Moving Average (Weighted) [WMA]

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The Moving Average (Weighted) 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 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. Function Value ------------------------ The weighted moving average is calculated by averaging together the previous values over the given period, including the current value. These values are weighted linearly, with the oldest value receiving a weight of 1, the next value receiving a weight of 2, and so on up to the current value, which receives a weight equal to the period. The moving average at the beginning of a data series is not defined until there are enough values to fill the given period. Note: For more exagerated weighting on the current values, you may want to use an exponential moving average. You could also average two or more weighted moving averages together. 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.