Random Flow Theory and FOREX - page 56
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Simple pattern recognition is, as far as I understand, within a stationary process. And we have a non-stationary process, which means that patterns can change. Here either the methodology of pattern recognition must work in a non-stationary process (I have no idea), or it must take non-stationarity into account. The second is clearer.
Or are you assuming that the patterns are in areas of stationarity? But there is no such thing.
There is no stationarity! The process is initially non-stationary. What is a pattern? For example, Fibo, a waveform, any indicator, etc. Does this pattern bring profit or not? Sometimes it does. In what area is the pattern located? I do not know. Any trading system recognizes some pattern, which in the opinion of the TS author reasonably or unreasonably possesses some predictive properties. If this TS is built on the assumption of stationarity, then, in my opinion, it will lead to a loss of DEPO, because the market is not stationary. If the TS allows for adaptation (e.g. optimization), then it is closer to non-stationarity. But one should forget about stationarity as a basic postulate.
Already forgotten. No need for abstract words.
Optimisation according to you is taking into account the non-stationarity of the market?
Any adaptive systems techniques? What are we talking about? How to adapt without knowing the nature of non-stationarity?
For example, how do you adapt a stop loss without knowing how volatility will change over time?
Already forgotten. No need for abstract words.
Optimisation according to you is taking into account the non-stationarity of the market?
Any adaptive systems techniques? What are we talking about? How to adapt without knowing the nature of non-stationarity?
For example, how do you adapt a stop loss without knowing how volatility will change over time?
Glad, because the GER is already making my teeth hurt.
Example. The TS is built on a single swing. We were lucky, the tester has found a period and gained profit. On Sunday we optimize it again and see that it has another period. The experience shows that we cannot live like this for a long time on a wave. But Kravchuk suggests sliding, calculating their parameters using DSP methods. If we sit in the sleigh of "non-stationary dynamic systems", this is nothing new in science. There are approaches for systems that have parameters that in principle cannot be determined.
Volatility. In MT the SL at a fixed distance is a stationary process: variance is a constant. Experience shows that any other stop (Atr, Bollinger) is better than MT.
4=2+2. It could be 3+1, but at least 2+2 is correct.
P.S. It's been a few years since I graduated in botany. But something has settled in....
Or 1.25+2.25+0.5 (there are an infinite number of other variants) - you know nothing about the restrictions imposed on the components, and these restrictions do not exist only in theory.
As always everything is checked by a limit transition. If something raises doubts, you can try to reduce the situation to an obvious absurdity. For example: If we take a ball of corresponding mass and diameter as a horse model and assume that exposure to the same force - for example a track on the road - produces the same reaction: the body flies away to the same distance - does this mean that the equation of the ball adequately describes the surface of the horse?
>> Good luck with that.
Or 1.5+2.5 (there are an infinite number of variations) - you don't know anything about the limitations imposed on the components, and these limitations do not exist only in theory.
As always everything is checked by a limit transition. If something raises doubts, you can try to bring the situation to an obvious absurdity. For example like this: If we take a ball of appropriate mass as a horse model and consider that when the same force is applied - for example a track striking the road - the same reaction occurs: the body flies the same distance - does this mean that the equation of the ball adequately describes the surface of the horse?
Good luck.
NOOOOOOO course, we still need to know the history of the horse. But the law of conservation of momentum can be demonstrated adequately.
NONE of course, we still need to know the history of the horse. But the law of conservation of momentum can be demonstrated adequately.
That's what I'm talking about - only in a given location and for a given purpose. In this case - interpolation at a given location with an acceptable margin of error... no more.
>> Good luck.
That's what I'm talking about - only in a given location and for a given purpose. In this case - interpolation at a given location with an acceptable margin of error... no more.
Good luck.
That's what I'm saying, at least we had a nice talk :)
That's what I'm saying, at least we had a nice chat :)
:)
wow, that's a good one. Let me explain without allegories: with DFT you get a decomposition of the signal into its components, after which you can NOT say that it is NOT made up of them, because the sum of the components will give you the original signal. And don't go on about cause and effect here, it's arithmetic. The catch is that it will be an interpolation, and outside of the decomposition cutoff it will almost always carry no meaning.
P.S. Unlike the Negro - if you break it down into parts, then... no it's cruel, inhuman and unappetising.
Yes you should read, Chumazik, the discussion of Prival with L-Programmer, to which I gave a link. Read it, don't be lazy. It's not a bunch of suckers. Who are you trying to sell the PTU-schinky understanding of Fourier to here? I'm not going to repeat for everybody here 101+ times why Fourier is erroneous for non-periodic processes and why anybody who is parroting Fourier is just a stupid PTU-shin.
https://forum.mql4.com/ru/19762/page29#174504
" with DFT you get a decomposition of the signal into its components, after which you can NOT say that it is NOT made up of them, ... " - no, it isn't! It's bullshit! It's the biggest bullshit in science for 150+ years! You won't get shit! (That's what Lagrange, Laplace and his companions said.) You'll get an approximate approximation by the sum of multiples of harmonics, and that sum should be ETERNAL - in both directions. Where have you seen such a Fourier "spectrum" in real life? Where is there such an infinite spectrum? Where is the computer memory that would accommodate such an infinite spectrum? You see, Prival got quiet here, probably because he's got some books on FFT and realized that it's a real mess. Take it from him.
By the way, where is he? We're a couple of vocational school kids short of a couple of mathletes with a degree. Where's "Math Math"? We are here humping cool maths for them, while they are all basking in the sand in the Crimea. This is ridiculous!
Glad, because GER is already making my teeth hurt.
Example. The TS is built on a single swing. We were lucky, the tester found the period and got profit. On Sunday we optimize it again and see that it has another period. The experience shows that we cannot live like this for a long time on a wave. But Kravchuk suggests sliding, calculating their parameters using DSP methods. If we sit in the sleigh of "non-stationary dynamic systems", this is nothing new in science. There are approaches for systems that have parameters that in principle cannot be determined.
Volatility. In MT the SL at a fixed distance is a stationary process: variance is a constant. Experience shows that any other stop (Atr, Bollinger) is better than in MT.
>> I see. Stalemate. No questions, no answers. Then why join the discussion at all? You don't have to answer.