Moving Average (Exponential Bars) [EMA]

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The Moving Average (Exponential Bars) function returns the moving average of a field over a given period of time, with emphasis given to more recent values. Parameters ------------------ Data          The data to use in the average. This is typically a field in a data series or a calculated value. Period        The approximate number of bars of data to include in the average, including the current value.                   For example, a period of 3 includes the current value and, most significantly, the two previous values. Function Value ------------------------ An exponential moving average is calculated by combining a certain percentage of the current value with an inverse percentage of the previous value of the exponential moving average. For example, if 25% weight is being given to the current value, 25% of the current value is added to 75% of the previous moving average to get the current moving average. The period is used to determine the relative weight which previous values should be given. The formula 2/(period+1) is used to determine the percentage. For example, a period of 7 would cause 25% (2/(7+1)) of the current value and 75% of the previous exponential moving average value to be used. Note: All previous values are used to make up a current exponential moving average, even values from before the period. The period is used as a rough estimate of how long new values will remain significant in the calculation. The value at the beginning of a data series is considered to be zero. Therefore, you may want to ignore values before the period has completed. Usage ----------- Moving averages are useful for smoothing noisy raw data, such as daily prices. Price data can vary greatly from day-to-day, obscuring whether the price is going up or down over time. By looking at the moving average of the price, a more general picture of the underlying trends can be seen. Since moving averages can be used to see trends, they can also be used to see whether data is bucking the trend. Entry/exit systems often compare data to a moving average to determine whether it is supporting a trend or starting a new one. See the sample entry/exit systems for an example of using a Moving Average in an entry/exit system.