a trading strategy based on Elliott Wave Theory - page 205
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Come on, Sergey. I got the general outlines, but the details don't matter.
Somehow this approach doesn't impress me.
You have misunderstood me. All I was trying to say is that the problems solved in this thread are somehow akin to quality control problems, which in turn are more "mathematically" formulated in the problem about decomposition. It is not about the process of organizing quality control, although there are interesting points there too. It was about the problem of determining the violation of a stochastic process (strange as it may seem, but, for example, the size of parts in production is a stochastic process, and with 'memory'). If you put aside the conventions, you will see that in its essence, the schedule of price changes (the market processes behind it) is very similar to quality control (read: production process control).
The shortest and most succinct description of key terms is in the electronic handbook of mathematical statistics for the program Statistica, on their website, in Russian.
And by the way, while we're on the subject of lyrics, there's a digression. Successful trading is nowhere near as easy as organising quality control in a factory.
In the context of the discontinuity problem its practical application to trading by Gorchakov is interesting
As for my methods in the market, they are divided into "short-term" and "long-term". "Short term" consists of constructing discontinuity criteria by a(i) invariant with respect to the mean process a(i) and sigma of the process s(i) within a conditionally non-stationary model
http://www.howtotrade.ru/forum3/posts/195.html
That is, it is a model which assumes that the relative price increments represent a non-stationary response to an unobservable stationary sequence. This is a common situation in the theory of signal extraction in the background of noise. The model is parametric because the constancy lengths a(i) (d(i) are also random variables) may be small and nonparametric criteria will produce large error.
This is what my trading systems are based on.
Long term" methods consist in permanent monitoring of stationarity of the average process a(i) and sigma process s(i) within the same model. They regulate weights of shorts and longs on short-term systems.
Actually functions I wrote about stationarity of distributions are functions invariant relative to the mean process a(i) and sigma. It was done only to verify the model and there was no other practical sense in detecting some stationarity in prices. The practical application is the work within the model.
More: http://www.howtotrade.ru/forum3/posts/192.html
Come on, Sergei. I understand the general outlines, but the details don't matter. Somehow this approach does not impress me.
I didn't say it was the best, and I suggest that you think about it. Right now, for example, I am investigating autocorrelation.
{0: 20}
{0: 21}
{0: 22}
...
{0: 4000}
I continue research and think how to define criterion better, with statistics everything is clear.
PS: Right now I'm just learning to define (identify) a trend on historical data, i.e. to find its beginning and end.
...
More: http: //www.howtotrade.ru/forum3/posts/192.html
What can you say, it's obvious that a statistician wrote it. :)
I will also add, it seems that what Pastukhov wrote in his dissertation is not all that he meant. It seems that H-volatility, it also can be attached to the solution of this problem.
...
r[i]=SUM{(Open[i+1+k]-Open[i+k])*(Open[i+k]-Open[i-1+k])}/SUM{|Open[i+1+k]-Open[i+k])*(Open[i+k]-Open[i-1+k]|}, where summing is performed over window k=0...100 (for example).
...
Yes, I forgot to add in a previous post that I don't use a sliding window on the data to calculate autocorrelation and consider its introduction unjustified, unless of course Neutron shows its advantage.
PS:
Neutron:
Let's get OPTIMAL behaviour not only in the market but also in research!
So there you go, decided to do my research optimally. :о)
...
Еще: http://www.howtotrade.ru/forum3/posts/192.html
What can I say, it's obvious a statistician wrote it. :)
I should also add that it seems that what Pastukhov wrote in his dissertation is not all that he meant. It seems that H-volatility, it also can be attached to the solution of this problem.
Yes, my education was not enough to understand what it says. Although, of course, you can figure it out.
It seems that what was expected in the near future is already happening - professionals in the field of science move from theory to practice.
Why not? MT4 provides excellent opportunities for that.
So soon there will be nothing for housewives to do here. :-)))
PS North Wind, what is H-volatility ?
...
PS North Wind, what is H-volatility ?
Here http://forum.fxclub.org/showthread.php?t=32942&page=9, about halfway down the page there is a short excerpt from the original source.
Wings, wings.... legs
well... )))
the problem is that he didn't calculate correctly.
So in practice it turns out that if you take the sum of any number of Self-Organizing Dynamic Systems, you get the same SDS in the output.
(with the same trands and flats. ;D)
I would like to suggest another fascinating article...
http://www.fractals.ru/pdf/23Mavrikidi.pdf
(For those who are interested only in the market and personal enrichment may not open - it does not say anything about the market, so there is nothing interesting for them).
P.S. Thank you, solandr, for suggesting a theorist in response to my prejudices...
Looks like what was expected in the not too distant future is already happening - professionals from science are moving on from theory to practice.
Wrong, professionals from science have been in the markets for a long time. And the professionals have very different results from capital formation to total ruin.