Machine learning in trading: theory, models, practice and algo-trading - page 2523
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how do you make your broadcast is it a third-party service or what? how does it even work? how can I do this?
1. Take this https://github.com/tvjsx/trading-vue-js
2. Install it on your hosting, add an indicator which reads from a json file
3. You launch a script there which updates the file if you pull this script
4. somewhere else you run your neuro or whatever and when the signal reaches the script from step 3
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this is not a right scheme, the indicator should receive signals via api, it didn't work for me
Thanks, it's too complicated for me yet.
Yes, from the definition of SB, that all increments in the future are independent with values in the present and past and hence the covariances are all zero.
Not unity, it is the variance increasing with time j. If we denote by d the variance of white noise Xi, thenCOV(Yj,Yj)=j*d^2. To do this, we have to represent Yj as the sum of X1+...+Xj and calculate, taking into account the properties of white noise.
As a result, after substitution, ACF=sqrt(min(j,k)/max(j,k)). If I didn't mess up something, of course).
I propose to close the subject of ACF SB here, so as not to make particularly impressionable practical practitioners nervous)
min and max will be +- ∞ ?
min and max will be +- ∞ ?
j>=1, k>=1
For example, j=2, k=8 -> min(j,k)=2, max(j,k)=8 -> ACF(2,8)=sqrt(2/8)=1/2
Yes, from the definition of SB, that all increments in the future are independent with values in the present and past and hence the covariances are all zero.
Not unity, it is the variance increasing with time j. If we denote by d the variance of white noise Xi, thenCOV(Yj,Yj)=j*d^2. To do this, we have to represent Yj as the sum of X1+...+Xj and calculate, taking into account the properties of white noise.
As a result, after substitution, ACF=sqrt(min(j,k)/max(j,k)). If I didn't mess up something, of course).
I propose to close the subject of ACF SB here, so as not to make particularly impressionable practical practitioners nervous)
For the first time something interesting started in the branch and close ;)
Illustrations will be to understand what the appeal of these formulas?
If we denote by d the variance of white noise Xi, then COV(Yj,Yj)=j*d^2.
Excuse me, colleague, for interfering, but isn't there a clerical error in this phrase?
Sorry to interfere, colleague, but isn't there a clerical error in this sentence?
Well, yes, the square is redundant: COV(Yj,Yj)=j*d (or we should have denoted the variance of white noise by d^2 ). Thanks, colleague. It doesn't affect the final ACF formula, but denoting variance and standard deviation and dispersion with the same letter is a very bad tone.
To be honest, I can't understand anything at all.
p.s maybe some super smart mathematician will take pity on me and explain what's going on here?
To be honest, I can't understand anything at all.
p.s maybe some super smart mathematician will take pity on me and explain what's going on here?