From theory to practice - page 151
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Who's that addressed to? A spherical horse in a vacuum?
YES! It's a memento to the forum members from me.
HOWEVER, Denis, from a tick archive I can get data with exponentially distributed time stamps????? It's hard to get evenly distributed - in my opinion, it's only when we take OPEN or CLOSE prices on the minutes.
It can be done. You just don't know the power of MQL5 :-)
In the meantime, I'm about to come up with the most ingenious idea.
This value - the sum of the increments - is the amplitude of the probabilities of the wave price function. In fact, this value is the solution to the Fokker-Planck equation with boundary conditions.
After statements like that, you should take your feet off the forum... ^)))))
Well then explain to memory what letters in these sentences mean ))))
I take it "sum of increments" is the quotation. What is the probability amplitude of the wave function is beyond comprehension at all.
Well then explain from memory what the letters in these sentences mean ))))
If you look carefully at the calculations inhttps://yadi.sk/d/Q26c4qoS3RbJRn, it uses the sum of the increments at a certain sample size. It forms a near perfect normal distribution relative to 0.
But, what is it? What is the physical meaning of it? It's not the mean, it's not the centre of mass, etc. etc. So what is it? Well, this is the amplitude of the price wave function and on its basis R. Feynman stated that one can predict the motion of a quantum particle (in our case - the price).
It is time to move to neural networks!
If you look carefully at the calculations inhttps://yadi.sk/d/Q26c4qoS3RbJRn, it uses the sum of the increments for a given sample size. It forms a near perfect normal distribution with respect to 0.
But, what is it? What is the physical meaning of it? It's not the mean, it's not the centre of mass, etc. etc. So what is it? Well, this is the amplitude of the price wave function and on its basis R. Feynman stated that one can predict the motion of a quantum particle (in our case - the price).
Time to move on to neural networks!
No shit, are you serious? And how do you do that?
you take the difference between quotes with a lag equal to a window, this difference forms a normal distribution, and how does this help the prediction?
No shit, are you serious? And how do you do that?
you take the difference between the quotes with a lag equal to a window, that difference forms a normal distribution, and how does that help the prediction?
I DON'T KNOW. I don't know. I'll have to ask Wizard. The algorithm I'm using is good enough for now. I'll look at the results and draw conclusions. I don't want to get into neural networks yet - I can get confused there (that's what networks are for!).
I DON'T KNOW. I don't know. I'll have to ask Wizard. For now, the algorithm I'm using is enough for me. I will look at the results and draw conclusions. I don't want to get into neural networks yet - I can get confused there (that's what networks are for!).
You will not get confused there, NS is a representation of one complex function as a superposition of many simple functions.
But in this case NS will not help you. Without knowing the essence of how NS works, you will start to fall into all sorts of tricks, such as fitting overtraining, etc.
You can not explain anything in a simple algorithm (can not explain read do not understand).
SZS NS is a universal approximator, that's all.I DON'T KNOW. I don't know. I'll have to ask Wizard. For now, the algorithm I'm using is enough for me. I will look at the results and draw conclusions. I don't want to get into neural networks yet - I can get confused there (that's what networks are for!).
Here is your indicator of the sum of increments for a period
First published in 2006, updated for language changes in 2016.
Add more STO to it and you get your calculation.
https://www.mql5.com/ru/code/9340
Here is your indicator of the amount of increments over the period
https://www.mql5.com/ru/code/9340
On the face of it, yes, it is very similar. I have to look at it more closely.
It doesn't look similar, it fits in essence.
There's a formula for the calculation in the description.
ZZ The only thing you have is the input series in exponential intervals.
HZZ But the exponential only folds the x-axis by an harmonic, since there is no averaging, it essentially does not change anything, in real time, the maxima will be at the same points.