Machine learning in trading: theory, models, practice and algo-trading - page 2557

 
Maxim Dmitrievsky #:

the sloping line is non-stationary, and it's all about time series.

stop talking nonsense, where did you weirdos come from again? :D it's only worth warming up the topic.

Sorry. Go on rocking like you've been doing for the last SEVEN years...

 
Maxim Dmitrievsky #:

then all is futile )

why?

it's just that we don't look for one correct cycle (sinusoid) which doesn't exist

but several simple cycles (sinusoids) the sum of which will create our complex non-sinusoidal cycle (complex from the word add)

 
Dmytryi Nazarchuk #:

Sorry. Keep kamlalaing like you have been doing for the last SEVEN years...

I didn't ask for advice.

 
Maxim Dmitrievsky #:

I didn't ask for advice.

This is not advice.

 
Dmytryi Nazarchuk #:

And this is not advice.

Opinion is not interesting either, your personality even less so

 
Maxim Dmitrievsky #:
Well there in the second part is interesting, in the end about time series and his experience with it. The rest is up to everyone
Non-stationarity is not as critical as the lack of regularity. If we assume that the time series is unpredictable at all, I'm afraid there is nothing more to be invented here.

At one time I took this course on intuition.

There are different kinds of non-stationarity. Only those that are algorithmically reducible to stationarity are available for study. For example, econometrics uses detrending and transition to differences. Another example would be HMM.

Regarding prices it is impossible (due to lack of data) to make a definite conclusion about the type of nonstationarity and whether there is (and what, if any) algorithm for the reduction to stationarity.

 
Aleksey Nikolayev #:

Alexei, do you have a good understanding of hmm?

 
Aleksey Nikolayev #:

At one time I took this course on intuition.

There are different kinds of non-stationarity. Only those that are algorithmically reducible to stationarity are available for study. For example, in econometrics, detrending and transition to differences are used. Another example would be HMM.

Regarding prices - in principle it is impossible (due to lack of data) to make a definite conclusion about the type of non-stationarity and whether there is (and what, if any) algorithm for reducing to stationarity.

Why do we need to detrend? It's like we need to look for trends. We should rather de-trend.)

 
mytarmailS #:

I couldn't have said it better.

Well done, but what to do?

Globally, I don't know. Locally - I try to choose predictors that are as unsteady as possible. From my observations, all derivatives of the zigzag may be based on the prices of one asset.

 
Maxim Dmitrievsky #:

Then everything is fuzzy ) and it is clear that the quotes are non-stationary, and it is cycles we are looking for.

There seems to be some cyclicality in the sense of repeatability (but not periodicity). Sometimes there seems to be some inertia. This gives me some hope.)

Reason: