✓ Mathematical
◆ The PatternMiddle = SMA(20), Upper = SMA + 2σ, Lower = SMA − 2σ.
Bollinger Bands — John Bollinger's volatility envelope (1983).
Middle Band = SMA(20)
Upper Band = SMA(20) + 2σ
Lower Band = SMA(20) − 2σ
Upper Band = SMA(20) + 2σ
Lower Band = SMA(20) − 2σ
Bands expand with volatility, contract during quiet periods.
Key concepts:
• Squeeze: Narrow bands → low volatility → big move coming
• Walk the band: In strong trends, price can ride the upper/lower band
• Mean reversion: Price touching outer band → may return to middle
• ~95% of closes fall within the 2σ bands
• Squeeze: Narrow bands → low volatility → big move coming
• Walk the band: In strong trends, price can ride the upper/lower band
• Mean reversion: Price touching outer band → may return to middle
• ~95% of closes fall within the 2σ bands
Pattern bridge: Price mean ± 2σ is a normal distribution confidence band applied to price. In ML, batch normalization standardizes activations the same way — center, then scale by deviation.
Performance in practice
- The Bollinger Squeeze (bandwidth < 6-month low) precedes large moves ~75% of the time — but doesn't tell you which direction
- Mean-reversion trades (buy lower band, sell upper) work well in ranging markets. In trends, price "walks the band" — touching the upper band is confirmation, not a sell signal
- Combining Bollinger with Keltner Channels creates the "TTM Squeeze" — a popular volatility breakout system used by active traders
When to use this
✓ Use when: Measuring current volatility vs historical norms. Mean-reversion strategies in ranging markets. Identifying squeeze setups before breakouts. Setting dynamic stop-loss levels.
✗ Skip when: As a standalone buy/sell at the bands. During news events (bands widen after the move, not before). When you need directional bias — bands are non-directional.