Dependency statistics in quotes (information theory, correlation and other feature selection methods) - page 36
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OK, peace and friendship and bubblegum.
Now to the discussion.
The initial signal is a quote, but we also roughen that down to timeframes, or try to squeeze something out of ticks (but that's the lot of the brave).
But the deterministic component in my book is not a trend. It is a predictive model, and its graph can be anything: straight or curved. And this model can also be non-linear and have an arbitrary level of complexity.
PS: I haven't heard what multipoint is :)
"The initial signal is a quote, but we also roughen that down to timeframes or try to squeeze something out of ticks (but that's the lot of the brave)".
Right. If the initial signal is a quote, then its coarsening is a bar. A timeframe is time. Do you translate the number into time somehow? With a tick it's clear - a one time quote. There is no question here.
"It's a predictive model, its chart can be anything: a straight line, a curve. And this model can also be non-linear and have an arbitrary level of complexity."
Deterministic component = predictive model. Understood.
Is it correct then from the definition: "Noise is usually the difference between the deterministic component of the signal and the original signal." implies that - a quote outside the predictive model is noise?
"PS: and what is multipoint, I haven't heard :)"
Well, here's an introduction to one of the representatives of that group ;)
Thank you.
Observing a down-trend:
MTS 60 min
Can you show on the chart where the noise is?
wrote that it is a relative concept. What is a useful signal for some models may be noise for others. And vice versa.
P.S. and not necessarily the difference between the quotes and the model's predicted values
wrote that it is a relative concept. What is a useful signal for some models may be noise for others. And vice versa.
OK, Vyacheslav, please show us the model, its useful signal and noise. How do you imagine it.
OK, Vyacheslav, please show me the model, its useful signal and noise. How do you envisage it.
Any model. Take the LR. The difference between it and the cotiers will be the noise in that model.
Any model. Take LR. The difference between it and the quotients would be the noise in that model.
I.e. anything that does not fit into the predictive model, anything that goes beyond it, is taken as noise within the analysis method applied. So?
Prove that there is no deterministic function in the quotes, or that there is and perfectly describes all data points, then yes, but otherwise it's an unsubstantiated claim.
What is a deterministic component? Is the sliff of a large pack of something in pieces over the course of, say, a week a deterministic component? I don't see how there can be a deterministic component to a quote at all.
The trend is a deterministic component of a quote.
I.e. anything that does not fit into the predictive model, anything that goes beyond it, is taken as noise within the analysis method applied. Right?
Yes, that's one noise. On the output so to speak))
Could be at the input of the model. But in general, it doesn't matter. Noise is something that is not intended by the model. Or rather the assumption is made that it can be ignored
Trend is a deterministic component of quotes
))) What is a trend? What is it expressed in? In what units? How does it compare to quotes? How does having a trend and quotes get "noise"? Go ahead.
))) What is a trend? What is it expressed in? In what units? How does it compare to quotes? How does having a trend and quotes get "noise"? Go for it.
Here we go - right from the front page of the thread and the patterns are concrete.