The Sultonov Regression Model (SRM) - claiming to be a mathematical model of the market. - page 12
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It is not a question of how or what to base a prediction on, but how to check its validity. If the residuals (error) are not Gaussian distributed, it's no good).
No, the residuals are tested for normal distribution (z-test for example). Stationarity is you test for something else)))
Even double-checked.
No. Taking EViews.
Normality test as a reference (Jarque-Berg) among other descriptive statistics.
Then there is the unit root test: 6 types of test with 8 types of automatic lag length selection; for level, 1st difference, 2nd difference; with inclusion of bias, trend and offset and without anything.
The normality test is a test of nothing.
It is more reliable to perform the test after detrending and removing the cyclic component.
It's not a question of how or what to base a prediction on, but how to check its validity. If the residuals (error) are not distributed according to gauss, it's not good))
Why ?
Does this mean that something else can be taken out of the error part or is it indicative of randomness in the error-free part ?
Then describe how you want to get "deterministic", and without noise?
You take a waving machine. The remainder is noise. What is the noise in the dash?
it means that the variables are deterministic rather than random
You take a mashka. The rest is noise. What's the noise in the wrecking ball?
OK, moving on - logically such a model should predict interventions )
OK, moving on - logically such a model should predict interventions )
No, of course it doesn't.
Why ?
Does this mean that something else can be taken out of the error part or is it indicative of randomness in the error-free part ?