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Correlation coefficients for 1 bar are not calculated, but are calculated for N bars. That is why the response of the slave pair to the movement of the master pair is obtained for N bars history section, not for 1 bar.
There will be noise in any case, but if the correlation coefficients and the less difference for correlation coefficients for pp. 1 and 2, the higher the noise value.
The reaction time still matters. If the offset is taken - 1 bar, and the pair reacts in time of 0.9 bar, it's one thing, it's real to get out from under the noise. But if the reaction time is 0.01 bar, that's another thing.
But, as always, practice is the criterion. You have to test it.
I want to show you a strategy by example (two signals today, manual play):
There is a method. Everything is learned by comparison. It involves calculating correlation coefficients for two cases:
Compare the correlation coefficients for the absolute values obtained in step 1 and step 2:
I agree with the 1st part of the picture, euro went up half an hour early (my time = MSc -1)
Second hike with the pound leading - I don't see it, the euro rolled back almost to the baseline and went back up again
We don't have what to measure the "strength" of the presenter in
As the simplest - number of "steps" - size + speed of "steps" x time
1 "step" is 10% of yesterday's range (euro = 11p, pound = 6p)
One should not measure correlation but cointegration, and this works if both pairs have the same level of integration.
We need to check whether currency is in long term equilibrium otherwise speaking, two non-stationary processes, give a stationary linear combination.
Naturally.
If we talk about outperformance, it has a place and Reshetov wrote how to check, so they do. It is used in the stock and commodity markets. There are macroeconomic time series leading. In forex I think Asians are ahead of Europe and states. Australia is good as a lead.
There's been talk about correlation... what method do you use to measure it?
There are many, not all of them are suitable.