Machine learning in trading: theory, models, practice and algo-trading - page 2525
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 for SB. What do we need it for?)
To understand that earnings are possible on the differences between real BP and SB. And look for these differences.)
To understand that earnings are possible on the differences between real BP and SB. And look for those differences )).
In the real market? Personally, I hold to some such philosophy:
*but I don't really want to discuss it, because it's useless to discuss assumptions without evidence.
In the first half of the noughties there was a flurry of scientific papers with attempts to use the constructed theory of dynamic chaos to predict financial time series. The basic idea: from the realization of a time series to reconstruct a dynamic system and use it for prediction. Then somehow the flow of publications got thinner.
Half of the forum is "making money" on SB as well, with a bang)
Didn't you notice that the number of "accidental wanderers" decreased. Even Alexander did not fall for my provocation ))).
I would also, if you don't mind, rewrite it in a more familiar form:ACF(t) = sqrt((n-t)/n), where n is the sample size.
For example, if 1<=t1<=t2<n, then ACF(t1,t2)=sqrt(t1/t2).
Also, I'm more used to assuming time (sample size) is infinite for SB, since many useful problems (same probabilities of reaching levels) are easier to solve with this assumption.
In the first half of the noughties there was a flurry of scientific papers with attempts to use the constructed theory of dynamic chaos to predict financial time series. The basic idea: from the realization of the time series to reconstruct the dynamic system and use it for prediction. Then somehow the flow of publications thinned.
I remember there was a book by Peters on the subject, where he calculated the dimensionality of the attractor for some market. It seemed to be quite large, which makes you wonder about the statistical significance of the result.
You only have the correlation of the last value in the sample with all the others.
Well this is the classical definition of ACF.
For example, if 1<=t1<=t2<n, then ACF(t1,t2)=sqrt(t1/t2). Also, I am more used to assuming time (sample size) is infinite for SB, since many useful problems (the same probabilities of reaching levels) are easier to solve under this assumption.
By the way, the answer to the retort,"The formula is derived, out of a sporting interest) is hardly useful for making money."
I remember there was a book by Peters on the subject, where he calculated the attractor dimensionality for some market. It seemed to be quite large, which makes you wonder about the statistical significance of the result.
Yeah, "Chaos and Order in the Capital Market. There were a lot of publications. But nothing has settled down.
By the way, the answer to the retort: "The formula is derived, out of a sporting interest) it is hardly useful for making money."
levels up? or levels down?)
The question should, of course, be addressed to Alexei. But I would answer "whatever". The question, I assume, is that SB travels a path proportional to sqrt(t).