Bayesian regression - Has anyone made an EA using this algorithm? - page 37

 
Well, yes. Analytical function(?!)+Random function(normally distributed)=Winer process(Random walk). Shall we sew an EA?
 
Алексей Тарабанов:
Well, yes. Analytic function(?!)+Random function(normally distributed)=Wiener process(Random walk). Are we going to sew an advisor?

Cut. :)

Any complaints about the buttons?

 
Yuriy Asaulenko:

Cut. :)

Any complaints about the buttons?

They'll be sewn on tight.
 
Bang, bang, bang, bang!

Since Matemata and Prival and the like, this is the first thread where...

I'm crying :)

 
Event:
Bang, bang, bang, bang!

Since Matemata and Prival and the like, this is the first thread where...

I'm crying :)

How about a roll call? All the living...
 
Алексей Тарабанов:
Shall we do a roll call? All the living...
Yeah, let's remember Mishek, too.
 
Event:
Yeah, and Mishek will be remembered.
No problem. Would love to see Mathemat and Mishek.
 
СанСаныч Фоменко:

There is nothing like that in the marketplace. All of the above R2 figures are nonsense, because there is no proof that the selected plot for calculation is part of the general population, which has at least the property of stationarity. That is why the figures have been obtained on the above plots, but they have nothing to do with the future: they may or may not match, they may match 100 times, and then they sell the deposit along with the profit.

I subscribe to every word of it. What is the point of building the regression, if in the next section the characteristics of this regression will be completely different. You can tweak the model to fit the data as much as you want, but it is easier to just admit that Y (price) does not depend on X (time), at least in terms of linear regression.
 
Vasiliy Sokolov:
I agree with every word of it. What is the point of building a regression if in the next section, the characteristics of that regression will be completely different. You can tweak the model to fit the data as much as you want, but it is easier to just admit that Y (price) does not depend on X (time), at least in terms of linear regression.
These are the plots we need to think about - for the data to be similar - we should take a pattern, in my opinion, rather than just a window of n bars.
 
Vasiliy Sokolov:
I agree with every word of it. What is the point of building a regression if in the next section, the characteristics of that regression will be completely different. You can tweak the model to fit the data as much as you like, but it's easier to just admit that Y (price) does not depend on X (time), at least in terms of linear regression.
Well, admitting anything is certainly easier than building a model, analysing it, and applying the Chow test to test the hypothesis of sample heterogeneity.....
Reason: