How do you know if and when the price of a crypto asset is about to crash and burn or rip to the moon?
Well, you don’t, but there are some charting tools which provide an overview of the current conditions in a market, and these can help inform your buying and selling decisions.
One great method you can use to measure volatility is the Bollinger Bands indicator.
Volatility is sometimes used to describe the risk an investor takes, and whilst highly volatile assets do tend to be regarded as “riskier”, volatility and risk are not the same thing.
Risk is the chance of experiencing a loss, whereas volatility is the speed and size of price changes in a market.
Crypto markets are often highly volatile, and it’s not unusual to see large and rapid changes in token prices.
Being able to measure volatility is an extremely useful skill for any trader as it can give you clues as to when to enter and exit positions.
Bollinger Band indicators are one of the most useful tools to help you quickly visualise the volatility of a crypto token (or indeed any financial market).
Bollinger Bands are a charting tool which use the moving average price for the last few candle ticks as the baseline to create an upper and lower band of price ranges with a standard deviation of 2.
This allows users to see not only price movements, but also get a visual representation of the relative volatility in the market.
A standard deviation may sound really complex, but it’s actually quite simple and is just the way statisticians compile and measure how far a set of data points vary from the average.
A good example is measuring air temperature during the winter. There will be an average temperature, but each day will be slightly different, and the measured temperatures will generally fall into a distribution around the average. The graph below shows how this distribution works:
Most of the time (68.2% of the time — that’s 34.1% on both sides of the average) our measured temperatures will fall within the orange bands in the graph above, and this represents 1 standard distribution of the average.
However, sometimes you’ll get a day which is slightly warmer or colder than normal, and the temperature reading might fall outside the orange bands (denoting a standard deviation of 1), and into the green bands — within the range of a standard deviation of 2.
A Standard deviation of 2 includes a total of 95.4% of all measurements, and so it’s a more accurate way to interpret data.
Of course, there will be some outliers, unusually warm or cold days, which will fall even further outside, and will denote a standard deviation of 3 (4.2%) or even 4 (0.2%), however, these are unusual “edge cases” and quite rare.
Of course, as the winter progresses, the mean average temperature will also change slightly, and this of course means the range (the width) of our standard deviation will also alter too, and may get a little tighter or wider as we get more or less volatile weather.
Let’s move back onto crypto prices.
In any financial market, there is a typical mean average price which changes over time as traders buy and sell.
Sometimes, however, there is a lot of buying or selling pressure which moves the price dramatically. This happens a lot in crypto, which is why we say it can get pretty volatile at times.
However, just as in the example using temperatures, the same principle applies.
68.2% of the time, price movements will be within 1 standard deviation of the current mean average price, and 95.4% of the time, they will be within 2 standard deviations.
Bollinger Bands are indicators which track the last price movements, and plot three elements on your screen — an upper and lower band, and a Moving Average line, with the width of each band, and are usually calibrated to measure the standard deviation of 2 — or 95.4% of all the recent price ranges.
Enough talk, let’s see what Bollinger Bands look like on a trading chart:
As you can see from the chart above, when volatility is low (ie the price range is quite small) the Bollinger Bands get much tighter and closer together.
Conversely, the distance between the bands widens when volatility increases.
The bands are a measure of 2 standard deviations away from the Moving Average line. As you can see, the majority (95.4%) of ticks are within the bands, showing that the price movements are within 2 standard deviations of the Moving Average.
What you’ll also tend to notice from the chart above is that when a candle touches a band line, this can signal a reversal in direction.
For example, when the price goes up and touches the upper band, this quite often precedes a sell-off as investors take profit and sell their tokens. This is called being over-bought.
Similarly, when the price drops and meets the lower band, this is an indication that it’s been over-sold, and buyers often step in at this point, putting demand-side pressure on the asset which raises the price back up.
It’s very easy to use Bollinger Bands, and almost every charting tool has this indicator.
Why not try it out on TradingView — just load up any chart, click Indicators and select “Bollinger Bands” from the search box and voila!
However, at this point, we should issue a warning.
Although they are a really useful indicator for visualising both the price and the volatility of an asset, Bollinger Bands don’t tell you which direction the price will go next, and they are not a foolproof way of reading a market.
Other factors will always come into play, and like all indicators, Bollinger Bands are trailing, meaning they only tell you what has happened in the past, not what will happen in the future.
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