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I explained the calculation period above - it does not exist, as a quotire is a non-periodic series
in which a quote is allowed to have practically negligible increments, with sufficiently wide possibilities for price management
is proved by Fourier transforms.
I would argue about a 2-3% overweight, but I won't.
Just to give you an example - black swan on the pound in '16, about 90% stood to buy....
And the funny thing is that it was a no-break for all markets, huge livantos
Can a counter-trend strategy withstand such a move? The answer is hopefully obvious.
And what's above is a reversal strategy
The author is off topic, he's right.
...
I give an indicator on the 1st item, for "it's all rock'n'roll" ;) (ok, but only for dabbling)
On the second - let's say everything is on sale, will there be asymmetry? The answer is YES.
I give an indicator on the 1st point, because "it's all rock'n'roll" ;) (ok, but only for dabbling)
on the second - let's say everything is on sale, will there be asymmetry? The answer is yes.
I can give you a hundred indicators based on regression and on splines, or on anything else. What is the point? You may or may not rock and roll, but it works unlike the second option.
It's not working.
Move on
I listened and listened to CheGevara (about Gauss on large TFs and quantile=1.6, etc.) and decided to make a simple indicator:
GBPJPY 2018 pair.
Used:
1. CLOSE M1
2. sliding window - week (7200 values CLOSE M1)
3. simple MA
4. dispersion calculation according to the formula from this branch + quantile =1.6
Looking at:
A total of 7 trades would have been made in 2018 (+6/-1)
Total profit: +733 full points.
If anyone is sure this is the Grail, let them set up a TS and post it here. Right to the branch. Let the suffering people use.
I listened and listened to CheGevara (about Gauss on large TFs and quantile=1.6, etc.) and decided to make a simple indicator:
GBPJPY 2018 pair.
Used:
1. CLOSE M1
2. sliding window - week (7200 values CLOSE M1)
3. simple MA
4. dispersion calculation according to the formula from this branch + quantile =1.6
Looking at:
A total of 7 trades would have been made in 2018 (+6/-1)
Total profit: +733 full points.
If anyone is sure this is the Grail, let them set up a TS and post it here. Right to the branch. Let the suffering people use.
Well ... I hope the few people who know who I'm talking about and who really understand what I mean have understood. That's enough for me :)
some do and some don't.
If you study, you won't want to write.
You will simply be misunderstood.
I am willing to share with people who know what works and that will give results.
;)
The highlighted context of your post is only wishful thinking, you will have to dig there yourself
What if you run it for the last 10 years? Is that possible? And find out where the series of profits in a linear regression converges to zero minus or plus?
I don't have such archives... As a matter of principle I didn't use them, I thought it was all nonsense and worked with Erlang's tick flows... And lo and behold - how it all turns out...
I listened and listened to CheGevara (about Gauss on large TFs and quantile=1.6, etc.) and decided to make a simple indicator:
GBPJPY 2018 pair.
Used:
1. CLOSE M1
2. sliding window - week (7200 values CLOSE M1)
3. simple MA
4. dispersion calculation according to the formula from this branch + quantile =1.6
Looking at:
A total of 7 trades would have been made in 2018 (+6/-1)
Total profit: +733 full points.
If anyone is sure this is the Grail, let them set up a TS and post it here. Right to the branch. Let the suffering people use.