OPEN-SOURCE SCRIPT
Laguerre Filter
This is the Laguerre Filter by John F. Ehlers. He published this filter design in the article Time Wrap - Without Space Travel.
This study open gamma and weight of each filter for to customize the filter design.
For example, setting gamma to 0.2, 0.7, 0.8,0.8 and weight 1,2,2,1, the curve is a very nice simulation to ALMZ(50),
setting gamma to 0.3, 0.3, 0.8, 0.9 and weight of 1,3,3,1 will produce a curve close to EMA(20),
basically, the Laguerre filter can simulate various type of moving averages.
The beauty of this Filter is it use only one data point and 3 filters output to reproduce various moving average, it is
an innovative approach to develop smoothing lines, and to avoid whipsaws on the price.
Each filter can be plotted for evaluation too.
Data of the first filter allows to input any bar, eg. 0 for current bar, 1 for one previous, for the purpose to evaluate forecasting idea.
Follows Ehlers' paper, this study allows to plot the weighted average line with all filter off.
This study open gamma and weight of each filter for to customize the filter design.
For example, setting gamma to 0.2, 0.7, 0.8,0.8 and weight 1,2,2,1, the curve is a very nice simulation to ALMZ(50),
setting gamma to 0.3, 0.3, 0.8, 0.9 and weight of 1,3,3,1 will produce a curve close to EMA(20),
basically, the Laguerre filter can simulate various type of moving averages.
The beauty of this Filter is it use only one data point and 3 filters output to reproduce various moving average, it is
an innovative approach to develop smoothing lines, and to avoid whipsaws on the price.
Each filter can be plotted for evaluation too.
Data of the first filter allows to input any bar, eg. 0 for current bar, 1 for one previous, for the purpose to evaluate forecasting idea.
Follows Ehlers' paper, this study allows to plot the weighted average line with all filter off.
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