From theory to practice - page 680
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
For dabbling, I took ideas purely from this thread. Sketched out an indicator with arrows.
Kick me if you're lazy.
I found algorithms of Variance - Gamma process (VG) generation in Kuzmina, who can help to translate them into Excel? )))))
First, we generate a standard Brownian motion
a) Standard normal distribution (it is clear)
(b) It is not very clear. Who can do it?
http://elib.bsu.by/handle/123456789/9487
PS Interesting to see this miracle))
I also thought I'd add: what you fight for, you get what you get)))))))
I found algorithms of Variance - Gamma process (VG) generation here, from Kuzmina, who can help to translate it into Excel? )))))
First, we generate a standard Brownian motion
a) Standard normal distribution (it is clear)
(b) It is not very clear. Who can do it?
http://elib.bsu.by/handle/123456789/9487
PS It is interesting to see this miracle))
Give me a full quote where something is unclear or needs to be done... I, for example, am too lazy to download a pdf and search through it. Many others probably aren't either :-(.
PS/ programmers are not lazy - they are optimal
i.e., expectation == linear function of time? not a constant? Or is it an error?
Calm down with the Nobel, and use your brain.I'm too lazy to download a pdf and look it up. Many people are probably too :-(
PS/ programmers are not lazy - they are optimal
It is on the last page, before the list of references, and there are two graphs. You don't need to download it, it goes straight to google
There are several ways of modelling dispersion gamma - process [4], [6]. Here are the algorithms for modelling dispersion gamma - process used in this work.
The formulas are squared, it is not possible to paste them here.
There's the last page, before the list of references, and two charts, if you're not too lazy)))
what is unclear in pt2) ? of course grad students wrote it, if you are lucky... :-)
in first column - G
second column - write v = NORMALLY distributed numbers (0.0 1.0)
in the third column W[0]=0 and then "the formula is given" :-)
It's not the first time I've seen the picture you're posting.
The question is - WHAT IS THIS!
is 10 times.
Guys, I'm worried about a number of questions, thanks CheGevara, in the right direction. What is primary, MM or all the same MO> 0? If we put at stake the assumption that after all the market is random, the exponential (geometric in terms of discreteness) random walk model will not give any profit on outliers (or a small deviation in the proverbial 2% non-randomness, covered by the total spread), in the end gives zero or about that, then the probability of a random event in its favour when using MM. Or vice versa: the market gives a chance, then with all the power of MM increase the chance proportionally.
"To check a TS, you should first try it with a fixed lot. If you are satisfied with the mathematical expectation, you may increase the profitability by capital management ".
Dependence of profitability on parameters of tick-maxes used at the channel boundary to determine the probability of a rebound from the boundary.
Why 100 times? Stop Loss will trigger 2 times, Take Profit will trigger 20 times.
10 times.
In my opinion, there is no need to simulate anything.
It is already clear to everyone that the market is a variance gamma process.
Once again, I draw attention to the variance of this process:
Recall that for Brownian motion the mean displacement= sqrt(2*sigma*t) according to Einstein.
If we had (theta^2)*nu = (sigma^2), we would have Einstein's formula.
But we have a superposition of two processes, gamma and Wiener.
For Wiener one, we calculate the usual sigma.
For gamma, we still need to learn how to count variance =(theta^2)*nu.
Then we subtract the obtained values from the expected payoff of the process and voila - the Grail! And no stupid quantiles need to be calculated.
Brothers, prepare your pockets!
Brothers, get your pockets ready!
where to send account number? :-)
PS/ Being inside (and now) a random process, one cannot reliably predict its future (that's why it is random). One can define statistical characteristics, based on them make an assumption, but it will have the same probabilistic nature and will not be qualitatively better.
Hegel, dialectics, non-creature-order out of chaos :-)