Bayesian regression - Has anyone made an EA using this algorithm? - page 14
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Polynomial.
If you add noise to the quotes, you get this distribution:
And how would that help trading?
Take it, calculate it, compare it.
Why should I? I don't care, you can stay in your fog as dense as you like for as long as you like.
Besides, this proposal of yours looks very strange. Since you are presenting yourself as such a unique expert and inventor, you must know polynomial regression and know its properties.
There is absolutely no need to calculate it, there is an indicator in the codebase, you can even change the degree of polynomial, and that's really power.
If you add noise to the quotes, you get this distribution:
And how would that help trading?
Why should I? I don't care, you can stay in your fog as dense as you like for as long as you like.
Besides, this proposal of yours looks very strange. Since you are such a unique expert and inventor, you should know polynomial regression and know its properties.
The polynomial needs to be adapted to the actual data every time, and in the case of (18) you don't need to do anything, it adjusts itself in the best possible way. You just don't have the courage to admit that a better model than (18) has not yet been invented in every sense.
Why adapt it? It is the polynomial that adapts best on its own. Your curvilinear regression will only rarely fit the data. The situation here is quite different, your regression is not that it is the best or the best, it does not apply here at all.
It's also not quite clear what you call adaptation? The very essence of regression is adaptation. Why else would you call it butter?
How can you give an estimate to something you haven't tried?
Why adapt it? It is the polynomial that adapts best on its own. Your curvilinear regression will only rarely fit the data. The situation here is quite different, your regression is not that it is the best or the best, it does not apply here at all.
It's also not quite clear what you call adaptation? The very essence of regression is adaptation. Why else would you call it butter?
The easiest way to shut me up is to show the workings of the polynomial model with this example. I am convinced that it has no predictive ability. It might be able to show something at a segment of the actual data entered, but then it gets away from reality.
Otherwise, you'd think yours would be applicable for forecasting.