OPEN-SOURCE SCRIPT
Retention-Acceleration Filter
Another Adaptive Filter
This indicator share the same structure as a classic adaptive filter using an exponential window with a smoothing constant.
However the smoothing constant used is different than any previously made (Kalman Gain, Efficiency ratio, Scaled Fractal Dimension Index),
here the smoothing constant is inspired by the different formulations for parameters resolution used in HPLC S. Said (J. High Resolution Chromatograpy &Chromatography Communciations, (1979) 193).
Different assumptions can be made which lead to different expressions for resolution in chromatographic parameters, therefore we will use highest's and lowest's in order to estimate an optimal smoothing constant based on if the market is trending or not. It can be complicated at first but the goal is to provide both smoothness at the right time and a fast estimation of the market center.
Handling Noise
In Red a Pure Sinewave. In White Sinewave + Noise. In Blue our filter of Period 3
Handling stationary signals is not the best thing to do since we need highest's and lowest's and for that non stationary signals with trend + cycle + noise are more suitable.
It is also possible to make it act faster by quiting the pow() function of AltK with sqrt(length) and smoothing the remaining constant.
This indicator share the same structure as a classic adaptive filter using an exponential window with a smoothing constant.
However the smoothing constant used is different than any previously made (Kalman Gain, Efficiency ratio, Scaled Fractal Dimension Index),
here the smoothing constant is inspired by the different formulations for parameters resolution used in HPLC S. Said (J. High Resolution Chromatograpy &Chromatography Communciations, (1979) 193).
Different assumptions can be made which lead to different expressions for resolution in chromatographic parameters, therefore we will use highest's and lowest's in order to estimate an optimal smoothing constant based on if the market is trending or not. It can be complicated at first but the goal is to provide both smoothness at the right time and a fast estimation of the market center.
Handling Noise
In Red a Pure Sinewave. In White Sinewave + Noise. In Blue our filter of Period 3
Handling stationary signals is not the best thing to do since we need highest's and lowest's and for that non stationary signals with trend + cycle + noise are more suitable.
It is also possible to make it act faster by quiting the pow() function of AltK with sqrt(length) and smoothing the remaining constant.
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