Dependency statistics in quotes (information theory, correlation and other feature selection methods) - page 18
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NEs can be distributed differently and be dependent or independent. If 2 CVs are independent, then the conditional distributions of independent random variables are equal to their unconditional distributions. In the case of one SV, the distribution is independent of the previous SV values
I am simply asking you to construct at least one of Alexei's matrices. I couldn't - until I put forward the distribution hypothesis.
Alexei said - whatever it is.
That's where I got stuck.
;)
you have returns (and Alexei claims that they are almost Laplacian in time distribution).
Now you test hypotheses about their independence from previous values. I care about that.
If the pattern of distribution of returns is uniform, correct. Otherwise it's not. that's what I'm talking about.
And the fact that volatility is sensitive to equity-volatility is a fact. but the reason is different.
And trying to ration it - would blur the obvious cut.
The further out (over sigma) - the more independence...
;)
So, in order and step by step please. There is one hypothesis, and it is the hypothesis of dependence, not independence. Why hypothesis?
What is meant by the uniformity of the model(which one?) and why is the claim of model independence of approach stubbornly ignored?
The reason for the discussed volatility behaviour is the sessionalism of the market and do not make a mystery of it.
The rationing attempt is intended to exclude a very strong but apparently useless real effect for us
P.S. Oh, genius guess :), you call the second process the same process taken with a time shift? And do you doubt that it is the same process? So moving an observer to a neighbouring time zone radically changes the nature of the observed quotes?
here's a simple enough chi-square to test the independence hypothesis. The assumption of the rhapsodic distribution of NE is not made
it is made implicitly. it is uniform.
Take a pdf of any distribution - it won't be that easy.
So, in order and step by step please. There is one hypothesis, and it is a hypothesis of dependence, not independence. Why hypothesis?
What is meant by equilibrium model (which one?) and why is the claim of model independence of approach stubbornly ignored?
The reason for the discussed volatility behaviour is the sessionalism of the market and do not make a mystery of it.
The rationing attempt is intended to exclude a very strong but apparently useless real effect for us
P.S. Oh, genius guess :), you call the second process the same process taken with a time shift? And do you doubt that it is the same process? So moving an observer to a neighbouring time zone radically changes the nature of the observed quotes?
I'll refrain from commenting for now.
Just read the discussion.
There is time.
:)
it is made implicitly. it is uniform.
Take a pdf of any distribution - it won't be that easy.
As far as I have read the source - nowhere does it make any assumptions about the NE distribution.
Why delve into this topic? There is no practical output to be seen. Even if the criterion shows us that there is a dependence - what to do next? Except write a dissertation :)
As far as I have read the source - nowhere is any assumption made about the NE distribution.
Why delve into this subject? You can't see the practical implications. Even if the criterion shows us that there is a dependence - what to do next? Other than write a dissertation :)
I'm just stating the obvious.
If we use to estimate the probability (frequency) of an implausible distribution - conclusions about independence are far-fetched.
That's why chi-squared is more often used to reject plausible reasoning.
which is what we're seeing.
:)
if Alexei had calculated the chi-squared theoretical for Laplace - cicavo.
and as it is, he couldn't even answer on the assumption of which distribution of returns his calculations are about.
explain...
I will refrain from commenting for now.
Just read the discussion.
There's time.
:)
You don't need to comment, you need to try to answer my questions. I'll tell you a secret - they're designed so that trying to answer them you'll understand something).
I read the discussion, by the way, do you seriously want to discuss a 17 page mixture of flies and cutlets?
Am I even correct in guessing what you call the two processes?
if Alexei had calculated the chi-squared theoretical for Laplace - cicavo.
and as it is, he couldn't even answer on the assumption of which distribution of returns his calculations are about.
clarify...
I don't understand half the words in this thread at all, but even I realised that the distributions have nothing to do with it at all.
The distribution of a process that has dependencies between individual counts doesn't have to be uniform or normal. It is obvious.
Example: Pushkin's poems. If the text mentions the words 'oak' and 'chain', then by any chance there is 'cat' somewhere nearby. This relationship between words has nothing to do with the distribution of the word 'tom', or any other word, in the paragraphs.
Why delve into this topic? You can't see any practical output. Even if the criterion shows us that there is a dependence - what do we do next?
The next step is to look for it. There may be indirect indications. For example, daily periodicity pointed to volatility as the cause.
Somebody's motivation may be refreshed by this :)