Trading Bollinger Bands With Cryptocurrency
Bollinger Bands are a specialized type of technical analysis tool. They are specifically a kind of trading envelope or band. The purpose of trading envelopes and bands is the same. They offer relative low and high definitions that may be used for creating rigorous approaches to trading, based on pattern recognition, and more. Usually, bands are seen as a way to measure central tendencies as a base, like a moving average. Envelopes, on the other hand, encompass price structure without having a central focus that is clearly defined, perhaps by referencing lows and high, or via cyclic analysis. In this article, we will be using trading bands as a way to refer to sets of curves that are used by market technicians for defining a low or high on a relative basis.
When researching the subject, the earliest trading band examples that I was able to find came in 1960 from Wilfrid Ledoux. He used curves that connected the Dow Jones Industrial Average's highs and lows as a type of long-term market-timing tool. The precise sequence for trading band development following Ledoux gets a bit cloudy. A trading system was proposed by Chester Keltner in 1960 called the 10-Day Moving Average Rule. Market technicians later referred to it as Keltner bands. Next came J.M. Hurst. In his work, he used cycles for drawing envelopes around price structures. This work was elegant that it was transformed into a kind of grail for the many people to attempted to replicate it. However, few succeeded.
Percentage bands were very popular in the early 1970s, although we do not know who created them. These were a moving average that moved up and down according to a user-specified percentage. One decided advantage that percentage bands have is deploying them by hand is easy. At any given point in time, a 7% band is comprised of a base moving average, a lower curve that is at 93% of the base, and an upper curve that is at 107% of the base. (It was suggested by Arthur Merrill to multiply and divide by one plus the desired percentage).
Percentage bands were by far the most popular bands when I first started to use grading bands. Then Donchian bands came along, which were a great example of envelopes. It consists of the lowest low and highest high of the immediate prior n-days. Those are the major types of envelopes/bands that I am aware of. There have been numerous variations on those concepts over the years, with some of them still being used today. Currently, the most popular trading band approaches are Bollinger, Percentage, Keltner, and Donchian bands. Percentage bands remain fixed, they don't adapt when market conditions change; Keltner bands make use of the Average True Range for adaptive mechanisms; Donchian bands use the recent lows and highs. Bollinger Bands make use of the standard deviation in order to adapt to market conditions that are changing.
When and How Does It Work?
When I became active in the markets in 1980 on a fulltime basis, my main interest was technical analysis and options. In those days, it was hard to find information on both of them, but I was persistent. I managed to make some progress with help from an early microcomputer. We used percentage bands at that time and compared price actions in the bands to supply/demand tool action like the David Bostian tool called Intraday Intensity. When a touch of the upper band on price was not confirmed in the oscillator by strength, that became a sell setup, while a similarly unconfirmed tag on the lower band indicated a buy setup. However, the problem with this approach was that over time the percentage bands had to be adjusted to keep them relevant to the price structure. Also, this adjustment process allowed emotions to enter into the overall analytical process. So if you happened to be bullish, then you naturally tended to draw the bands so that a bullish picture was presented. If you were bearish on the other hand, it naturally resulted in a picture that had a bearish bias. That was clearly a problem. We had some success with reset rules such as lookbacks. However, adaptive mechanisms were what was really needed.
At the time, I was trading options and had developed some volatility models in SuperCalc, which was an early spreadsheet program. I was copying a volatility formula down a data column one day and noticed that over time the volatility was changing. When I saw that, I wonder if the volatility could be used for setting trading bands' widths. Today that idea might sound obvious, however, it was a real leap of faith at that time. Volatility was viewed as a static quantity at that time, as a property of the security and if it changed at all, it only did so in the very long-term, such as over the life of the company. Today, we are aware that volatility is a very dynamic quantity.
How can I use it in the blockchain space?
After doing some experimenting, I settled in on the formulation that we all are familiar with today, an n period moving average that has bands drawn below and above it at intervals that are determined by a multiple of the standard deviation (the population calculation of the standard deviation is what we use). Today's faults are the same ones from 35 years ago. The moving average has 20 periods with bands that are set at minus and plus two standard deviations from the same data that is used for calculating the average. However, at that time there were no "Bollinger Bands." They came later when Financial News Network host Bill Griffeth asked me on air what my bands were called. I had presented a chart of mine that showed an unconfirmed tag of the upper band and had explained that a sell signal would be generated on the first down day. Then Bill asked me what I called the lines that were around the price structure. I was completely unprepared for the question, so I just blurted out "Bollinger Bands," which was the obvious alliterative choice.
So what are Bollinger Bands exactly? They are curves that are dawn around and in the price structure. They are usually comprised of a moving average (which is the middle band), a lower band, and an upper band. They answer the question of whether prices are low or high on a relative basis. The time when Bollinger Bands work the best is when the middle band is selected to reflect the intermediate-term trend. Relative price level data is combined with the trend information.
Excerpts from John Bollinger-
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