Moving averages are trend followers. There are various calculation approaches that can be used over any period of time and with different courses. Common to all averages is their characteristic as a “flexible” trend line, which provides objective information about the trend direction of the market without any room for interpretation. Each analysis program allows the calculation and display of moving averages.
A simple moving average is the average of the prices of the last X periods. Periods can be days, weeks, hours, or minutes. Forex trading often uses hourly or daily averages.
A simple moving average with X = 10 gives the average price of the last 10 time units used. With the inclusion of each new time unit, the oldest falls out. The closing prices of the respective periods can be included in the calculation as well as the average prices.
Moving average: the longer the slower
The average is shown as a line in the chart. The line reacts more strongly to market movements the fewer periods it covers. A short moving average therefore swings quickly and never moves far from the market. A very long average, on the other hand, behaves sluggishly and clearly moves away from the course, especially when there are rapid price movements in one direction or the other.
The simplest application of the moving average uses it without an additional filter as an indicator of the prevailing trend that is being followed. Example: If the market rises above its 250-day average from below, this is interpreted as a long signal. However, if it falls below the average line from above, either only the long position is closed or even a (net) short position is opened.
Practical explanation in trading
In practice, this simple concept is rarely used. However, it does illustrate basic properties and weaknesses of moving averages. The very long average in this case means that a large part of the market trend is missed because the entry signal is given late. The exit is also only signaled clearly after reaching the top. A shorter average would generate signals faster – but also more false signals. Especially in volatile sideways phases, short moving averages cost a lot of money.
The optimization of this conflict of objectives is the subject of countless trading systems that are based on moving averages. In addition to filters, other average values are used (the average is then weighted linearly or exponentially, for example).