Machine learning in trading: theory, models, practice and algo-trading - page 2272
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About the same. How to prepare the data for training.
Well go ahead! If you have any problems contact ...
I will add ))
Ideally, you should make the series stationary, find cycles on the spectrum, build a filter for these cycles.
How to make the series stationary? Correction for the average volatility by the time of day? Logarithm and filtering?
How do you build a spectrum? The deeper the history is, the stronger the noise is, the weaker the signal can be. But everything changes on the market. If we take a short time span, there is no guarantee that it is a cycle and not a random coincidence.
I showed you my statistics on the spectrum.
The entire multibillion-dollar market is full of nocturnals and scalpers, and you say ... some stationary filters, I'm not strong. We don't need a perpetual motion machine, let it change, but not immediately
https://github.com/balzer82/FFT-Python
there is more of this, but I don't understand what he did
https://github.com/snazrul1/PyRevolution/blob/master/Puzzles/DSP_For_Stock_Prices.ipynb
Well, go ahead! If you have any problems, ask ...
I will add ))
Regarding Fourier, the way I see it is this. First some decomposition is done, e.g. stl
then loops are searched through bpf
then the loops are wrapped with trade logic. (including MO) It does not look complicated.
Why are you picking on Fourier?
Why are you picking on Fourier?
You do it, don't ask too much.
i'll do it soon
Uh... what's with the Fourier when you can use autocorrelation?
Uh... why do we need a Fourier when we can use autocorrelation?
where here?
where in here?
how did you look for cycles via PCA or Fourier?
I started doing so much at a time that I got confused... but it's temporary )how did you look for cycles through PCA or Fourier?
what cycles? when? in prices?
what cycles? when? in prices?
where are you at all? in prices, yes ) above it says