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Moving averages are used to smooth short-term swings to get a better indication of the price trend. Averages are trend-following indicators. A moving average of daily prices is the average price of a share over a chosen period, displayed day by day.

- For calculating the average, you have to choose a time period.

- The choice of a time period is always a reflection upon, more or less lag in relation to price compared to a greater or smaller smoothing of the price data.

Price averages are used as trend following indicators and mainly as a reference for price support and resistance. In general averages are present in all kind of formulas to smooth data.

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A simple moving average is calculated by adding all prices within the chosen time period, divided by that time period. This way, each data value has the same weight in the average result.

Figure 4.35: Simple, exponential and weighted moving average.

The thick, black curve in the chart of figure 4.35 is a 20-day simple moving average.

An exponential moving average gives more weight, percentage wise, to the individual prices in a range, based on the following formula:

EMA = (price * EMA %) + (previous EMA * (1 – EMA %))

Most investors do not feel comfortable with an expression related to percentage in the exponential moving average; rather, they feel better using a time period.

If you want know the percentage in which to work using a period, the next formula gives you the conversion:

A time period of three days corresponds to an exponential percentage of:

The thin, black curve in figure 4.35 is a 20-day exponential moving average.

A weighted moving average puts more weight on recent data and less weight on older data.

A weighted moving average is calculated by multiplying each data with a factor from day “1” till day “n” for the oldest to the most recent data; the result is divided by the total of all multiplying factors.

In a 10-day weighted moving average, there is 10 times more weight for the price today in proportion to the price 10 days ago. Likewise, the price of yesterday gets nine times more weight, and so on.

The thin, black dashed curve in figure 4.35 is a 20-day weighted moving average.

If we compare these three basic averages, we see that the simple average has the most smoothing, but generally also the biggest lag after price reversals.

The exponential average lies closer to the price and also will react faster to price swings. But shorter period corrections also are visible in this average because of a less smoothing effect.

Finally, the weighted average follows the price movement even more closely.

Determining which of these averages to use depends on your objective. If you want a trend indicator with better smoothing and only little reaction for shorter movements, the simple average is best.

If you want a smoothing where you can still see the short period swings, then either the exponential or weighted moving average is the better choice.

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