a trading strategy based on Elliott Wave Theory - page 243
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Any approximation leads to the loss of information or to the extraction of essential information, at least in Pastukhov's case the approximation leads to interesting results.
And concerning the sense, of course, there is no great one, but in terms of taking ticks or minute bars in this matter this aspect seems to me to be essential. Although, I can imagine that the addiction to ticks may well exceed all reasonable arguments, which is actually nothing bad, except the pleasure of additional time spent with ticks in comparison with minutes....)))
And where did you find Pastukhov's approximation. As far as I understand his work, he does not do approximations at all. He searched for and found an adequate characteristic, with the help of which one can evaluate how arbitrage-like, and thus how profitable, the market is. However, the question of how to do this is beyond the scope of this dissertation. The strategy he cited is largely an illustration, so to say, an experimental proof of applicability of theoretical results, that is, in fact, it does not guarantee anything either.
And where did you find Pastukhov's approximation. As far as I understand his work, he doesn't do approximations at all. He was looking for and found an adequate characteristic, with the help of which one can evaluate how arbitrageous, and thus earning opportunity, the market is. However, the question of how to do this is beyond the scope of this dissertation. The strategy he cited is largely an illustration, so to say, an experimental proof of applicability of theoretical results, that is, in fact, it does not guarantee anything either.
In the section of the text, which is designated as 1.2, I don't know how to call it properly, it is shown that cagi and renko constructions are, in a sense, the best approximations of the function.
Unfortunately I haven't got through all subtleties myself, I don't know many designations etc., but, as I understand it, the ideological basis of the whole work is the approximation. If you look at the price series through statistical properties, as I understand it, you inevitably get a normal distribution, or something similar, and an inevitable consequence about market efficiency. To get around this, instead of statistical properties an approximation is considered. this is despite the fact that the research supervisor is the main randomizer in russia)))
Quote "the main aim of the paper is to build a model of the price behaviour of a financial asset...." and this is done by approximation. On the basis of this approximation, valutility is constructed, or rather the way it is measured. Valotality itself is a quite stable process characteristic and accordingly on the basis of its value a conclusion is made whether something can be won or not and respectively with what strategy, trend or counter-trend strategy.
The winning strategy is really quite theoretical, but the thesis gives a hint where to go next: into the patterns, i.e. something that was discussed at the beginning of this thread. Although I think you can try to do something at the level of this strategy.
Maybe you've read his articles instead of the thesis, it's true that the moment of approximation is somehow obscured there.
You are right, approximation as such is used in the paper. However, the words "in some sense" are key. The purpose of this approximation, as I understand it, is not the approximation itself, but to investigate, again, the statistical properties of price behaviour on some regular basis. And it is as a result of this research that it is possible to argue that for some markets this very normal distribution does not appear and therefore the market is not efficient, resulting in the possibility of arbitrage.
H-volatility introduced by Pastukhov is shown to be independent (for the arbitrage-free market) from the parameter H, which makes all approximations equal and H-volatility a fundamental and consistent market characteristic. And moreover we talk not so much about approximations, as about the use of Open and Close in Pastukhov's scheme. So if, as shown in the paper, the used constructions are the best approximations, then why should we go away from them to the worst ones. Is it possible to get something new or better in the trade in this case ?
In the persistent case, when the price series have regularities, and thus it is arbitrage, this coefficient is different from 2. If it is more than two, if I'm not confused, the trend strategy wins, and if it is less, then the anti-trend strategy wins.
Especially when all the works, such as price series models, are based on time decomposition. Pastukhov has shown that in terms of valatility measurements these breakdowns are equivalent, it means they can be combined, my conclusion so to speak. what was the starting point of this discussion.
What is the physical meaning of the result - valatility equals 2*H*N? And that is my interpretation - width is twice shorter than length on average. It means that the price has already broken the support line and is on the way up again. In the arbitrage case the length of the channel is slightly longer and that is where we make profit. If we take only blows then the width will decrease and the length will remain the same. (this is my intuitive guess). This is so to speak a possible benefit, a concrete one, that should be checked. In principle, it is always interesting to see how the screw that holds everything together in such an important matter is turned.
That is, you believe that if we take Close of the same series, the value calculated by Pastukhov's formula will decrease (and I agree with this) and it means that the H-volatility will decrease? And that would therefore give you an opportunity for arbitrage ? Well, well ...
As far as I guess, it's a comparison of two values with different dimensions (points and ticks, respectively), but you can't compare them that way... Or am I just not sure what you mean?
Here are the results of profitability calculations for "my" quotes and Yurich's quotes for the same period:
Thus, we can conclude that the strategy is dependent on the quotes provider! The TS will have to be "fine-tuned" according to its own brokerage company.
In general, the profitability of kagi on your ticks coincided with ours:
Which cannot but rejoice!
I would like to warn you right away that this is a very slippery slope, which nullifies all the efforts already made and puts the proposed idea on a par with other ideas used in the Forex market. "Sharpening" and "Fitting" in this case can be considered synonymous with fairly close results...
What is the point of doing tick analysis if we come to the same "broken trough" (the influence of the quotation provider) as we do when investigating other ways of forming packets of information (bars)?
I would like to warn you right away that this is a very slippery slope, which nullifies all the efforts already made and puts the proposed idea on a par with the rest of the ideas applied in Forex. "Sharpening" and "Fitting" in this case can be considered synonymous with fairly close results...
What is the point of doing tick analysis if we come to the same "broken trough" (the influence of the quotation provider) as we do when investigating other ways of forming packets of information (bars)?
Moreover, this contradicts the statement that H-volatility is a
a stable characteristic.
Obviously, the profitability of a TS depends on the presence and strength of "hidden" relationships (SP) between ticks, and its TS ability to identify and exploit these relationships. In its turn, a CB is a characteristic of a particular instrument, regardless of AC. But, the existing methods of filtering (MF) of streaming quotes of CA differ depending on the predilections of management. Thus, the profitability of TS depends on the stability in time of two integral characteristics: CB and MF. The stability of CB is proved in the thesis by Pastukhov, and the stability of MF for a particular VC is obvious, although there are certainly no guarantees!