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NGBaltic

NG [Gaussian Filter Multi-Pole]

NGBaltic  
Moving Averages gaussian gauss
334
10
movingaverage gaussian gauss
When smoothing data there is always a trade-off between lag and removal of noise.
Gaussian filter has a consistently low lag and a very smooth curve.

This filter works for poles higher than the 4 (usual usage).
Mathematically maximum poles is 15 after which coefficients are too high to see any difference.

By tuning Lag and number of Poles you can achieve a very smooth MA with least lag possible.
It's just as good as 3rd gen moving averages and can be used as input feed for other indicators.
Open-source script

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