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Bollinger Band Basics

Contributed by John Bollinger

Bollinger Bands are available on MetaStock and most charting software. They have become popular primarily because they answer a question every investor needs to know: Are prices high or low?

What are Bollinger Bands? They are curves drawn in and around the price structure on a chart providing a relative definition of high and low. To wit: Prices near the upper band are high, prices near the lower band are low.

The base of the bands is a moving average that is descriptive of the intermediate-term trend. This average is known as the middle band and its default length is 20 periods. The width of the bands is determined by a measure of volatility called standard deviation. The data for the volatility calculation is the same data that was used for the moving average. The upper and lower bands are drawn at a default distance of two standard deviations from the average.

These are the standard Bollinger Band formulas

Upper band = Middle band + 2 standard deviations
Middle band = 20-period moving average
Lower band = Middle band - 2 standard deviations

Here is an example of Bollinger Bands applied to a chart:



To teach you how to use Bollinger Bands effectively would take a book, however the following rules serve as a good beginning point.

15 Basic Rules for Using Bollinger Bands

1. Bollinger Bands provide a relative definition of high and low.
2. That relative definition can be used to compare price action and indicator action to arrive at rigorous buy and sell decisions.

3. Appropriate indicators can be derived from momentum, volume, sentiment, open interest, inter-market data, etc.

4. Volatility and trend already have been deployed in the construction of Bollinger Bands, so their use for confirmation of price action is not recommended.

5. The indicators used for confirmation should not be directly related to one another. Two indicators from the same category do not increase confirmation. Avoid colinearity.

6. Bollinger Bands can be used to clarify pure price patterns such as M-type tops and W-type bottoms, momentum shifts, etc.

7. Price can, and does, walk up the upper Bollinger Band and down the lower Bollinger Band.

8. Closes outside the Bollinger Bands can be continuation signals, not reversal signals--as is demonstrated by the use of Bollinger Bands in some very successful volatility-breakout systems.

9. The default parameters of 20 periods for the moving average and standard deviation calculations, and two standard deviations for the bandwidth are just that, defaults. The actual parameters needed for any given market/task may be different.

10. The average deployed should not be the best one for crossover signals. Rather, it should be descriptive of the intermediate-term trend.

11. If the average is lengthened the number of standard deviations needs to be increased simultaneously; from 2 at 20 periods, to 2.1 at 50 periods. Likewise, if the average is shortened the number of standard deviations should be reduced; from 2 at 20 periods, to 1.9 at 10 periods.

12. Bollinger Bands are based upon a simple moving average. This is because a simple moving average is used in the standard deviation calculation and we wish to be logically consistent.

13. Be careful about making statistical assumptions based on the use of the standard deviation calculation in the construction of the bands. The sample size in most deployments of Bollinger Bands is too small for statistical significance and the distributions involved are rarely normal.

14. Indicators can be normalized with %b, eliminating fixed thresholds in the process.

15. Finally, tags of the bands are just that, tags not signals. A tag of the upper Bollinger Band is NOT in-and-of-itself a sell signal. A tag of the lower Bollinger Band is NOT in-and-of-itself a buy signal.

These rules outline the basic guidelines for using Bollinger Bands. For a more comprehensive understanding of the bands, I suggest that you read “Bollinger On Bollinger Bands”. The book starts with the basics, builds to the complex and teaches the technical process including which indicators to use and how to read charts.
The Bollinger Band Tool Kit for MetaStock provides easy to use implementations of all the trading systems and indicators from the book.

John Bollinger, CFA, CMT is probably best known for his Bollinger Bands, which have been widely accepted and integrated into most of the analytical software currently in use. He is the president of Bollinger Capital Management, a money management firm, and publishes a monthly newsletter, The Capital Growth Letter. He has eight financial websites: www.BollingerBands.com, www.BollingerOnBollingerBands.com, www.EquityTrader.com, www.FundsTrader.com, www.GroupPower.com, www.MarketTechnician.com, www.PatternPower.com and now a forex site, www.BBForex.com.

Support Tip
How can I find and delete local securities that are no longer trading?

Contributed by Equis Support

A good technical trader regularly cleans up the symbol lists they use for trading. Creating an exploration to identify securities that are no longer trading takes just a moment and saves you time in the future. The following method identifies securities that are no longer trading and provides a way to easily remove them from your lists.


Create a new exploration with the following formula:

Col A name: month, Col A formula: Month()
Col B name: day, Col B formula: DayOfMonth()
Col C name: year, Col C formula: Year()
Filter ( (Year() < 2009) OR (Month() < 2) )

Run the exploration. The results will be the securities that are no longer trading. Select all of the results and delete them.

Below is a step by step process of how to create this exploration:

1. Open MetaStock

2. Open the Tools menu

3. Select The Explorer

4. Click New

5. Name the new exploration (we suggest "no longer trading")

6. In Column A, type in the following:
- name: month

- formula: Month()

7. In Column B, type in the following:
- name: day

- formula: DayOfMonth()

8. In Column C, type in the following:
- name: year

- formula: Year()

9. In the filter column, type in the following
- ( (Year() < 2009) OR (Month() < 2) )

- Note: you'll want to change the '2009' and '2' to the current year and month before you run this exploration.

10. Click OK

11. Click Explore

12. Add your data folders to the Select Securities dialog

13. Click OK

14. Click Reports when complete and select the Results tab

15. Select the first security, hold down the Shift key and click on the last security

16. Right click on the selected securities

17. Select delete securities

MetaStock Features
The RMO ATM

Contributed by Devin Ekberg

With the recent highly turbulent financial markets, it is extremely important to consider volatility and volume as part of a trader’s technical . Volatility is defined as the relative rate at which the price of a security moves up or down, and is calculated using a statistical method of standard deviation. Volatility can be a trader’s best friend or worst enemy depending on how his/her accounts for it.

Most traders expect to make money quickly and easily; knowing when markets are dormant, active, or hyperactive can mean the difference between a fast moving profit and a slow churning loss. The RMO ATM add-on for MetaStock contains many templates and strategies for measuring volatility, including a set of indicators called “Zone Detector” and “Zone Fill” (See Figure 1 below).



The Zone Detector (dark green line) ranges from 0-1 indicating a period of sufficient activity (1) or insufficient activity (0). A value of one indicates enough activity is present to move the price action in either direction quickly and efficiently. When the value is zero, a trader is more likely to experience a sideways or choppy movement in price action.

The Zone Fill (light green histogram) is a secondary measure suggesting the activity is not only favorable for a trade, but also considered “hyperactive” and a trader can feel more comfortable with a larger position or more aggressive profit target.

These two indicators can be used along with the other strategies in the RMO ATM add-on as a filter for executing only the trades with the highest probability for success. Imagine a mechanism keeping one’s money out of the capital-draining choppy markets, and only in efficiently trending markets.

The RMO ATM was created by Rahul Mohindar, who is best known for his RMO Trade Model template in MetaStock 10. I have many clients who have given superb feedback in these strategies even in the most unpredictable financial markets of our lifetimes. If you have any questions about this product or others, you may contact me anytime for more detailed information. Until then, I hope your trading is successful.