Bollinger bands

Bollinger bands are an indicator of price volatility, that is, they indicate whether prices in a given period are subject to major changes or not.

In high volatility, it can be used to identify the formation of a significant price change, whereas low volatility identifies a moment of lateralization.

Bollinger bands also give us an operational signal, in fact when they are violated they also give us an overbought (violation of the upper band) or oversold (violation of the lower band) operating signal.

It is calculated as follows (source wikipedia):

To calculate the Bollinger bands, first use a moving average of G days (often 20) to which the value of the standard deviation multiplied by a given F factor (often around 2) is added or subtracted .

The upper band is then obtained by adding the standard deviation to the moving average F times. The central band (if you want to view it) is given by the moving average. The lower band is calculated by subtracting from the moving average F times the standard deviation.

On cryptocurrencies we recommend the standard parameters:

  • Period: 20
  • calculated on: closing price;
  • Standard Deviation 2;

In image 1 we can see an example on the BTC chart:

Image 1: Tradingview – bollinger bands on btc – 1 day time frame

In image 1 we can see signs of oversold and overbought marked in black.Circled in green, however, a false signal: the price after arriving oversold continued to fall instead of rising.

As with the other indicators and oscillators, it is therefore advisable to obtain feedback on prices and volumes before carrying out any operation.


  1. Wikipedia
  2. Achille Fornasini, “Financial markets: choice and management of speculative operations – Methods and systems of modern Technical Analysis to support operational decisions”, 1st edition of 1996, ETAS

Moving Avarages

Until now, to analyze the price trend, we have mainly talked about straight lines and figures that can be seen directly by looking at prices.

Additional instruments are oscillators, indicators and moving averages. These are tools that accept prices as input, but do not need to manually plot on the chart. Most need some input parameters that are used to calibrate their reactivity, also in relation to the timeframe used.

The first and simplest tool we will analyze is precisely the moving averages.

Moving averages can be used to filter price trends from noise (ie try to eliminate oscillations). The faster the moving average (ie the period on which it is calculated is shorter) and the more it tends to follow the trend in prices. By increasing the number of periods, instead, the short-term fluctuations are eliminated and the long-term price trend can be deduced.

A moving average calculated on too many periods of time, may cause you to lose important price changes on the spot.

Moving averages can also be used to generate operational signals of purchases or sales.
The operational signals that can be generated are the following:

  • When the moving average is above the price chart, then the trend is rising;
  • When the moving average is below the price chart, then the trend is going down;
  • When the average is above the price chart is in doubt.

A technique often adopted is to use two averages together, in order to understand the type of trend, a faster or a slower one. At this point the operational signals are given by the crossing of the two averages:

  • If the fast average rises above the slower one then it is a bullish signal;
  • On the contrary, it is a bearish signal.

A possible use of intersections is with:

  • 5 periods for the fast one
  • 20 periods for the slow one

NB : generally speaking,  moving averages  are not very reactive to trend’s changes;

NB2: The averages are not able to recognize if you are in a lateral phase of the market, giving false signals, so they are often used with the ADX and DI indicators, which we will talk about later

In image 1 we can see an example of the application of two moving averages (20 in red and 5 periods in green) on the graph of the BTC with 1 day timeframe. 

Image 1: TradingView Chart – Timeframe 1day – Example of moving averages over BTC

For example, we can see that in the last period of time the moving average in red is above the green one, which indicates that the trend is bearish. It can also be noted that i have two crossings, one (of the green that goes beyond the red one) in the uptrend phase, the other (of the red one that overcomes the green one) in the downtrend phase.


  1. Gabriele Belletti, “Trading con gli oscillatori. Strategie e tecniche per il trading di precisione”, Hoepli