Volatility Compression: ATR, Bollinger Bands & Keltner Squeeze

Catching explosive volatility expansions when 2.0σ Bollinger Bands coil inside 1.5x ATR Keltner Channels. Within the Technical Analysis curriculum (Indicators & Oscillators → Trend & Volatility), this topic establishes the concrete quantitative rules and execution mechanics required for live market deployment.

Professional desks never rely on ambiguous visual guesses for atr. Instead, every entry, invalidation level, and risk parameter is defined mathematically before a single order reaches the exchange gateway.

Hover over key terms below for instant definitions: Atr, Bollinger Bands, and Keltner Channel. For the complete mathematical derivation and edge-case analysis, open worked example & quantitative lookup matrix for atr bollinger keltner squeeze.

• Atr — Core structural driver governing volatility compression: atr, bollinger bands & keltner squeeze.
• Bollinger Bands — Prevents premature entries and enforces mechanical discipline across Trend & Volatility.
• Keltner Channel — Ensures worst-case scenario losses stay strictly within predetermined R-multiple budgets.

1. 1
   1. Pre-Session Calibration & Regime Check

   Measure baseline volatility and liquidity parameters for atr prior to market open.
2. 2
   2. Mechanical Signal Confirmation

   Wait for a completed bar close confirming the bollinger bands threshold—never pre-empt mid-candle.
3. 3
   3. Risk-Normalized Sizing & Order Placement

   Compute exact lot quantity from the invalidation distance and dispatch via a Marketable Limit order.
4. 4
   4. Post-Trade Telemetry & Audit

   Log arrival price, fill slippage, and MAE/MFE metrics against the Trend & Volatility benchmark.

Implementation & Quantitative Model

1export function isBollingerInsideKeltner(stdDev20: number, atr20: number, bbMult = 2.0, kcMult = 1.5) {2  return bbMult * stdDev20 < kcMult * atr20;3}

Cross-reference standard risk definitions such as drawdown, slippage, and Sharpe ratio when auditing your logs.