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If "pretty words" and "effects" are removed, there are many more interesting things. Physicists take particle coordinates and find out what kind of particles they are, a trader has a task to discover "his particle" from other coordinates. :-)
He reversed the equation and predicted the past based on future data, and predicted the future based on that past data.) So it turns out that the future directly affects the past.
Topikstarter: do you yourself have at least a basic knowledge of physics and mathematics? Question: what classical equation does the unsteady Erwin Schrödinger equation go into when the action quantum goes to zero?
It is funny how people discover that the equations of mechanics are covariant with respect to the time inversion operation. why wouldn't they be covariant? energetically, everything satisfies the principle of least action on the entire trajectory, which is the only one.
Not only, compare your results or compare together with this approach: https://www.mql5.com/ru/articles/250
Why is cheesy interpolation passed off as an "approach"?
Approaches were known to high school students in the 1970s USSR: see attachment. The part where a predictive filter is described. Predictive filter - sound?! :-0
About the "uncertainty principle".
As a result of much work on digital filter design, I've come to the following conclusion: uncertainty here links time and price.
Either you have no lag in time (an error on the time axis of zero), but do not know exactly the "true" price, which is different from the observed on the graph (there is an error on the price axis), or
You know exactly the true equilibrium price (no error on the price axis), but have a lag in determining it (there is an error on the time axis).
That's the trick. In short: Your filter is either not filtering or lagging. But there are nuances. A congenital condition: both filtering and not lagging is possible. But it takes above-average intelligence to break the seemingly immutable uncertainty ratio.
About the "uncertainty principle".
As a result of much work on digital filter design, I have come to the following conclusion: the uncertainty here relates time and price.
Either you have no lag in time (an error on the time axis of zero), but do not know exactly the "true" price, which is different from the observed on the graph (there is an error on the price axis), or
You know exactly the true equilibrium price (no error on the price axis), but have a lag in determining it (there is an error on the time axis).
That's the trick. In short: Your filter is either not filtering or lagging. But there are nuances. A congenital condition: both filtering and not lagging is possible. But it takes above-average intelligence to break the seemingly immutable uncertainty ratio.
Makes sense, I've read similar articles. Is it possible to break ? I haven't read about it before.
In the attached brochure for schoolchildren the filter looks into the future ("predicts") :-) but here it is only necessary not to lag behind...