Introduction Hello community, here I applied the Inverse Fisher Transform, Ehlers dominant cycle determination and smoothing methods on a simple Rate of Change (ROC) indicator You have a lot of options to adjust the indicator.
Usage The rate of change is most often used to measure the change in a security's price over time. That's why it is a momentum indicator.
When it is positive, prices are accelerating upward; when negative, downward.
It is useable on every timeframe and could be a potential filter for you your trading system.
IMO it could help you to confirm entries or find exits (e.g. you have a long open, roc goes negative, you exit). If you use a trend-following strategy, you could maybe look out for red zones in an in uptrend or green zones in a downtrend to confirm your entry on a pullback.
Decreased lag of Hann Window smoothing by applying it to the price instead of the indicator itself. Increased linewidth and decreased transparency on background colors
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Updated plot
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Just to update the chart
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Added divergence detection
Removed wrong Kalman filter
Reworked smoothing system -> Now you can apply the smoothing methods on the source price (which is close[1]) or on the indicator itself depending on what your goal is with the smoothing.
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Applied the IFT after the smoothing to stick to the scale of -1 to 1
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Removed 34 as max length of Homodyne Discriminator