Random Flow Theory and FOREX - page 67
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NR is not characterised by return to the mean (it does not say anything about the presence of memory in the series). Return to the mean (or vice versa) is called persistence and is measured in Hursts for example.
Memory has nothing to do with it. It will return statistically. By the way, it is possible to make money on persistence, or rather on 2H volatility, but it is very low, the system is flimsy. The trick is to calculate the compensation for transition of persistence to antipersistence and vice versa.
It was about the cumulative sum, not just the distribution of increments.
By the way, your distribution graph in the previous post doesn't look like HP. What sigma?
Sigma and in the first post 35 cents.There are three tails "cut".I already wrote about them.This is the cumulative amount minus the muving.The amount "does not run away",it comes back to it.
Memory has nothing to do with it. It will come back statistically. By the way, it is possible to make money on persistence, or rather on 2H volatility, but it is very low - the system is flimsy. The trick is to calculate compensation for persistence transition to antipersistence and vice versa.
Well here it's about earning a return to the mean, which is visually characterized by flatness. Memory is the key concept here. By the way one of TA postulates.)
As for earning on persistence if we are talking about a practically real series, then why not. If we speak about the theoretical series with such characteristic then as they say, there is not enough information to confirm or refute it.
Sigma and in the first post 35 cents.There are three tails "cut off".I have already written about them.This is the cumulative amount minus the muving.The amount "does not run away",it comes back to it.
It's too spiky for HP.
>> More like a Laplace distribution.
Too spiky for HP
I was breaking it up into intervals of 3 cents, I can't remember now, it was more likely because of this. I got inconsistency around zero. The point is that the frequencies tend to НР.
Well it's about earning a return to the average, which is visually characterised by flatness. Memory is the key concept here. By the way one of the tenets of TA ;)
As for earning on persistence if we are talking about a practically real series, then why not. If it is a theoretical series with such characteristic then as they say, we have not enough information to confirm or refute it.
We are talking about the euro/dollar pair.
The standard example with a coin and its cumulative sum is an example of a stationary series ideally forming a SB
What would this process have and how does this relate to the definition of stationarity?
What is the variance of this process and how does this relate to the definition of stationarity?
In eagle, if heads are 1, tails -1, then MO=0, D(X)=((0-1)^2+(0+1)^2)/2=1
Conant dispersion and constant MO. Why non-stationary?
Even if we take a cumulative sum over any fixed number of throws (e.g. 100), the distribution would be normal as well with MO=0 and a fixed, easily calculated variance.
I told you straight away that for you it would remain "the tumbling ninth wonder of the world".
You're not getting it again, brother. Or did you really think I wanted something from you? :-)
I am used to find proof or refutation of all questions that interest me.
And in this case I just wanted you to give me a receipt for your hollowness. Which you did. >> congratulations.
I am shocked at the difference between the two and everything stops working at once.
Young man, I was still waiting for you to correct your mistake, which was politely pointed out to you, but you are not itching and do not think to correct(s).
Distributions
Your alleged "normal distributions"
You don't have a normal distribution.