Best described by Ehlers himself:
John Ehlers:
- Take EMA of price (better, a 3 Pole filter).
- Take the difference (delta) between Price and its EMA.
- Take an EMA of delta (or a 3 Pole filter):
- Smoothing will help reduce whipsaws.
- Ideally, smoothing introduces no major trend mode lag because delta is detrended.
- Add the smoothed delta to EMA for a zero lag curve.
- Add 2*(smoothed delta) to EMA for a smoother predictive line.
If Ehlers take EMA, delta of EMA and EMA smoothing ,where does Kalman fit into?
cemal:
Best described by Ehlers himself:
If Ehlers take EMA, delta of EMA and EMA smoothing ,where does Kalman fit into?
:)
Frankly, my personal opinion is that is what Ehlers does all the time. But since he is well known in the TA, I left it as is (including the name)
Interesting why it's called Kalman filter, it looks like one of Ehlers low pass filters, Kalman filter looks completely different. Kalman needs 2 phases predict and update, and here is just smoothing of ema's and introducing more lag over lag with huge overshoot. When prices going down this filter is going up and vice versa :) https://puu.sh/zBI7f/436ae34c1e.png
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Nonlinear Kalman filter:
One more from the creations of John Ehlers.
Best described by Ehlers himself:
John Ehlers:
Author: Mladen Rakic