Market phenomena - page 24
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it's not that simple. I remind you of Alexei's post:
Avals, yes you take your time to draw conclusions...
Farnsworth, ok I won't :), but why do you wonder:
"Once again I'll point out, I don't know about colleagues, but when taken within the RMS increments gave a trend - I was greatly surprised. "
If you have such bandwidths in the matrix from the first post? Or is it no longer about that matrix?
Farnsworth, ok I won't :), but why are you surprised:
"Once again I will point out, I don't know about colleagues, but when taken within the RMS increments gave a trend - I was greatly surprised. "
If you have such bandwidths in the matrix from the first post? Or is it no longer about that matrix?
No it's not, it's different methods. The purpose I wrote about, - to find models and stochastic logic for transition between states with practical applications. "I'm iterating", and, hell, I haven't even started from the beginning :o) And as a basis - to find these "patterns"
On a previous post later I added: "what Alexey wrote - I confirm it completely". That's right.
Where do patterns/dependencies come from? They take a timeframe and put some of the increments in one pile and some in another depending on the value. And a few points or a shift of reference point may change the composition of these "processes". Where does the trading logic come from with such a breakdown? We will refer 20 points on m15 to omega, but if we had 21 points it would be different - it's alpha :) Where did such a returnee division matrix come from in the first place? How could it have turned out differently than even a random walk, as the matrix shows that one "process" will get more negative returnees and the other more positive? Of course, one process will get more negative returnees and the other will get more positive returnees?
The arguments are understandable, but here I see one topic for "thinking about". There is one process on the market, authored by regulators, which in principle could be tried to isolate in this way, or rather in a similar but more complex way. It is more characteristic of the nais than of the exchanger. There is little doubt that it is definitely there, it is sometimes very clearly visible, it is legitimate and it is described by the participants themselves. That's what I think.
But yes, 20 or 21 pips is not important.
The correlation for these processes has not yet been looked at. Moreover, I haven't looked at it on purpose. The main reason is that I "picked out" from the series only those counts that fell under the classification. The appearing holes were simply ignored. That is, according to the original conception, there is a deterministic trend, with a more complex structure than just a line, but it is deterministic. And this "trend" process is interrupted (exactly interrupted or destroyed) by another, more complex "killer process" (tails, ears, whatever sticks out). It is important to note that it is not the trend that is mixed with the noise, but rather two, very complex processes competing, one creative, the other destructive.
To use? - Almost easy :o) You can predict the "carrying process" accurately enough (within reasonable limits), and then, for example, using the Monte Carlo method, estimate future destruction, as well as estimate the most probable levels of price accumulation after the "crash".
And I think that in this endless process of trend creation and destruction there must be these very "stochastic patterns". Coming at them from different angles, and here's another approach. But the philosophy changes a bit, it turns out that there is a trend, it is predetermined by the very nature of the company, society, country, whatever. It is one, i.e. there are no bulls and bears. But there are environmental conditions in which this trend cannot exist in ideal conditions, and society itself can destroy it (the trend). But this is all lyrics, don't pay attention.
In principle all is correct, it is not the only way of filtering.
PS IMPORTANT: I couldn't filter out this process in terms of DSP, I couldn't do it at all!!! But this primitive method gave results. I think this should work well here, anything involving the prefix "multi".
Next Sunday I'll try to evaluate the different characteristics of these particular processes.
The CLC, in my mind, is not capable of showing anything there. It is too far from the people, i.e. the trading crowd.
I don't know, I don't like the concept of existence of two processes - "trend" and "killer". I have not managed to find its confirmation. Probably I searched badly.
The arguments are understandable, but here I see one topic for "thinking about". There is one process on the market, authored by regulators, which in principle could be tried to isolate in this way, or rather in a similar but more complex way. It is more characteristic of the nais than of the exchanger. There is little doubt that it is definitely there, it is sometimes very clearly visible, it is legitimate and it is described by the participants themselves. That's what I think.
But yes, 20 or 21 pips is not important.
