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Yes, the sample size is different for each pair. Exactly. This is very important. Even Vizard_, in my opinion, does not fully grasp this point. And the answer is simple - the wave function of each pair is different, so to say, named.
Why so many questions? Comrade takes the sampling period of the price - 1s. Then all sorts of statistics. If anything has not changed during this time)). Already the author has become Wizard.))
What I really don't understand is the exponential time. What for? There are standard approaches with weighting factors that reduce the weight in the statistics of old data.
With exponential time (counts) we just throw out some of the info between counts, and as the window moves, that info starts to flicker - counts appear, disappear, and reappear, etc.
Once again - without Wizard I would have come to these charts much later. Although I would have. He noticed it and just helped out a bit. Apparently, he got tired of waiting.
And here's the thing - this algorithm is already good and we'll see the results. If the results are positive, I'll stay on this algorithm forever. But, once again - Feynman has explicitly argued that on the basis of knowledge of the wave function and its amplitude one can and should predict the motion of particles. And Wizard is sitting on neural networks, it's just obvious. So, if something is suddenly wrong, we will smoothly move to the next branch and start to teach everyone there and to interfere between phrases :)))))
So, similar to the picture above, can you post a list of your pairs with sample volumes for each of them?
Why so many questions? Comrade takes the sampling period of the price - 1s. Then all sorts of statistics. If anything has not changed during this time)). Already the author has become Wizard.))
What I really don't understand is the exponential time. What for? There are standard approaches with weighting factors that reduce the weight in the statistics of old data.
With exponential time (counts) we just throw out some of the info between counts, and as the window moves, that info starts to flicker - counts appear, disappear, and reappear, etc.
The only thing the author is right about is that nobody does that).
I suspect that in order to get the inverse of the exponent and then a linear relationship between the normal and the resulting distribution
The problem is that by adding randomness where there was none before, we are increasing entropy, not decreasing it.
If a deterministic method were proposed, there would be no problem.
There, the step of measurement depends on the past data according to a formula. Like in Kagi or Renko, but a bit more complicated.
Either from the accumulated volume, or from the accumulation of volume on a buy when the market is falling.
I hope the examples are clear. But a random sequence is overkill.
Sample volumes:
AUDCAD = 19600
AUDCHF = 14400
AUDJPY = 12100
AUDUSD = 14400
CADJPY = 16900
CHFJPY = 19600
EURAUD = 32400
EURCAD = 44100
EURCHF = 16900
EURGBP = 14400
EURJPY = 22500
EURUSD = 16900
Well, this is for processing an archive of 200,000 quotes, we need at least 1,000,000.
I wonder what is so special about EURCAD that it supposedly needs 3 times as much sampling)
All the crosses are similar in volatility and trendiness, there are differences, but not by times.
It smells like a fiction. Alexander, where did such a difference in calculations come from?
I wonder what is so special about EURCAD that it supposedly needs 3 times more sampling)
All the crosses are similar in volatility and trendiness, there are differences, but not by times.
It smells like a fiction. Alexander, where did such a difference in calculations come from?
Dear programmers, why is it that although I have a check everywhere when I open an order
but I still have 4 orders opened simultaneously on different pairs?
Is it because of this?
This parameter is the same for all EAs.
Trainees! Where are the reals? No kidding and no jokes...