What Are Moving Averages?

In technical analysis, one of the commonly and widely used tools to analyse the price action is a Moving Average. Whether you are watching stocks, futures, FX pairs or cryptocurrencies, Moving Average helps to visualize the average price on the chart.

What is a Moving Average (MA)?

Moving average is an indicator of price action based on the historical data. The indicator calculates the average price of an asset in a set timeframe on the chart. For the reason of strictly relying on the historical data, the Moving Average is classified as a lagging indicator. The calculation of a moving average is simple, yet someone might think that the moving average simply adds a set of data and divides it by it’s quantity, however it’s not entirely like that.

How is MA calculated?

Moving averages take a subset of data and divide that by the number of sets. For example, to calculate a 7-day moving average on Bitcoin’s daily chart, the calculation is done as follows:

Average prices of Day 1 + Day 2…. + Day 7 / 7 = 38 195.24

Average price of Day 1 is the calculation of 7 subsets, i.e. Day 1 has the Moving Average calculation as described above and so on.

And as the day ends and the average price is set, the calculation begins from the daily average of the price 6 days before the current day, the last bar is summed. Same calculation method is applied to other time-frames, monthly, weekly, hourly and minute. It is worth mentioning that the length of the MA is strictly based on the average price of an asset within the set time-frame. See example of a MA on an hourly chart below. Going 7 candles back, we start calculating the MA, the same way as above.

Hour 1 + Hour 2 +...+ Hour 7 / 7 = 38.632,31

When the last bar closes, and the new one opens for the next hour, the MA recalculates 6 previous bars and the new bar.

In other words, in the example with the set length at 7, the MA doesn’t calculate the whole set of historical data and divides it by 7, but uses 7 last subsets.

Why are Moving Averages important?

In accounting and finance, moving average helps to identify the average price of the money flow to have a clearer balance sheet and to predict the future average flow. For instance, a company may see based on the historical data the average weekly money flow based on a quarterly, annual historical data and set a goal and predict the future average flow over the next fiscal period.

In financial markets, MA are used to identify support and resistance levels of an asset. MA when used in a combination of RSI and Volume indicators may provide a clearer picture of the next price action. Whereas, MA can show the average price over the period of time, RSI can show the asset’s power and Volume can indicate the strength of the market participants and their willingness to support the either direction of an asset.

Types of Moving Averages.

There are several types of MA, but the most commonly used ones are SMA and EMA.

SMA - Simple Moving Average (SMA), the simplest calculation of data is used to identify the average price of an asset. The calculation is the same as described above and to ease your understanding we will show a mathematical formula of the SMA calculation.

SMA = AP1 + AP2 + AP3 +...+APn / n

Whereas:

AP = Average price

n = the defined time period / length

EMA - Exponential Moving Average (EMA) adds weight to the calculation in order to better predict the future price movements. To calculate the EMA, first SMA for the designated time period has to be completed, then a smoothing factor/multiplier is applied. The multiplier is found by this formula - [2 / (time-frame) +1]. So for the 7-day EMA the multiplier would be [2 / (7 +1)] = 0,25.

Mathematical formula for EMA calculation is as follows:

EMA = [AP - EMA (yesterday)) x multiplier + EMA (yesterday)]

Whereas:

AP = average price

Multiplier = [2 / (time-frame) +1]

Conclusion

Moving Averages still remain an essential part of the technical analysis, and used to generate various indicators such as John Bollinger’s - Bollinger Bands. MA’s identify support and resistance zones of an asset and are best when applied with other oscillators and momentum indicators.