Time Series Moving Average
A Time Series Moving Average issimilar to a Simple Moving Average, except that values are derived from linearregression forecast values instead of raw values. A Moving Average is mostoften used to average values for a smoother representation of the underlyingprice or indicator. The time series moving average is calculated using linearregression techniques. Rather than plotting a straight linear regression line,a time series moving average plots the last point of the line. The MovingAverage (Time Series) function returns the moving average of a field over agiven period of time based on linear regression.
The time series moving average iscalculated by fitting a linear regression line over the values for the givenperiod, and then determining the current value for that line. A linear regressionline is a straight line, which is as close to all of the given values aspossible.
Moving averages are useful forsmoothing noisy raw data. By looking at the moving average of the price, a moregeneral picture of the underlying trends can be seen. Since moving averages canbe used to see trends, they can also be used to see whether data is bucking thetrend. Entry/exit systems often compare data to a moving average to determinewhether it is supporting a trend or starting a new one.