Moving Average (Exponential Support) [EMA%%]

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The Moving Average (Exponential Support) function returns the moving average of a field, with emphasis given to more recent values. This version of the exponential moving average is used to support the common functionality between Moving Average (Exponential Bars) and Moving Average (Exponential Percent). Parameters ------------------ Data          The data to use in the average. This is typically a field in a data series or a calculated value. Percent      The amount of weight to give to the current value as a decimal percentage (0 .. 1).                   For example, a value of .25 uses 25% of the current value and 75% of the previous moving average. 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 value at the beginning of a data series is considered to be zero. Therefore, the initial values of this function may not be useful. 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.