You do not understand the argument. It has to be seen in terms of a stochastic system model with a random structure. This logic does not imply such conclusions "20 pips on m15 would be considered an omega, but if it were 21", no, no, this is a completely, completely different system and a different logic of building a model of the process and trading accordingly . Apparently, you need to have an idea of the theory itself, or to elaborate on it. I will try to correct it (if possible).
And the fact that not everything is clear (and from a trading point of view) is not so important at the moment.
Gradually approaching the models, and the phenomenon. So, stochastic models with a random structure presuppose, of course, the models themselves and a description of the transition between them (i.e. some probabilistic logic of intercepting one process by another, which these models generate). We can say that BP is described by 100 differential equations of Ito, and then there is a question of identification of models, - what functions, what biases, what diffusion coefficients for each, what is the initial probability vector of states of systems, in general - is not a trivial task.
So I've actually invented a transformation that decomposes any initial time series into two subprocesses. I haven't seen anything similar earlier, but maybe it's one of particular cases of canonical representation of random functions. Who knows, I'm not a professional mathematician. The gist of it is "sifting" through a grid. But never mind, I won't lay out the mathematics yet, I have to deal with the ideas and the concept. What's important is that after transformation we get only two processes, these processes are linear but have more complicated structure.
Random process. The process is matched in its characteristics to the increments of M15
After the transformation we obtain:
For a random process, the coefficients b(alpha) and b(omega) in the models, will be modulo the same, the difference in lengths respectively will show the predominance of one or the other dynamics, and for a random process the internal structure of the separated processes will be close to the line. There are still some theoretical issues and development of better algorithms, but that is a separate story.
By the way, another indirect (in the sense not yet strictly proven) assertion is that the quoted process is not random, since the decomposition characteristics are different from those of random BPs (well ... not strictly all there yet).
So, there remains the question of transition probabilities between states (processes). If these transitions can be considered "Markovian", then by Kolmogorov-Chempen formula it will be possible to obtain probabilities of states of the system at a given horizon in the future.
About the coolest phenomenon (this isn't just a branch of ready-made phenomena, as if research is allowed or not?). So, here I am sure there are "stochastic patterns" (TA has nothing to do with it), a very strong certainty, I hope they will be confirmed. It is possible that I am wrong and then, I already feel, it is scary to imagine, paukas after all an invoice for the lost profit will be submitted for payment.
I wanted to insert a few words.
I find the obtained result very curious and unexpected. (If I understood correctly that the red line shows the cumulative BP of the summed differences not exceeding the + - lambda?) Even very unexpected. The second thing that surprised me was the difference with the price data - very obvious. Although, I would ask what kind of distribution did you specify for the synthetic random numbers?
The second thing I wanted to say is about the hypotheses of the author of this thread - Markovian transitions. I think some non-randomness can be found (if we stick to the model with separation of increments inside the lambda and outside the lambda), as there is some autocorrelation of increments (taken modulo). But if you think about the originally proposed model with troughs over the whole range of values, I don't know, you have to try it.
Once again, I don't know about my colleagues, but when I was surprised by the trend within the RMS - I was very surprised.
"Inertia is the phenomenon of a body maintaining its speed of motion (both in magnitude and direction) when no forces are acting on the body" :)
Why are you actually surprised that there is a global long-term trend?
Where did such a matrix of division of returnees come from in the first place? How could it have turned out differently than even the random walk, since the matrix shows that one "process" will receive more negative returnees, while the other will receive more positive ones? Of course, one process will get more negative returnees and the other will get more positive returnees?
Candid:
..... If they are available.
Once again, I don't know about colleagues, but when taken within the RMS of the increment yielded a trend - I was very surprised.
"Inertia is the phenomenon of a body preserving its velocity (both in magnitude and direction) when no forces are acting on the body" :)
Why are you actually surprised by the existence of a global long-term trend?
Why not assume that such a matrix is not the cause but the consequence of two such processes. If they are present, of course.What is there to assume? Everywhere you look, except at the obvious.
Is that what you're doing here? Sounds delusional to me.