You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
That's not an answer, it's an excuse like "get lost, nasty: even a fool knows how to do it, and you're picking on me".
OK, let's go the other way, if you're too lazy to write an algorithm here. Name one statistically significant sine wave on weeks.
I don't have it, I don't have the packet with me. I would do the following:
1. Price()=Sum_i a_i*sin_i() - normal Fourier.
2. Price()=Regression(sin_1,sin_2, ....) - take several sinusoids and run the package. The mathematical package will show the statistical significance of the variable, i.e. the sine wave. The significance criterion that is used is specified in the package.
If you are talking about the present, how can you know which figure is coming? For example, three waves could be a ZigZag figure and part in a momentum figure or a flat correction could be part of the terminal. If you only have three waves, then you have no figure, only a guess (when you add future variants it will start cutting off) and also the characteristic of the figure (is it impulse or not, i.e. is there :5 in structural notations).
In the past, the figures do not overlap.
I cannot know which one is formed, but I can look into the past to see which one is there right now. Suppose now there is some figure of five rays, two more rays appear, and a new figure of 5 rays is formed - that's the intersection.
1. It will turn out that these very Fourier... - It has already been discussed so much that there is no stationarity there and Fourier is generally not applicable, and instead of a normal expansion we get scientific nonsense - I don't want to remember.
2. Cycles are something periodic, with phase and amplitude. And as I understand it, it has a constant phase and a constant amplitude. I would love to see such a thing on the market - it's a grail. No, a grail! That's right.
A crisis every 17 years is not a grail? The same thing happens every 17 years for stock markets (always) and currencies (the last 2 times, there were no free-floating rates before).
A crisis every 17 years is not a grail. Every 17 years the same thing happens for stock markets and currencies (the last 2 times).
You invest $100 and wait 17 years to earn $200....))))
1.Take a weekly chart, decompose it into a Fourier series and see that the price is the sum of several statistically significant sinusoids.
:) Why would you need to decompose a Fourier series to see sinusoids? A Fourier series is by definition the sum of sinusoids, obviously when decomposed into a Fourier series there will be sinusoids.
I can't know which one is forming, but I can look back in time and see which one is there right now. Let's say there is some figure of five rays now, two more rays appear, and a new figure of five rays is formed - that's the intersection.
There is no such thing. Neely introduces a limit on the ZigZag.
Is a crisis every 17 years not a grail? The same thing has happened every 17 years for stock markets (always) and currencies (the last 2 times, no free rates before).
1. I am writing you that Fourier is not applicable, due to the non-stationarity of the series - this needs to be pointed out.
2. Let's look at the prehistory of crises by year. What do you think of the current crisis? The crisis of 2008 or 2009 or 2010? So what happened in 1990-1993? Where did the 1998 crisis go? It was not only in Russia. How to deal with it, 10 years is not 17.
:) Why would you decompose a Fourier series to see sinusoids. Fourier series by definition is the sum of sinusoids, obviously when decomposed into a Fourier series there will be sinusoids.
Sinusoids, then, are infinitely many, which means they are no longer sinusoids ))).
There is no such thing. Neely imposes a limit on the ZigZag.
Aha! Neely says so be it!
Sinusoids are infinitely many, which means they are no longer sinusoids ))).
It's up to you to decide how many sinusoids you will have when decomposed into a Fourier series.