Bollinger Band Mean Reversion
Learn how Bollinger Bands combine a moving average and volatility envelope, and how mean-reversion systems handle band walks, squeezes and volatility regime change.
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Bollinger Bands place a volatility-sensitive envelope around a moving average. Mean-reversion traders often fade moves toward an outer band, but strong trends can “walk” the band instead of reverting.
Learning objectives
- Explain the centreline and volatility-envelope construction.
- Distinguish band touch from a complete mean-reversion signal.
- Account for band walks, squeezes and changing volatility.
What it is
A common Bollinger Band uses a 20-period simple moving average plus and minus two rolling standard deviations. The width expands when realised volatility rises and contracts when volatility falls.
The bands describe recent price dispersion, not a hard probability distribution. Crypto returns are not perfectly normal and can exhibit fat tails, jumps and volatility clustering.
How it works
In range conditions, price may oscillate around the centreline and outer-band excursions can identify stretched location. In strong trends, price can repeatedly close near or beyond one band.
A squeeze—unusually narrow bands—signals low recent volatility, not direction. Fading the first expansion after a squeeze can be hazardous because the market may be transitioning into a trend.
Mean-reversion systems can combine band location with a trend filter, close-back-inside rule or momentum deceleration. Each additional condition reduces frequency and changes entry price.
Stop placement should be independent of the band if the band itself expands with volatility. Otherwise the stop can mechanically move farther away after the trade deteriorates.
How to analyse and apply it
| Check | Why it matters | What to verify |
|---|---|---|
| Lookback N | Defines the centreline and volatility sample. | Keep fixed and test robustness. |
| Multiplier k | Controls envelope width. | Treat 2σ as convention, not certainty. |
| Regime | Determines whether fading extremes is sensible. | Filter out strong directional breakouts if required. |
| Entry confirmation | Can reduce band-walk entries. | Define close-back-inside or structure rule. |
A strategy is not complete until the signal, sizing, execution, invalidation and review process are explicit. Any discretionary override should be recorded so it can be separated from the tested rule set.
Worked example and thought exercise
A 20-day average is £100 and rolling standard deviation is £4. With k=2, bands are roughly £92 and £108. Price closes at £109, then the next day closes back at £107.
A system that requires a close outside followed by a close back inside has a signal; a system that buys every lower-band touch would behave very differently. Neither should be mixed in evaluation.
Thought exercise: if bandwidth has just risen from 6% to 18%, should the same fixed cash position size be used?
Common mistakes and practical workflow
- Assuming ±2 standard deviations means 95% of future prices stay inside.
- Fading a strong band walk without a regime filter.
- Treating a squeeze as a directional signal.
- Moving the stop outward because the bands widened after entry.
Practical workflow
- Calculate bands from a fixed data source/timeframe.
- Classify trend and volatility regime.
- Specify touch vs close-back entry.
- Set invalidation separately and size for current volatility.
- Record performance by regime, not only in aggregate.
✅ Knowledge checkpoint
- Why do Bollinger Bands widen?
- What is a band walk?
- Why does a squeeze not predict direction?
- Why is a normal-distribution interpretation dangerous in crypto?
FAQs
❓ Does a price above the upper band mean “too high”?
No. It means price is high relative to a recent moving-average/volatility envelope.
❓ What does a squeeze mean?
Recent realised volatility has contracted; direction remains unknown.
❓ Can bands be used in trends?
Yes, but the interpretation may shift from mean reversion to trend strength.
❓ Should stops follow the expanding band?
Only if that is explicitly part of a tested rule; otherwise it can increase risk after entry.
📋 Summary
Bollinger Bands adapt price location to recent volatility, which makes them useful context for mean reversion. Their weakness is regime change: volatility expansion and trend persistence can turn an apparent extreme into the start of a larger move.
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