Machine learning in trading: theory, models, practice and algo-trading - page 2657
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Overlapping wavebreakers arean utterly disgusting sight.
Renate's right, if I understand him correctly.
Well, there is a rightness there only in the banal statement that there is no universal good solution for this problem.
To get rid of non-stationarity by constructing cleverly arranged signs is quite a normal idea, but not universal either, of course.
In my research I proceed from the standard assumption of piecewise stationarity, when the market has some stationary states between which it sometimes switches. Of course, it is not a universal approach either (non-stationarity may well be "floating").
Well, there is validity there except in the banal statement that there is no universally good solution to the problem.
To get rid of nonstationarity by constructing cleverly arranged signs is quite normal idea, but it is not universal, of course.
In my research I proceed from the standard assumption of piecewise stationarity, when the market has some stationary states between which it sometimes switches. Of course, it is not a universal approach either (non-stationarity may well be "floating").
The sadness of course is that it is not speed and acceleration)))))
Quite a normal approach to investigate. Stationary states are visible, modelled, transitions are also visible, but not modelled as stationary states. And floating non stationarity, it is still a complex substance, but noise always was and will be.
Well, there is validity there except in the banal assertion that there is no universally good solution to the problem at hand.
To get rid of nonstationarity by constructing cleverly arranged signs is quite a normal idea, but it is not universal, of course.
In my research I proceed from the standard assumption of piecewise stationarity, when the market has some stationary states between which it sometimes switches. Of course, it is not a universal approach either (non-stationarity may well be "floating").
I don't think the idea of piecewise stationarity is working.
Reducing the lag leads to an increase in the false positive error rate, it's always a question of a trade-off between the two.
HMM is not quite suitable for me, because switching is not quite uniform, there are stuck states or too frequent switching. It is easier to assume that the switching moments are deterministic (and unknown).
Enumeration, enumeration... trigonometry, logarithms, moments of distributions, time-features... you can't guess what it should look like any other way
What are you talking about?)
about looking for signs
about looking for signs
there's nothing on the graph but increments and time. And derivatives don't give anything new. It is strange that clustering is stalled.
there's nothing on the graph but increments and time. And derivatives don't give anything new. It's strange that clustering fails.