Bollinger Bands—Part 1: The Basics

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Introduction

Imagine that you are placed on an island with only a trading platform (TradingView of course) and the island gods only permitted three indicators. What three indicators would you carefully select? At the top of my list would be the Bollinger Bands.

Some people seek out complex or cryptic indicators in search for a better edge. Of course, some indicators and modes of anlaysis can be very useful despite being complex. But some indicators like the Bollinger Bands, can be valuable because of their simplicity, and they can also have a wealth of analytical value that is more complicated than would appear at a glance.

In 1983, John Bollinger invented the eponymous Bollinger Bands. This valuable indicator operates centrally on the concept of standard deviation. In other words, standard deviation is a basic statistical concept behind the indicator, i.e., this concept is basic for mathematics professors and experts, but perhaps intermediate to advanced level for others.

Standard Deviation

One can easily find the common standard-deviation formula on the internet from many reputable sources. But one doesn't have to master the formula to use the concept of standard deviation—standard deviation essentially measures the variation in the data points around a mean (or average). Khan Academy offers a very useful and insightful guide to those who want to learn the core concepts of standard deviation. Supplemental Chart A contains Khan Academy's standard-deviation illustration and its well-worded explanation, although no one alive today can take credit for discovering and establishing this formula.

Supplemental Chart A (Credit to Khan Academy's website for illustration with explanation of standard deviation)



Here is a short, somewhat summary explanation of standard deviation's formula (though it doesn't apply to standard deviation of samples, a slightly different formula).

• Calculate the mean of a data set (e.g., a price series).
  
• Calculate each data point's distance, or variance, from that mean.
  
• The distance between each data point and the mean is then squared.
  
• Sum all the squared distances between each data point and the mean.
  
• Divide the sum of the squared distances by the total number of data points, or values in the data set.
  
• Take the square root of the quotient from the previous step, which is the average of all data points' squared distances from the mean.
  

Moving Calculations

Having identified the statistical concept at the heart of the bands' operation, it helps to remember that the moving average at the center of the bands, sometimes called the middle band of the Bollinger Bands, mean that the entire indicator should be considered a "moving indicator." In other words, even the standard-deviation bands, plotted a given number of standard deviations above or below the moving average, are moving based on the price data that evolves as time passes. Just like the moving average at the center of the bands continues to calculate the mean based on a moving lookback window of 20 periods or some other fixed number of periods, the standard deviations above and below the mean also derive from a moving lookback window.

Analysis / Interpretation

Bollinger Bands, as John Bollinger described in the journal Technical Analysis of Stocks & Commodities, "answer the question whether prices are high or low on a relative basis." He further explained that the "bands do not give absolute buy and sell signals simply by having been touched; rather, they provide a framework within which price may be related to indicators." He essentially recommended comparing price in relation to the bands and then using the action at the edges of the bands and using such signals in combination with another well-selected indicator (e.g., one might consider RSI).

As created by Bollinger, the bands are typically set at +2 and –2 standard deviations above the mean. This can be adjusted on TradingView's platform. A well known trader, Anthony Crudele, uses the Bollinger Bands set at +3 and –3 standard deviations from the mean. He also uses the bands extensively as part of his system, and he does so with some unique and interesting features that he added. This author recommends following his videos regardless of whether his strategy is ultimately followed or adopted or whether some other strategy is adopted as most suitable for a particular asset or time frame.

The bands not only measure whether price is high or low on a relative basis. But importantly, they reveal realized-volatility conditions in the market. If price volatility (or variation from the mean without regard to direction) is expanding in a trend-like move on the specific time frame being examined, whether hourly, daily, weekly, monthly or longer, then the Bollinger Bands reveal this by opening and widening, much like jaws. The jaws of the bands contract when volatility is contracting. Volatility—implied and realized—tends toward cycles and mean reversion. So the bands helpfully show traders where volatility is within its cycle. Some traders, for example, use the bands to trade squeezes, and when the bands contract for a substantial period of consolidation and narrow significantly. The squeeze helps increase the probability of a volatility expansion, a potential a widening of the bands as price moves either in the direction of the prior trend or a reversal. As with other indicators, the significance of the signal should be interpreted in the context of the time frame being analyzed.

Supplemental Chart B


In Supplemental Chart B, notice how the Bollinger Bands contracted as price consolidated in the latter part of last year on the weekly chart of SPY. The Bollinger Bands have been expanding as price has pushed higher to new highs at the degree of trend shown, i.e., the uptrend from 2022 lows to present.

Conclusion

The Bollinger Bands provide more analytical tools and features than the ones described today. If readers are interested in a more in-depth post on Bollinger Bands (perhaps a Part 2 as contemplated by the title), please indicate this in the comments! Look forward to hearing from you.

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Author's Comment: Thank you for reviewing this post and considering its charts and analysis. The author welcomes comments, discussion and debate (respectfully presented) in the comment section. Shared charts are especially helpful to support any opposing or alternative view. This article is intended to present an unbiased, technical view of the security or tradable risk asset discussed.

Please note further that this technical-analysis viewpoint is short-term in nature. This is not a trade recommendation but a technical-analysis overview and commentary with levels to watch for the near term. This technical-analysis viewpoint could change at a moment's notice should price move beyond a level of invalidation. Further, proper risk-management techniques are vital to trading success. And countertrend or mean-reversion trading, e.g., trading a rally in a bear market, is lower probability and is tricky and challenging even for the most experienced traders.

DISCLAIMER: This post contains commentary published solely for educational and informational purposes. This post's content (and any content available through links in this post) and its views do not constitute financial advice or an investment or trading recommendation, and they do not account for readers' personal financial circumstances, or their investing or trading objectives, time frame, and risk tolerance. Readers should perform their own due diligence, and consult a qualified financial adviser or other investment / financial professional before entering any trade, investment or other transaction.

1 lut

Uwaga

When the bands are expanding, "opening the jaws" as some seasoned traders like to say, this is not the time to treat a band tag by itself as an overbought / oversold signal and trade a reversal accordingly. As the bands expand, it is often in conjunction with a a trend move. Sometimes, fakeouts can occur in which price tags a band in a direction counter to its ultimate move. But the overbought / oversold signal of a band tag works best only when the bands are essentially stable and flat, usually contracted, and moving sideways along with price action trading in a range, the tag does not result in a decisive move where price starts walking the bands and the bands start expanding.