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Technical Analysis

Bollinger Bands

Volatility bands placed above and below a moving average.

Full Definition

Bollinger Bands consist of a middle band (typically a 20-period simple moving average) and upper and lower bands set at a specified number of standard deviations (usually 2) above and below the middle. The result is a dynamic envelope around price that expands during high volatility and contracts during low volatility. Developed by John Bollinger in the 1980s, they remain one of the most widely used volatility indicators.

Bollinger Bands have several interpretations. Price touching the upper band can indicate overbought conditions, while touching the lower band suggests oversold conditions, useful for mean-reversion strategies. A "Bollinger squeeze," where the bands contract tightly around price, signals low volatility that often precedes a high-volatility breakout. Conversely, wide bands during strong trends can stay on the outer band for extended periods, which technicians call "walking the band," and should not be interpreted as reversal signals.

For example, if EUR/USD is ranging and its Bollinger Bands are unusually narrow with the middle band at 1.0870, upper band at 1.0895, and lower band at 1.0845, that squeeze suggests a breakout is near. A trader places buy stops above the upper band and sell stops below the lower band to catch the breakout direction. When price surges through 1.0895, the buy stop triggers with a stop below the middle band at 1.0870 (25 pips) and target at a measured projection of 1.0960 (65 pips), producing a 1:2.6 risk-reward.

In copy trading, Bollinger Bands contribute to the volatility-aware trade selection of systematic strategies. SteadyFlowFX's 9 algorithms may use band-based signals to identify squeezes, breakouts, and mean-reversion opportunities across the 8 currency pairs. The verified Myfxbook 1.73 profit factor reflects trade selection that often benefits from volatility filtering. Understanding Bollinger Bands helps subscribers see why certain setups appear during specific volatility environments.

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