a trading strategy based on Elliott Wave Theory - page 126
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There is a rather serious inaccuracy in the postulates in the book (as far as I can see from the published page) (IMHO: a misunderstanding of the process). The point is that PRICE IS NOT A FUNCTION OF TIME. At any rate, it is impossible to prove it conclusively.
In that statement that I have described, the approach is built on the assumption that it is impossible to define reliably a function of what parameter the price is. Another assumption is that the price is a function of a superposition of external factors. We are trying to approximate changes in price and relate them to changes in time which is not the same thing. In other words, time is not an independent (variable) variable, it depends on several factors. It means some internal time of the system at the moment of which the event takes place. An external observer observing all this from outside in its system of coordinates can draw absolutely incorrect conclusions. For example: we stand on a road and count the number of cars that have passed in either direction. Of course on the basis of some information we can say that the number of cars passing on the track is a function of time but is it so? I specially gave an example for which the absurdity is obvious. It's more complicated than that ;).
Took the scanner down 2 more pages in continuation of this page. There's the end of the equation output. There are 2 pages at 250 kb - https://c.mql5.com/mql4/forum/2006/08/prodolzenie.zip
About ways of solving the forward and backward problem. But only in a general way.
There is a rather serious inaccuracy in the postulates in the book (as far as I can see from the published page) (IMHO: a misunderstanding of the process). The point is that PRICE IS NOT A FUNCTION OF TIME. At any rate, it is impossible to prove it conclusively.
In that statement that I have described, the approach is built on the assumption that it is impossible to define reliably a function of what parameter the price is. Another assumption is that the price is a function of a superposition of external factors. We are trying to approximate changes in price and relate them to changes in time which is not the same thing. In other words, time is not an independent (variable) variable, it depends on several factors. It means some internal time of the system at the moment of which the event takes place. An external observer observing all this from outside in its system of coordinates can draw absolutely incorrect conclusions. For example: we stand on a road and count the number of cars that have passed in either direction. Of course on the basis of some information we can say that the number of cars passing on the track is a function of time but is it so? I specially gave an example for which the absurdity is obvious. Everything is more complicated here ;).
Regards, Vladislav.
Good luck and good trends.
Hello, Vladislav.
I will add one more quote to your post:
"The application of a single time scale for all analytical purposes is impossible due to the extensibility
of the concept of time itself. According to Einstein's Theory of Relativity, time is not absolute but relative:
it depends on the speed of the observer's movement in space. In Elliott Wave Theory (as applied to
the behaviour of markets) time depends on the psychology of crowds. Time stretches and compresses under the influence of the moods of
crowd, driven by mass hopes and fears of financial and economic nature. This manifests itself in the stock market
as a correlation of supply and demand forces. That is why, considering the dynamic and fractal
nature of price movements, it is impossible to use one price scale for all purposes of analysis.
Price figures of all scales, big and small, are formed on the market simultaneously".
Sincerely,
Alexey
In my opinion, the price really won't depend on time directly. Rather, it is the functionality, the components of which (of which there are many) will in turn already depend on time on some "attachment". All in all it turns out to be quite an impressive astrolabe, which is not much to solve. Although, there may be exceptions for goods, the pricing of which is strongly influenced by seasonality, and various natural cyclical processes (droughts, floods, for example) i.e. time. Apparently the book is also designed for "marketing professionals" who need to predict how much galoshes will cost and whether it makes sense to build another 38 shops and expand production. Of course my opinion of the book is premature. For galoshes it can probably be calculated in an abbreviated version.
As for the potential energy of the channel, and it does not depend on time in any way, but that is my understanding.
As for stretching or compressing time in a crowd - that's strong and requires a trained and expanded mind. :о))) Have read Eliot's wave theory from http://www.elliotwave.com/ and other available sources, but haven't found that. I'm afraid Einstein has nothing to do with it either. Rather it has more to do with economics.
As for the fractality of the market, I agree. Alex, if by fractality you mean the movement, for example, from M30 period to H1, I'm afraid it isn't so. At least, the nature of fractality in my understanding is not exactly that. What we see - Open, High, Low, Close are values of the same BID, taken according to certain rules, in which time is directly involved. Take a complex mechanical system and measure its parameters according to the same principle as the periods are formed on forex. And I'm afraid that your further calculations will become very complicated.
Guys, Vladislav is messing around :-))
Pouring oil on the fire that has been flaring up in this thread around his strategy.
