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This is the second time you've said "we've arrived", so make up your mind, smoothing in no way fits the concept of a trend as we understand it.
I prefer the term "smoothing" rather than "trend". Anyway, smoothing has an analytical form and is easily extrapolated
Traders don't care what the econometric sect likes. Brokers don't pay for smoothing because it is lagged, i.e. yesterday's day. And averaging leads to deep equity drawdowns.
If you will pay out of your pocket for the smoothed data forecasts or at least compensate for the losses, then we would like that too.
Traders don't care what the econometric sect likes. Brokers don't pay for smoothing because it is lagged, i.e. yesterday's day. And averaging leads to deep equity drawdowns.
If you will pay out of pocket for smoothed data forecasts or at least reimburse losses, then we would like that too.
Reshetov, read what I write for once, look at my model - its meaning is available even to you.
For others who read this thread.
The main thing is the following: when decomposing a quote into components, no matter with the help of indicators, regressions, VS or in any other way, we must be able to return to the basic quote, i.e. if we add all that we have decomposed it into, we must obtain the basic quote. Not a pip of data should be lost. How to achieve this in TA I don't know. How to achieve it in regression I have shown in the branch.
I was like everyone else and thought of the trend as a straight line. And then I wondered why a straight line and not a curve? And I quickly found out that a huge number of people say it is a curve. Immediately a lot of problems disappeared. Because we are interested in the direction of the trend on the last bar, and what happened 200 bars ago - doesn't matter. So long live the curve!
insist on adopting the Gamma function
Reshetov, read for once what I write, look at my model - its meaning is available even to you.
For the rest of you who are reading this thread.
The main thing is the following: when decomposing a quote into its components, no matter with the help of indicators, regressions, NS or any other method, we should be able to return to the initial quote, i.e. if we add all that we have decomposed it into, we should get the initial quote. Not a pip of data should be lost. How to achieve this in TA I don't know. How to achieve it in regression I have shown in the branch.
You should specify the type of functions that separately describe the components of quotient, that is why you are not understood, everyone is so good at dividing into components, but it is difficult to explain this division.
Why, I have explained. I can do it again.
Let's take a quotient. While there is a trend in it, we cannot say anything about the statistics - the trend will overrun all statistics.
We select the trend by smoothing НР, take some bars НР (4) and add to it the difference between the kotir and smoothing.
Let's look at the residue of this regression. We see that the trend (ACF) remains again. Once again, like above, but for the residue from the first regression.
We look at the residue of the new, extended regression. We see that there is no ACF. Let's rejoice and look for ARCH - it is some properties of initial quotient that were not visible at the beginning. That's it.
Result: we have two smoothing + two different residues after smoothing. If we add them up we get the initial quote, not a pip loss. In addition we modeled ARCH if necessary, which is not expressed in pips, but was the initial quotient.
I have written it many times. You can see in the formula.
Well, just because you don't know doesn't mean that others don't know. And there is no divide between TA and econometrics.
Most people, of course, just play with pictures of indicators without even knowing about the formulas of the indicators. But we seem to have people here who understand mathematics...
Just because you don't know doesn't mean others don't. And there is no divide between TA and econometrics.
Most people, of course, just play with pictures of indicators without even knowing the formulas of the indicators. But there are people here who understand the maths...