Market model: constant throughput - page 8
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Look, but a bunch of clever men, but how can you, periodically get together and start telling tales and fooling ordinary fellow citizens.
Compression is conventionally a function of distribution, but how do you think you can predict the price of all this?
Look, but a bunch of clever men, but how can you, periodically get together and start telling tales and fooling ordinary fellow citizens.
Compression is conventionally a function of distribution, but how do you think you can predict the price of all this?
I don't think you can - I wrote https://www.mql5.com/ru/forum/129152/page3 It's purely a topic for " Pure maths, physics, chemistry, etc.: brain-training exercises that have nothing to do with trading" :)
:D
As we can see, random BPs are shrinking more and more with the addition of new BPs. "Gold" has shown itself to be real.
Why random BPs are compressed (contain general information) is not clear from information theory. At the level of compression algorithms this process is more or less clear.
The random series contain no meaningful information. Pure white noise.
But real series contain non-trivial, meaningful information about market conditions. The very information that expert writers are hunting for. However, it must not only be obtained, but also interpreted correctly, and properly used. So forex will live another day. :-)
In my opinion, the work proves not so much that the flow of quotes is not the SB, as that the useful information is available.
Compression is conventionally a function of distribution, but how do you think to predict price from all this?
There are algorithms for what is called context modelling. They are not just functions of a distribution. The same PPM.
In addition, there are articles that have used the degree of compressibility of the data as one of the inputs to the prediction algorithm.
To me, the work proves not so much that the flow of quotes is not SB, but that useful information is available.
There are algorithms for what is called context modelling. They are not just functions of a distribution. The same PPM.
PPM was only looked at by eye: the results of sliding window compression are almost identical to LZMA.
Also, there are articles which used the degree of compressibility of the data as one of the inputs to the prediction algorithm.
As an aside: this is a paraphrase of the same thing.
I wouldn't say that. The information can also be useless. Admittedly, in order for the difference between SB compression and quote stream to be interpreted as useful information a profitable TS should be constructed. I think this is a bit easier than proving the usefulness of this information in general.
There are algorithms for what is called context modelling. They are not just functions of a distribution. The same PPM.
In addition, there are articles that have used the degree of data compressibility as one of the inputs to a prediction algorithm.
Well, if you (don't consider "you" to be rude please) are so in the loop, why didn't you tell Mr. Dickfix anything? What are you all like, three bags of mathematicians here on the forum and proud of it all, you start arguing on clever topics with clever words, but pardontez in the branch what? Compresses dickfix with what? Compresses what? Malevich.
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Ah, okay. Forget it.
Well, if you (don't consider "you" to be rude please) are so in the loop, why didn't you tell Mr. Dickfix anything? Why are you all so, three bags of mathematicians here on the forum and are proud of it all, you start arguing on clever topics with clever words, but pardontez in the branch what? Compresses dickfix with what? Compresses what? Malevich.
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Oh, come on. Forget it.
and talk? :) This is the kind of forum and audience that everyone wants to discover something that others haven't thought of :)