The moving average is one of the most used and at the same time one of the most useful technical indicators. There are, however, different types of moving averages. To understand the differences between them, we will present you with an overview in this article.

A simple moving average is the most common form of a moving average. For its calculation every period used is treated equally. If you are using a 15 period moving average, for example, your result will be the exact average of these 15 periods. Period 1 and period 15 will influence the result in exactly the same way.

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Some traders believe that recent price movements are more relevant for predicting the future. If you are using a 15 period moving average, they would argue that the most recent period is far more relevant than period 15. To let the moving average reflect this belief, they multiply each period with a factor. The more recent a period is, the higher the factor. The most recent period is multiplied with the total number of periods used. For each following period, the factor is reduced by one. In a 15-day moving average, the most recent period is multiplied with 15, the second most recent period with 14, and so on. The last period is multiplied with 1. In other words: The most recent period will reflect the result 15 times as much as period 15.

The exponential moving average is special form of the weighted moving average that emphasizes recent periods even more. For its calculation, the weighing factor is applied exponentially instead of linear. This means, the most recent is exponentiated by the number of total periods used. For each consecutive period, the exponent is reduced by one. This calculation creates a parable with much steeper declining weighing algorithm than the regular weighted moving average with linear factors.

For a volume weighted moving average, the period’s price is multiplied with the period’s volume. This type of moving average is used by traders who believe that periods with high volume are more significant for future price developments than periods with low volume.

Which moving average you should use for your trading largely depends on your personality and which type of moving average you feel the most comfortable with. The most important difference between these types of moving average is their quickness to react to recent price movement.

**An exponential moving average** places more emphasis on the most recent time period than a weighted moving average, which places more emphasis than a simple moving average. The more recent periods influence the moving average, the quicker a change in price direction will make the moving average turn around.

If you are using a moving average to generate trading signals or indicate the general market direction, this creates a significant difference. Since an exponential moving average is the quickest to react, it will generate the most trading signals and provide you with the most trading opportunities. It will, on the other hand, also create the highest number of false signals which cause you to lose trades.

Therefore, an exponential moving average is **best suited for** traders looking to generate many signals and have the moving average as close to the current price as possible. This can be due to a high risk tolerance by these traders, or to a specific point in their strategy.

One of the most debated forms of use for a moving average is as an indicator of the main market direction in a trend following strategy.

While an exponential moving average will change direction more quickly and therefore has tendency to generate signals too early, a simple moving average sometimes takes too long to change direction and generates signals too late.

Therefore, none of them is by definition better than the other. If you are using a moving average this way, you have to use a trial and error approach to find the right type for you. A good trading diary will help shorten your search.

If you want to learn more about the use of moving averages in binary options, we recommend you to read the following: