Random Flow Theory and FOREX - page 63

 
begemot61 >> :
Just a stationary random process with a known distribution (not necessarily Gaussian) is very easy to make money on. It's just that besides the probability of going up or down (50/50, if that's what you mean) there are other properties.

"Known" by whom? Or maybe it's "Known - one of the first five dozen ALL known theoretical distributions, each of which can easily be reduced/derived to normal" ?

Keep in mind that 97% of probability and statistics formulas refer to normal distribution of a random variable. If its distribution differs in any way from normal or "standard dozen", the formulas simply do not work. So there are immediately a bunch of problems that ROBAST probability theory deals with, i.e. little dependence on non-normality of the distribution. But before applying the robust one (there isn't much of it yet) you need to have a distribution function at hand and I would ask you to clarify - how do you or anyone else know the distribution of our price series and whether there is such a thing as a "probability distribution" for a price series at all? How and at what interval are you going to calculate it?

 

If your sigma and expectation are the same, why not make a trillion:)

 
registred >> :

If your sigma and expectation are the same, why not make a trillion:)


Actually "sigma" is that kind of gut at the bottom of your stomach:

https://ru.wikipedia.org/wiki/%D0%A1%D0%B8%D0%B3%D0%BC%D0%BE%D0%B2%D0%B8%D0%B4%D0%BD%D0%B0%D1%8F_%D0%BA%D0%B8%D1%88%D0%BA%D0%B0_%D1%87%D0%B5%D0%BB%D0%BE%D0%B2%D0%B5%D0%BA%D0%B0

And when one worries at changes in the expectation of price series, then indeed one's sigma-key changes too.

Oh, or are you talking about something else?

 
AlexEro >> :

Actually "sigma" is that kind of gut in the lower abdomen:

https://ru.wikipedia.org/wiki/%D0%A1%D0%B8%D0%B3%D0%BC%D0%BE%D0%B2%D0%B8%D0%B4%D0%BD%D0%B0%D1%8F_%D0%BA%D0%B8%D1%88%D0%BA%D0%B0_%D1%87%D0%B5%D0%BB%D0%BE%D0%B2%D0%B5%D0%BA%D0%B0

And when one gets worried when the expectation of price series changes, then indeed one's sigma-key changes as well.

Oh, or are you talking about something else?

Uncle, if you are already too smart, I pity you:) If not, I suggest you read what a stationary process is, whether it is random or not.

 
registred >> :

Uncle, if you are already too clever, I pity you:) If not, I suggest you read what a stationary process is, whether it's random or not.


Aubanki! Here we go. Turns out there are even "stationary non-random processes"?! Where are they? Almost for the first time in my miserable life Google HAS NOT SEEN THESE ON THE INTERNET ! (More accurately, it gave out only a link to THIS THING on this forum. This thread has already gone down in the history of science). It's just a holiday. Every day there is terrific news, and on a world historic scale.

Colleague, I want to ask you one very important question - have you read Mark Twain's story "How I edited an agricultural newspaper"? If not, I will quote a lot of it here. It will be more useful than giving links to Wikipedia.

 
Choomazik >> :

That's it, in a nutshell. "...classical geometry, augmented by a few new postulates. It is complete and consistent..." wrong. About 15 years ago, in botany, I had to give a proof in an exam :)

To be honest, I didn't check about the geometry, I just read it in some popular book. And I was even terribly surprised by this fact. And astonishment, as you know, helps to consolidate information.

But I am still curious, what botanical proof did you use?

 
Mathemat >> :

To be honest, I didn't check about the geometry, I just read it in some popular book. And I was even terribly surprised by this fact. And astonishment, as you know, helps to consolidate information.

But I'm still wondering, on what botanical you were guided by your proof?

Theoretische Informatik II . Not my proof, but Gödel's, which is quite elegant (I don't remember the details anymore, it was a long time ago). I can recommend a good book on the subject, Russian translation: http: //www.ozon.ru/context/detail/id/129157/

 
AlexEro >> :

Aubanki! Here we go. Turns out there are even "stationary non-random processes"?! And where are they? Almost for the first time in my miserable life Google HAS NOT SEEN THESE ON THE INTERNET ! (More accurately, it gave out only a link to THIS THING on this forum. This thread has already gone down in the history of science). It's just a holiday. Every day there is terrific news, and on a world historic scale.

Colleague, I want to ask you one very important question - have you read Mark Twain's story "How I edited an agricultural newspaper"? If not, I will quote a lot of it here. It will be more useful than giving links to Wikipedia.

One more time, just in search of where you are looking there, random process I suggest you look, I think it will become clear what I meant. :)

 
Choomazik >> :

Theoretische Informatik II . Not my proof, but Gödel's, which is quite elegant (I don't remember the details anymore, it was a long time ago). I can recommend a good book on the subject, Russian translation: http: //www.ozon.ru/context/detail/id/129157/

I confess my ignorance on the subject of completeness and inconsistency. If I have offended you, faa1947, I apologise. But still your

Straight theorem: If a theory is incomplete (it has unprovable propositions - axioms), then it is not contradictory.

- This is some kind of nonsense... And the "Inverse theorem" (which of course is not inverse to the Direct theorem, but inverse to the theorem proved by Gödel) is valid only for sufficiently rich mathematical theories. I hope I am not confused here?

 
Yurixx >> :

This has already been stated here by some people. Would you be so kind as to provide a scheme, algorithm, proof or whatever you like, but meaningful, to show how to do it. You can confine yourself to random rambling with a normal distribution. Pls.

To put it simply, you have a Gaussian distribution (in case of other distributions it can work too, as long as it is known and stationary). You have a bell that shows that the price is often close to the mean value. You wait for the price to bounce "far enough" from the average and open a trade in the direction of the average. The price will always return to the area "close to the average". What is "far enough" and "close to the average" can be determined from the distribution.