It is second nature to stick Bollinger Bands on price charts but most traders do not understand the full value of this time-tested indicator (for additional reading, refer to The Basics Of Bollinger Bands®). Let’s change that with a review of its many applications and examine new ways through which it can improve your bottom line (for related reading, refer to Using Bollinger Band® "Bands" To Gauge Trends). We will start with a brief background on its construction and then move on to the original interpretations you can apply right now in your market analysis.

American financial analyst John Bollinger laid the groundwork for this powerful tool in the early 1980s, first applying it to the options markets. Price channels at that time kept a constant width, ignoring volatility as a major variable. Bollinger changed that omission by adding standard deviation (SD) rules to Keltner Channels so they would expand and contract in reaction to shifting market conditions (for related reading, refer to What's the difference between Bollinger Bands® and Keltner Channels?). The indicator had no name when Bollinger posted his first band-heavy charts on the Financial News Network, a former incarnation of CNBC, but was dubbed Bollinger Bands as it grew in popularity in the 1990s (for related reading refer to Tales From The Trenches: A Simple Bollinger Band® Strategy).  

Most traders expect trending action when Bollinger Bands expand and rangebound conditions when bands contract but this simplified interpretation rarely produces actionable buy or sell signals. The real power of the bands is awakened when price/band interactions are categorized into observable patterns that yield specific predictions on short-term price action (for related reading, refer to How do I create a trading strategy with Bollinger Bands® and moving averages?). These organize naturally into top, center and bottom band crosses, well as relative band angles when price strikes them. In addition, the depth of penetration through the top or bottom band holds special significance in prediction because it only happens when a security’s behavior stretches away from its typical state of rest, or mean reversion level.

Most technical analysis programs come with Bollinger Bands preset to the 20-bar Simple Moving Average (SMA) and 2 SDs. The moving average denotes a central tendency point where price should return after it swings higher or lower. Standard deviation predicts how far a swing should carry based on current volatility, which is updated with each price bar. Top and bottom bands visualize these hidden levels, which are relative to the moving average chosen for the indicator. The 20-bar works fine in most cases, so there is no need to data mine for the perfect input.

Fine Tuning Standard Deviation

It is a different story with standard deviation because highly emotional markets routinely push price beyond 2SDs. An effective solution is to add shadow bands at 3SD to account for these volatile conditions, which require more risk-sensitive buy and sell signals. You can see an additional layer of information with Tesla Motors (TSLA) in the summer of 2014 when it rallied to an all-time high. Although the stock pierced the 2SD band repeatedly, 3SD held the trend in each instance, providing reliable clues on reversals and waning momentum. Also note how peaks in price rate of change (PROC) tended to match excursions into the 3SD bands. This highlights the natural symbiosis between these indicators.

Box and Flower Patterns

Bollinger Bands show their greatest power when price rises into the top band or descends into the bottom band. The shifting relationships between price, bandwidth and band-angle generate an assortment of patterns that emit unique short-term price predictions. Generally speaking, expect bands to hold back price when they remain horizontal into a cross or slope against price direction. These are called rising or falling box patterns. Alternatively, the top band turning higher in response to rising price or the bottom band turning lower in response to declining price indicates that resistance is moving away, allowing the developing trend to extend higher or lower. These emit flower patterns, evoking the image of flower petals opening to the energy of sunlight.

Combine price pattern analysis (for related reading, refer to How To Interpret Technical Analysis Price Patterns: Triple Tops And Bottoms) with Bollinger Bands to elicit the most reliable short-term predictions. Illumina (ILMN) gaps up to a new high in October and stalls out two weeks later. Bollinger Bands contract, as a new trading range develops, yielding a crossover with the rising bottom band (1) in November. This falling box pattern holds, triggering a reversal that generates a top crossover into a contracting band (2) a few weeks later. This rising box pattern holds as well.

The stock returns to the bottom band (3) in December, piercing it and stretching nearly 100% outside its boundaries. This predicts an impending reversal that combines with support at the top of the October gap, even though the bottom band opens on the second bar. This is common behavior because the price pattern has greater impact on short-term direction than shifting volatility. The top cross (4) in January carves an upside down version of the December failure, with a slight upward turn that runs straight into resistance at the October top. In both cases, timely reversal bars forced Bollinger Bands back toward the horizontal, re-establishing the rangebound box for another round of two-side action.

Stairstep and Climax Patterns

Fully opened bands with price moving easily along its edges create stairstep patterns, denoting stable trends that may continue for an extended period. Thrusts outside the band, reaching toward 3 and even 4SD signify overheating, commonly associated with a climax pattern that predicts a pause in the trend or outright reversal. Simple retracements (for related reading, refer to Retracement Or Reversal: Know The Difference) to the band’s center, the 20-bar SMA in most cases, signify natural mean reversion swings or resting periods that should attract willing buyers in an uptrend and willing sellers in a downtrend.

Freeport-McMoran (FCX) enters a deadly stairstep pattern during a long downtrend. It descends day after day in September and October, touching but rarely piercing the bottom band. A deeper penetration mid-month (red rectangle) triggers an immediate retracement that stalls exactly at the 20-day SMA mean reversion level. The stock resumes its downward trajectory into November and enters a retracement that spends another seven days reverting to mean. A quick pop into the declining top band (blue rectangle) sets off a rising box reversal as expected, yielding more downside into December. Once again, it pops to the 20-day SMA, spending more than two weeks at that level, before plunging into the 3SD bottom band and completing a climax pattern that triggers another reversal (green rectangle).

Multiple Time Frames

The Bollinger Band analysis works extremely well when applied to two time frames at once. For example, focus on relatively rare strikes at top, center and bottom weekly bands, using those levels for buy or sell signals when daily bands line up in similar patterns. The Illumina (ILMN) weekly chart shows a 10-month trading range that ends right after the stock pierces the horizontal bottom band, triggering a weekly falling box reversal. The initial trend wave ends at the top band, yielding the sideway pattern highlighted in a prior example. Note how the two falling box reversals highlighted on the daily chart began at the 20-week SMA. Finally, the top weekly band is lifting up and away from price bars, completing a bullish flower pattern that predicts an eventual breakout.

The Bottom Line

Bollinger Bands have become an enormously popular market tool since the 1990s but most traders fail to tap its true potential. You can overcome this deficit by organizing price-band relationships in multiple time frames into repeating patterns that predict specific short-term price behavior.