Se tens o Metastock podes facilmente ver, tens as médias móveis simples, exponênciais, triangulares, etc:
Simples:
A simple, or arithmetic, moving average is calculated by adding the closing price of the security for a number of time periods (e.g., 12 days) and then dividing this total by the number of time periods. The result is the average price of the security over the time period.
For example, to calculate a 21-day moving average of IBM: First, we would add up IBM's closing prices for the preceding 21 days. Next, we would divide that sum by 21; this would give us the average price of IBM over the preceding 21 days. We would plot this average price on the chart. The following day (tomorrow) we would do the same calculations: add up the previous 21 days' closing prices, divide by 21, and plot the resulting figure on the chart.
Exponencial:
An exponential (or exponentially weighted) moving average is calculated by applying a percentage of today's closing price to yesterday's moving average value.
For example, to calculate a 9% exponential moving average of IBM: First, we would take today's closing price and multiply it by 9%. We would then add this product to the value of yesterday's moving average multiplied by 91% (100% - 9% = 91%).
Because most investors feel more comfortable working with time periods rather than with percentages, MetaStock converts days into an exponential percentage. For example, if a 21-day exponential moving average is requested, a 9% moving average is calculated.
The formula for converting days to exponential percentages is as follows:
For example, to calculate a 10-day exponential moving average, you would use 0.18:
To convert an exponential percentage into time periods, you would use the following formula:
Using our previous example, we can check to see that a 0.18 exponential moving average is actually a 10-day average.
The method used to calculate an exponential moving average puts more weight toward recent data and less weight toward past data than does the simple moving average method. This method is often called exponentially weighted.
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