Random Flow Theory and FOREX - page 54
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In practical terms, how is that? Are there any considerations?
For example, I have calculated a pattern assuming a stationary process. Now, how do I exploit this pattern assuming a non-stationary process?
Do I need to investigate this regularity in a non-stationary process? And how can I do it without knowing properties and nature of this non-stationarity?
To study non-stationarity by the example of this regularity?
Yeah, how? Any fool can just throw around abstruse "definitions" on an anonymous forum without any responsibility for the "definition". Try to show in practice that the model-definition works.
The GER thesis that all information is in the price seems to be used by everyone who makes quotes series forecasts. Or are you doing something different?
The thesis is slightly different, but that's not the point. It's about the underlying assumptions, the non-negotiable axioms: price is a random walk and then Gaussian, normal law and there you go. There's no such thing at all.
I can predict that the negro I saw in the picture will remain a negro in life :)
What's in it for you? You need to know where he's going. The insurance company wants to know how long he is going to live and how sick he is going to be in his life, so they ask where he was born, what his lifestyle is, what he does for a living, what he does for a job and what he was sick with in his childhood.
And you have only a price range, and in the best case it is not even the volume of currency purchases, but the TYCICAL AMOUNT. And they tell us that by decomposing the image of a Negro in a picture into sinusoids, we can know where and how fast he will run.
I will twist what Avals just said: the real living Negro is not made up of sinusoids. He is composed of water, of cells, of blood and meat, he has free will, which he is guided in all his movements. Your image of a Negro can, in certain cases, be "decomposed into sinusoids", and even derive some benefit from it. For instance, you can use an image of a Negro running to continue the motion cycle of his legs and make a movie about the Negro's running. Only the real Negro will stop after 30 seconds, and your extrapolation of his image will show that he is running EVERYWHERE. And his mood has CHANGED! And he no longer wants to run! Therefore, the mechanical extrapolation of his running on the picture of the video will not do anything.
You don't have a Negro. You only have an image of him. That is why you will not be able to make long-term predictions by his image (by means of decomposition into sine waves). You have to know where he is running, why he is running and how many resources he has for running, when he will get tired, and how to determine from individual pictures that he has started to get tired.
Fierstein?
Reception.
Wow, that's really something. I will try to explain without allegories: with DFT you get a decomposition of the signal into its components, after which you will NOT be able to say that it is NOT composed of them, because in sum the components will give the original signal. And don't go on about cause and effect here, it's arithmetic. The catch is that it will be interpolation, and outside of the decomposition section it will almost always carry no meaning.
P.S. Unlike the Negro - if you take him apart, then... no it's cruel, inhumane and unappetising.
In practical terms, how is that? Are there any considerations?
For example, I have calculated a pattern assuming a stationary process. Now, how do I exploit this pattern assuming a non-stationary process?
Do I need to investigate this regularity in a non-stationary process? And how can I do it without knowing properties and nature of this non-stationarity?
To study non-stationarity by the example of this regularity?
Stationarity is a special case of non-stationarity. Markets are stationary at some intervals, but you can't get market reversals from those intervals, i.e. what you can get from non-stationarity. On this post I gave a link to Peters. I'm rooting for the correct methodological approach. Efficient markets are a dead end, i.e. you can grind for centuries with depo emptying. If initially markets are considered as dynamic non-linear systems and the theory available in this field is directed to recognition of some patterns which have prediction ability - it is perspective in its basis, maybe you or I will fail, but not a deadlock, i.e. some day, someone will get it, but in GER never and nobody.
Зная, что негр останется негром, страховая компания может прикинуть по статистике заболеваний негров, по статистике продолжительности жизни негров на этом континенте. И это зная зная только что он негр. И среднестатистически будет права
I wonder how you can tell from a picture, and decomposed into sinusoids, what continent he is from and what stage of the disease he is in ;)...Psychics in sutdia ;) ? I'm just saying.
Good luck.
The theses are slightly different, but that's not the point. It's about the premise, the non-negotiable axioms: price is a random walk and then Gauss, the normal law and there we go. There's no such thing at all.
Here's a look at the article I linked to above, they only left this (key) thesis (IMHO of course) from the GER.
I wonder how you can tell from a picture, and decomposed into sinusoids, what continent he is from and what stage of the disease he is in ;)...Psychics in sutdia ;) ? I'm just saying.
>> Good luck.
Negroes are from two continents. You can tell them apart from the picture, they are different :)