Moving Average (Variable Length) [MAVL]

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The Moving Average (Variable Length) function returns the moving average of a field over a variable period of time. Parameters ------------------ Data          The data to use in the average. This is typically a field in a data series or a calculated value. Period        The 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 the two previous values. Maximum Period   The maximum value that Period can contain.                              Larger values require extra memory to be set aside for this function to be calculated. Note: An end point to the Period parameter can be simulated using the Lag function to obtain a previous value of this function. See the notes for the Lag function for more information. Function Value ------------------------ The moving average is calculated by averaging together the previous values over the given period, including the current value. The moving average at the beginning of a data series is not defined until there are enough values to fill the given period. If the period is greater than the maximum period or negative, the value is not defined. If the period contains a fractional number, only the integer portion will be used. Usage ----------- Variable length functions can be used in association with other calculations, such as "Bars Since" functions, to determine values since an event occurred. For example, the following formula would return the average of the High field since the highest high in the last ten bars: MAVL ( High, Add ( BarsSinceHigh ( High, 10 ) , 1 ) , 10) 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.