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As for wavelets, this is quite a scam. If we take any function, decompose it into a Fourier series and reconstruct it relative to the zero harmonic level, it falls under the definition of a wavelet, because the integral of the function histogram at this very level is 0. The wavelet operators only invent that their "inventions" supposedly contain more information than the Fourier transform. Fucking lobbyists are lying.
Astonishing knowledge of the subject - I mean, wavelet analysis. Actually, in wavelet analysis.
decomposition is not in a basis of infinite-time sinusoids, but in a basis of short
"wavelets. This makes it possible to analyze non-stationary
series. Information display in wavelet analysis is made in contrast to the Fourier analysis,
on a two-dimensional plane. Due to these features, wavelet analysis has received the widest
It is used in a huge number of areas - seismic, radar, compression
and information security, medicine, etc. By applying wavelet analysis to the input signal, the learning curve of neural networks will increase by orders of magnitude.
It would be interesting to know how a connoisseur of arbitrage, analytical geometry, neural networks and Fourier analysis, can build a Fourier decomposition and then extrapolate the simplest almost
table analytic function y=A0*sin(x**2) given on the interval say from 0 to
10*pi. Within wavelet analysis, this is not difficult to do.
Actually from a statistical point of view - the market is almost random, with little trend component. But there is enough of that...
As far as wavelets are concerned, this is quite a scam. If we take any function, decompose it into a Fourier series and restore it, it falls under the definition of a wavelet with respect to the zero harmonic level, since the integral of the function histogram at this level is 0. The wavelet operators only invent that their "inventions" supposedly contain more information than the Fourier transform. Fucking lobbyists are lying.
By applying wavelet analysis to the input signal, the learning speed of neural networks will increase by orders of magnitude.
Do you have results showing that the market is not random? I've done a lot of different analyses of quotes, then substituted random, and the difference was minimal. I don't know the methods of proving time series randomness, nor do I know if they even exist. In fact, I've never encountered evidence that any time series in nature is random (ant population, heartbeat, etc.), nor the reverse.
I didn't use Bernoulli's scheme, I compared it with a pseudo-random sequence obtained from the built-in Random function in MathCad. You can blame the function, but I'm sure there is no correlation between it and the time series of quotes. Let's be more specific, since you don't need the help of an oculist, show me where the differences are. Since you are so confident, why not back it up with explicit evidence.
You'd better read a maths book at your leisure. Maybe you'd find some familiar letters there. You're banging on your chest, like you've been researching quotes for randomness. I thought that you must have really examined the probability distributions in quotes, calculated all sorts of dispersions and derivative functions, defended several dissertations and published several scientific works. But as a result it turns out that getch is an ordinary amateur, who has signed up for his own incompetence, or, to put it simply, lameness.