilities: 45-85% depending on surge magnitude
  Bounce probabilities: 55-95% depending on drop severity
  Captures immediate overextension and panic selling
  More volatile but faster signal generation
  
  7-Day Timeframe
  Pullback probabilities: 50-90% (higher confidence)
  Bounce probabilities: 50-90% (slightly moderated)
  Filters out noise and identifies sustained trends
  Stronger mean reversion signals due to extended moves
  
  Probability Tiers
  
  Pullback Risk (After Surges)
  Moderate (45-60%): 5-10% surge → Expected -3% to -12% pullback
  High (55-70%): 10-15% surge → Expected -5% to -18% pullback
  Very High (65-80%): 15-25% surge → Expected -10% to -25% pullback
  Extreme (75-90%): 25%+ surge → Expected -15% to -40% pullback
  
  Bounce Probability (After Drops)
  Moderate (55-65%): -5% to -10% drop → Expected +3% to +10% bounce
  High (65-75%): -10% to -15% drop → Expected +6% to +18% bounce
  Very High (75-85%): -15% to -25% drop → Expected +10% to +30% bounce
  Extreme (85-95%): -25%+ drop → Expected +18% to +45% bounce
  
  The probability ranges are derived from:
• Crypto volatility patterns: Higher volatility than traditional assets creates stronger mean reversion
  
• Behavioral finance: Extreme moves trigger emotional trading (FOMO/panic) that reverses
  
• Historical backtesting: Probability estimates based on typical reversion patterns in crypto markets
  
• Timeframe correlation: Longer timeframes show increased reversion probability due to reduced noise
  
  Key Features
• Dual-direction signals: Identifies both overbought (pullback) and oversold (bounce) conditions
  
• Multi-timeframe confirmation: 1D and 7D analysis for different trading styles
  
• Customizable thresholds: Adjust sensitivity based on asset volatility
  
• Visual alerts: Color-coded labels and table for quick assessment
  
• Risk categorization: Clear severity levels for position sizing