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Marius wrote:Hi Nikola,do you really want to know how it is implemented, or do you want to know how to use it? For the latter, you should install the Series Extension and have a look at the operator Moving Average. Basically this is also true for the implementation details, you can download the code of the series extension and look at the implementation of the operator.Best,Marius
The Triangular Moving Average is an average that is weighted with weights that rise from the most recent sample towards the farthest sample. So in effect the weighting function is a triangle that moves as the moving average moves. The triangle is wide k units and its height is 2/k units so that the area of this triangle is 1. This gives the last historical values a higher weight and to old values a lower weight.The Exponential Moving Average is a weighted average whose weights are exponentially decreasing from more recent historical samples to older historical values. MA(t) = α X(t) + (1-α) MA(t-1)where α is the smoothing factor. To compute an α factor that is roughly equivalent to the simple moving average window we can use the simple formula: α = 2 / (k + 1) where k is the window length.