Not Mashka's business! - page 12
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
I told you - there's no picture! If you do see it, then you need help :-)
Seriously, it's the most usual casual recursive filter, of the form:
y[i]=a*x[i]+b*y[i-1], where a=0.1, b=0.9
It's extremely inconvenient to "write mobile", but I couldn't help replying. Seryoga, if you mean by mysterious signal this crap, then it is rubbish in the literal sense and has no prognostic property whatsoever. The twist of Burg's method is that the covariance function of current values and future values is estimated. Probably, this estimation is reduced to the estimation of autocorrelation, the theory also allows for it. The rest is a matter of technique.
Posted a corrected Wiener row (random, Brownian-like)
for TC testing. Now its length is 2*10^6, the autocorrelation function for the first difference series is shown on the left (the first count is identically 1 and is not shown). The distribution function for the amplitudes of the first difference is shown on the right. The distribution is purposely chosen to be non-Gaussian, it is more consistent with the distribution observed in reality for market BPs.
Neutron
Maybe you missed it, it's not a gauss, but it's not the one you chose either. Check out my research and see if it helps.
'Building a trading system using digital low-pass filters'
Neutron
Maybe you missed it, it's not a gauss, but it's not the one you chose either. Check out my research and see if it helps.
It's the second order of accuracy. Maybe it's not so important.
This is code for finding the ACF of the first difference of BP x as a function of the step. The ACF is plotted on the interval from 1 to time.