Profit from a random price range - page 6

 
Mathemat:
Mak, you've bent it the wrong way. The price never intersects with the muving?!
It does,
but we're talking about the distribution function of the difference between the price and the moving average.
If price is bounded, then the difference involving it will also be bounded.
This means that there are values that this difference will never take.
 
Mak:
You're a nerd yourself...
Do you know the difference between a random variable and a random series?
And don't teach me about probability theory, read what it is first.

Explain it to me in your nerd language.
 
To begin with, it would be a good idea to define the concept of random series of all sorts of values and signals.

Here is an extract from the article: Vladimir Kravchuk (c) "New adaptive method of following the trend and market cycles".

"For deterministic (non-random) signals the transition from a temporal description of the signal to a frequency description, i.e. calculation of the frequency spectrum, is done using the Fourier transform.

However, random noise can no longer be described by a frequency spectrum because the Fourier transform of noise is also a random process. Typically, random processes are represented by the spectral power density of a process (SPM). The SPM is the Fourier transform, not of the random process itself, but of its autocorrelation function.
"

So there is a method for checking price series for randomness after all. If the frequency spectrum is highly variable, then the quotes are random.
 
Mathemat:
olexij, you yourself have guessed what I meant about transforming fractal to normal. But the conclusion about going back to efficient market theory is, in my opinion, wrong. The normal data that is obtained in this way are synthetic data. They are not directly related to the market.

Well, it would be better to ask S.V. about the details. He started this mess, on many pages he tried to justify the possibility of profitable work on normal, and then he also threw in this idea of transformation without showing its implementation. I respect the opinion of both S.V. I respect S. and Rosh' s opinion, but I strongly doubt that it is possible to build something long-term profitable on normal data. But on a pure fractal distribution with a decent Hearst index (close to 1), I think it is possible, because it is clearly a persistent series. Weeks, for example, have H significantly higher than minuses...

2 Mak:
3. So the distribution of the price difference and the moving average will ALWAYS be bounded from below by some value, and the value of the difference may aspire to this limit, but can never reach it.

Mak, you've bent something wrong. Price never intersects with the muving?!

You probably guessed that in order to transform something you should at least know what is there, if you transform by those methods that you mentioned, and simply saying "here - a fractal distribution" is not enough. Besides, you can't do without losing information, hence my conclusion about an efficient market.
Then, as far as I understand, what they are trying to achieve is the linearization of the problem. Well, the problem here is all in the details...


P.S. Please put punctuation marks yourself and don't get clever about it :)
 

olexij, it is not necessary to know what is available if what is available does not change its parameters. I am talking about p.d.f. Returns. Let it not even be a fractal distribution, whatever. As long as it doesn't change depending on a segment of historical data.

2 Mak: The assumption about the limited difference between the price and the muving is, to put it mildly, unreasonable. Price is bounded, but, for example, Peters' distribution of neighbour price differences (Returns) is considered fractal, i.e. theoretically these differences are not bounded. There is no value that it cannot take, although of course, starting with some, they are highly unlikely. For example, 10 sigmas (on the daily euras, on the order of 700-1000 pips)...

 

Since I was reminded here, I should probably clarify my own position on the possibility of profits on random walks.

If you play perfectly honestly, you really can't win on a random walk with mo=0 (in the sense that players mean "win"). That's the way it is. It follows from both the first law of arcinus and other theorems, the same Dub. Every time you play such a game you will either lose a little or win a little, markedly with 50% probability. That is all.

If you have random wandering with drift (conditionally you can call it a trend), and you know exactly what it is, and you know where the drift is directed - then you can win with almost no risk. And it's kind of already been said in this thread.

However, if you play as I suggested in the above link, you can surely win even on random walk with mo=0. But, once again, it is not exactly the game we are told about in theorems. Once again, this game has nothing to do with reality and is intended to demonstrate the importance of accurate testing. The point is that the winnings there are accumulated by undercounting the bets won and lost. That's right.

If you manage to play a game like I suggested, you will definitely get rich. :) And I should add that distribution in this game also makes a big difference. The game is simply not feasible on some kinds of random wandering.

ZS. Without regard to what has been discussed, if you convert the existing distribution to another then you can indeed have an advantage at times, but a very shaky one.

 
NorthernWind:

However, if you play as I suggested in the link above, then you can win for sure and on a random walk with mo=0. But, once again, this is not exactly the game we are told about in the theorems. Once again, this game has nothing to do with reality and is intended to demonstrate the importance of accurate testing. The point is that the winnings there are accumulated by undercounting the bets won and lost.

Can I repeat the link, I still can't understand why you can't win (if you play by my rules)

 
Prival:
NorthernWind:

However, if you play as I suggested in the link above, then you can win for sure and on a random walk with mo=0. But, once again, this is not exactly the game we are told about in the theorems. Once again, this game has nothing to do with reality and is intended to demonstrate the importance of accurate testing. The point is that the winnings there are accumulated by undercounting the bets won and lost.

Can I repeat the link, I still have no way of understanding why you can't win (assuming you play by my rules)


I don't understand the question. If you have the ability to set your own rules, you can win. If it's a classic oracle, only half the time, and half the time you'll lose, so the average result will be around 0.
 
NorthernWind:
I don't understand the question. If you have the ability to set your own rules, you can win. If we are talking about a classic eagle, only half of the time, and half of the time you will lose, so the average result will be around 0.


In oracle, with a perfect coin, yes I agree. But transferring the proof obtained on the coin, to forex IHMO not correct. Where can = 0, or at least a constant. And who is forcing me to make a bid (Buy, Sell) at every tick (minute, hour) + as soon as the tick (minute, hour) is over, I get a win (loss), and even fixed?

 
Prival:
NorthernWind:
I don't understand the question. If you have the ability to set your own rules, you can win. If it's a classic oracle, then only half of the time, and half of the time you will lose, so the average result will be around 0.


In an oracle, with a perfect coin, yes I agree. But transferring the proof obtained on the coin, to forex IHMO not correct. Where can = 0, or at least a constant. And who is forcing me to make a bid (Buy, Sell) at every tick (minute, hour) + as soon as the tick (minute, hour) is over, I get a win (loss), and even fixed?


Fixed loss and gain can be arranged, in pips - take profit and stop loss of the same size. :) It does not depend on where you enter and how often, in general terms, nothing, if the entrance does not exploit some regularity of the series. It's the same for the exit.

But in general, I have never said and probably would never say that the price series is absolutely identical to the horizon. But they do have some features in common, as well as differences.

By the way, there wasn't exactly an orlyagka in the game, there was a Gaussian distribution.

Reason: