Machine learning in trading: theory, models, practice and algo-trading - page 1591
You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
will not work for many reasons, it's been researched for a long time and it's not even the matter of ticks filtering by the DC server
here is what i know where to look forhttps://www.mql5.com/ru/forum/102066/page9#comment_2968124 in this picture where the arrow is an ejection
these ticks will always be, this is how the market works - why they occur is another question
And if you follow your assumption about the jumps in ticks, you will consider these spikes, but these ticks just do not form the direction of further movement, at most they may occur on the high/low of a bar
i couldn't find any screenshots of the tick indicator from Prival, it has a very good way to display these spikes - so that you don't have to guess where the tick is coming from, one of the variants is that MM often mixes asc/bid with a time lag in the quote flow, but this is a real quote! )))
There is no such assumption. There is an obvious assumption about the multiplicity of the tick jump. Perhaps you have confused discreteness with binarity?
I think that even if both will float in not wide limits, it is also not a big deal
In theory, it is important to have more matrix expectation and 2-3 clusters are enough (positive/negative + neutral cluster with zero, which is useless)
in practice, there may be more, so that they are more GaussianGentlemen, could you please suggest the most grail neuron for flyleaf?
I broke the history into sections, and now I need to pull the neuron up here:
As you can see, there's really no correlation between the pairs.
Pair trading sucks.
It's already in Bomb #2 :)
but it wasn't :-)
The tempo_of_variations/duration/periodicity should produce a picture similar to a diffraction or spectrogram
The main question about seasonal fluctuations in the context of rates: how often and for how long a quote moves N points on K real time measurements and whether there are signs of a pattern there.
The real time is marked, because it and bars are different things
Gentlemen, please advise the most grail neuron for the fly.
I've broken it down into sections, and now I need to pull the neuron up here:
As you can see, there's really no correlation between the pairs.
Pairwise trading is bullshit.
What and how were the charts measured in one chart?
What and how were the graphs summarized in one chart measured?
I once wrote that the principle is the same as the visual evaluation.
In other words, when we look at the chart - how do we know if the price is falling or rising?
Translated it into code, got this result.
The first time I did it, I posted a screenshot in this thread.
That was over a year ago.
I have decided to add more than one pair to this indicator today.
I realized that the sauce is different - I've got a chart that is divided into segments, where it is practically impossible to lose, it is a flat, I should go further.
But it wasn't :-)
the tempo/variation/duration/periodicity should produce a picture similar to a diffraction or spectrogram
The main question about seasonal fluctuations in the context of rates: how often and for how long a quote moves N points on K real time measurements and whether there are signs of a pattern there.
about real time is noted, because it and bars are different things
too complicated... i'll have another Kindzmaraouli, then we'll talk)
There is no such assumption. There is an obvious assumption about the multiplicity of the tick jump. Perhaps you have confused discreteness with binarity?
No, I supplemented it with my picture and a link to an old discussion
these posts:
the real market distribution is only the tick distribution, and it's not normal at all.
For currencies even it is not real. More precisely, it is not real and it is not "normal" at all (not in terms of distributions either).
Because there is no center. There is no single source of ticks and no guarantee that they will reach the user. Not only that the "hypothetical tick stream" of a particular server is a product of aggregation of other servers, but this stream is thinned by the server and the terminal for technical reasons.
it's a different story. statistical characteristics of ticks depend on a particular DC, its peers and their software.
In Forex there is no point in trying to analyze ticks, it only makes sense to analyze ticks in relation to a specific exchange
SZZ: imho, the usefulness of real ticks only in the final testing of TS, but that's another story
because all MOs work with stationary series, starting from Kolmogorov, a brochure on predicting stationary series was thrown by Alexander
Returns are the first thing to be analyzed, the primary data.
You can also analyze the indicators. But there may be losses and delays if the indicator is based on MACs.
I think someone has tried. I have not.
But wouldn't 50-100-500 consecutive returnees describe any graphical and candlestick patterns?
That's the point, there can't be anything more nonstationary than quotes, i.e. returns. I don't quite understand how they become stationary to work with them.
But take candlestick patterns, for example, they are of course some sequence of returns, but if we reduce them to the analysis of the patterns themselves, we get rid of a lot of uncertainties, degrees of freedom and we reduce them to a discrete table distribution of no particular type. I found someone's attempts in this direction, I'm studying.
Or about the normal distribution - it is marginal with tending to infinity number of influencing factors and their independence. I wonder if anyone has done a mathematical modeling of the market as it is structured now by this principle -
We have a huge set of agents who at random intervals put random bids into the market (within certain limits, of course), will the distribution of returnees be normal in this case? You may say nonsense, but a lot would be clear from this simulation, probably some institute dabbled in it, I should look it up.
The statistics are just a tool. Should you scold a hammer for hitting your fingers?
Absolutely agree, but just sayings don't come out of nowhere, so it has long been noticed this property of statistics to distort facts depending on the interpretation. It's like - Evil is not in the gun, but in who pulls the trigger.
That's the thing, there can be nothing more unsteady than quotes, i.e. returns. I don't quite understand how they can become stationary in order to work with them.
But take candlestick patterns, for example, they are of course some sequence of returns, but if we reduce them to the analysis of the patterns themselves, then we get rid of a lot of uncertainties, degrees of freedom and we reduce them to a discrete table distribution of no particular type. I found someone's attempts in this direction, I'm studying.
Or about the normal distribution - it is marginal with tending to infinity number of influencing factors and their independence. I wonder if anyone has done a mathematical modeling of the market as it is structured now by this principle -
We have a huge set of agents who at random intervals put random bids into the market (within certain limits, of course), will the distribution of returnees be normal in this case? You may say nonsense, but a lot would be clear from this simulation, probably some institute dabbled in it, I'll have to look it up.
Absolutely agree, but just sayings don't come out of nowhere, so it has long been noticed this property of statistics - to distort facts depending on the interpretation. It's like - the evil is not in the gun, but in the one who pulls the trigger.