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Cross Smoother Filter

Just another attempt to smooth things up! But in a lot easier way.
If you are thinking about complicated math formulas that may be happening under this curve, I have to say you are absolutely wrong.

Its all done by splitting the given length in two parts for a moving average and making it two moving averages with half length!
But applying a moving average over another will cover 1 less bar than sum of their periods, so one bar should be added to one of them to cover the required number of bars.

Well the result is not as simple as the code...
Here is John Ehler's Super Smoother Filter (white) and Cross Smoother Filter using WMA.
syot kilat
They are not exactly the same, but very similar.

The Filter relys on the used moving average type and its characteristics to smooth the data.
However any moving average can easily fit in the formula, but common moving averages seem to have good result. Specially WMA and EMA.

WMA (blue) and CSF using WMA (orange)
syot kilat

EMA (blue) and CSF using EMA (orange)
syot kilat

SMA (green) and CSF using SMA (orange)
syot kilat

Logarithmic Moving Average is also included. You can try it as well :)
Moving AveragessmootherTrend Analysis

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