From theory to practice - page 256
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Alexander, how many values did you take for the sample to understand that the distribution is logarithmic?
About 200,000 ticks.
This time the error is irrelevant. All that matters is that these intervals are not initially uniform or exponential.
The flow of events is clearly not random! This once again shows the non-marking nature of processes in the market.
I repeat - we do not have a developed mathematical apparatus for describing non-markovian processes, that's why most traders get confused, invent more and more new ways to fight the market, etc.
I, on the other hand, do it simply - I forcefully read the quotes through the exponent.
That gives me the right to use the equations of diffusion, where, by the way, the time root that you love appears, that's what I'm talking about.
Sincerely,
Alexander_K2
"As we noted earlier, the flux intensity is in a sense a mathematical expectation of the number of events per unit time (the inverse of it indicates the average time between events). The second quantity characterizing how big is the spread in time of events' arrival relatively to the mathematical expectation is dispersion.
Suppose events in a stream follow exactly one after another every 12 minutes without deviations. The intensity of this flow would be 5 events per hour. But if events occur randomly, e.g. 12 ± 2 minutes, they will also average 5 events per hour. For example, if 1000 events occur in 200 hours, the intensity value of 1000/200 = 5 events per hour. Therefore the streams cannot be distinguished from each other by this characteristic. But obviously the second stream will be more random than the first one. All the more so if the events in the stream follow each other for 12 ± 10 minutes."
The main thing here is to understand, if we have a random stream as input, why do we need to make it random again, by reading between exponential time intervals?
About 200,000 ticks.
Unfortunately, I don't think this number is sufficient for a good analysis.
A random variable with a Cauchy distribution is a standard example of a distribution that has no expectation and no variance.
https://ru.wikipedia.org/wiki/%D0%A0%D0%B0%D1%81%D0%BF%D1%80%D0%B5%D0%B4%D0%B5%D0%BB%D0%B5%D0%BD%D0%B8%D0%B5_%D0%9A%D0%BE%D1%88%D0%B8
Fortunately, market price series are certainly not Cauchy distributions.
Yes, that's about right. Basically a normal bollinger, opening on a strong deflection, on a return to the middle. It's just that A_K2 has implemented it in a very convoluted way, pulling all his knowledge of physics out of his ears :)
By how much does the expectation he calculated there differ from the one that can be calculated directly from the market data? Their values should be dumped into the log for each trade. Is the RMS much different? The levelsbehind which it goes back to the average are not calculable without converting to its space? How doesthe number of trades and percentage of profitable ones change if these levels are placed further/closer to M?
Then you and the author simply do not have the answers.
There is no time, "get your pockets ready". Right?
I gave you the answer concerning the passing of signals to the robot, because I remember how A_K2 wrote about it. On the details of calculations in the model, I'd rather let the author answer. I personally am not interested in the answers. My pockets have long been fine, I read the thread out of boredom).
If I understand correctly, the author works in the price space, and before he deducted the trend from the price as a muving, but it seems not anymore.
How profitability changes when varying levels - well it's necessary to code the whole algorithm in MT and run it on historical data, we're all waiting for those tests from the 1st page of this thread))) The author either doesn't want or cannot make it in MT, or he is too busy sewing sacks for money).
Whether the author doesn't want to, or can't, or is too busy sewing money bags in MT)
:)))))))))) Being, in fact, an ancient old man, it's the cash that I have a great love and respect for. Where else to keep it but in bags?
Yesterday I started reading the thread myself from the beginning and realised that, yes, it is almost impossible to understand what we are talking about here.
I am too lazy to write an article - it would require a lot of work, rigorous formulas and proofs.
I offered to arrange for the model in VisSim to be sent to those who wanted it on request. Very few people contacted me. Either they are shy, or they consider it beneath their dignity to contact someone... I don't know. I can't put the model right here on the forum. It turns out that it will get both those who literally fought the market like lions, but something did not work out, and those who did nothing at all. This is not fair. I will still think about what to do.
Reminded me of something - Yusuf and his ph 18. Look at his signals... There were robots in the same article (18) and the losses were EXCEPT.
https://www.mql5.com/ru/code/10339
Ok. I'm going to go look for Yusuf. Gotta get into his healing market theory. Bulls and bears... And it's all described by hyperbolic cosecans. That's the stuff!
Oooh! Right on topic - haven't made it to here yet. still on page 246 of the branch... :-) and already on topic... my post.
Pyssy. arm yourself with patience - IMHO - you need an article. Note - Yusuf is a PhD!Oooh! Right on topic - haven't made it to here yet. still on page 246 of the branch... :-) and already on topic... my post.
pyssy. arm yourself with patience - IMHO - an article is needed. Note - Yusuf is a PhD!Roman, screw it, this reading, let Yusuf read and hyperbolic arctangens bend the time series. Move on to the model - I sent it to you in person.