From theory to practice - page 683
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K2's monitoring isn't great, if anything...
So what?! There's a month's worth of upside, I think... That's not the point. What is it?! It's the fucking Grail you have to pull out of the Variance Gamma Process. It's there and I can see it.
So what?! There's a month's worth of benefits, I think... That's not the point. What is it?! It's the fucking Grail you have to pull out of the Variance Gamma Process. It's there and I can see it.
And do you go to the second Alexander's PM? Because I'm writing and I don't know if you read it or not.
Do you go to the second Alexander's PM? Because I'm writing and I don't know if you're reading or not.No. He's busy :)))
he's just never won, that's why he's freaking out.
K2's monitoring isn't exactly shining, so...
K2 has the prospect of finding the right solution. But he wants 100% quality entry, but the market will never let him do that.
You can only make money on probabilistic MO. Right entry and right exit. Cut the losses, keep the profits. You don't need anything else.
For the five hundredth time, I am publishing the Grail:
The process variance makes sense to me.
sigma^2 is the usual variance of the sliding window increment distribution
theta^2 is an unusual variance, namely = 2*(b^2), where
nu is an order of gamma distribution, and if we are talking about Laplace distribution, nu=1.
But expectation, may the thunder strike me, is not clear to me...
I reread the correspondence between Automat and Vladimir - options, saturation functions... Fainted and fell asleep...
I tried to build a variance channel relative to the MA and the median, the results improved by about +10%, but it's not the same... Wrong, as it were...
Continuing to dabble...
For the five hundredth time, I am publishing the Grail:
The process variance makes sense to me.
sigma^2 is the usual variance of the sliding window increment distribution
theta^2 is an unusual variance, namely = 2*(b^2), where
nu is the order of gamma distribution, and if we are talking about the Laplace distribution, nu=1.
But expectation, may the thunder strike me, is not clear to me...
I reread the correspondence between Automat and Vladimir - options, saturation functions... Fainted and fell asleep...
I tried to build a variance channel relative to the MA and the median, the results improved by about +10%, but it's not the same... Wrong, as it were...
Continuing to dumb down...
it's all correct, and the formula is essentially the same, whatever you do:
- econometrics with its ISC
- Fourier transform.
- other distributions
However.... I've been saying for a long time that we have N = infinity, so the increments are infinitesimally small
Relatively large increment is only possible by transforming the timescale, or if you use the formula:
dPrice/dt
There is no time in your formula
Suppose there is a flask with some substance on the table, the table has some vibration, and this vibration sets the tone for movement of particles of this substance (roughly speaking, if I may say so).
We calculate the process that happens there and make predictions about the motion of the particle. And then someone came to the table and shook the flask and left it on the table again.
Now let's suppose that at the market that we want to forecast something unpredictable happens that breaks everything that was calculated and forecasted before. A new phase begins, which you do not know when it will change.
You put on glasses so you don't get spit in your eyes.)
But you can't see anything through them. I won't exchange any more phrases with you(((
he's just never won, that's why he's freaking out.
K2's monitoring isn't exactly shining, so...
I won't claim, as Sascha usually does, but perhaps the ejection is determined by an angle > 45 degrees.