IMHO the price is as much a function of time as it is of time. If only because the events, on which the price depends, develop in time and are related to it. Here I completely agree with grasn. The only question is what to do about it.
Vladislav, for example, used integral methods in his approach, which allowed him to solve this problem. And as far as I understand this is what he wanted to hint at in his post. So for anyone who wants to replicate this strategy, there is a reason to close this particular gap in their education.
Here is such a practical point. I am now practicing entries on history. Actually, there are many variants of inputs and inputs may depend on details of method implementation (which is different for everyone). But in order to compare the test results, we need to standardize the exits. And here it's as if the method itself gives possibilities that don't depend on implementation details. For example, I now use as a stop an exit beyond 3.5 RMS and as a profit an exit beyond 1.5 RMS (on the other side of the middle channel line) when determining the quality of entries. If anyone has their own views on this, it would be interesting to know.
Regarding market fractality, I agree. Alex, if by fractality you mean transition, for example, from M30 period to H1. At least, the nature of fractality in my understanding is not exactly that. What we see - Open, High, Low, Close are values of the same BID, taken according to certain rules, in which time is directly involved. Take a complex mechanical system and measure its parameters according to the same principle as the periods are formed on forex. And I'm afraid your further calculations will get very complicated.
I wonder what the nature of fractality is in your opinion? I'm afraid that everyone understands market fractality differently, even Bill Williams has his own views on the subject, so there is a difference of opinion. So what are really FRACTALS?
A little digression into history:
The birth of fractal geometry is usually attributed to the 1977 publication of Mandelbrot's book `The Fractal Geometry of Nature'.
Benoit Mandelbrot was the first to formulate a definition of the fractal that describes it quite precisely:
"Why is geometry often called cold and dry? One reason is its inability to describe the shape of a cloud, a mountain, a tree or a seashore. Clouds are not spheres, mountains are not cones, shores are not circles and the bark of a tree is not smooth and lightning does not travel in a straight line...
Nature demonstrates not just a higher degree, but a very different level of complexity. The set of scales for measuring the length of objects is infinitely large and capable of accommodating an infinite number of needs. The existence of these objects challenges us, inclining us to study their forms.
Mathematicians have neglected this challenge, moreover they have wanted to escape from nature by inventing theories unrelated to anything that we can see or feel". Mandelbrot explains the notion of a fractal as a kind of entity, self-similar or selfaffine in one sense or another, i.e. a small part of a fractal contains information about the whole fractal. Only such explanation allows to cover wide set of objects worthy to be called fractals without visible annoying gaps. Any attempt to give a stricter definition cuts off some rather capacious class of objects, unacceptably narrowing the world of fractals. The simplest fractals, such as Kantor dust, von Koch snowflakes, Sierpinski sponge and carpet, dragon curves, Peano and Hilbert curves and many others, have regular geometrically regular structure. Each fragment of such geometrically regular fractal exactly repeats the whole structure. Examples of fractals are boundary and shorelines, pores in bread, holes in some varieties of cheese, particles in powders, etc.
Artificial products created by man, such as communication languages, are the result of processes in the left hemisphere of the brain and therefore represent linear and digital systems. We have created our trading systems in the same way that we created communication languages in our time. Since language is often helpless in describing nature, linear trading systems do not meet our expectations when analysing the market for profit. With the fractal approach, chaos ceases to be synonymous with disorder and takes on a subtle structure.
Classification of fractals.
Geometric fractals.
Fractals of this class are the most visible. In two dimensional case they are made with the help of some broken line (or surface in three dimensional case), called a generator. In one step of the algorithm, each of the segments composing the broken line is replaced by a generator broken line, at an appropriate scale. As a result of infinitely repeating this procedure, a geometric fractal is obtained.
SEE FIGURE 1.
[img]https://c.mql5.com/mql4/forum/2006/08/%D0%E8%F1.1_5.GIF [/img]
Construction of a triadic Koch.
Consider one such fractal object, the triadic Koch curve. The construction of the curve starts with a segment of unit length - this is the 0th generation of the Koch curve. Then, each link (one segment in the zero generation) is replaced by the forming element denoted by n=1 in the figure. This replacement results in the next generation of the Koch curve. The 1st generation is a curve with four straight links, each with length 1/3. To obtain the 3rd generation, we proceed in the same manner - each link is replaced by a reduced formative element. Thus, to obtain each subsequent generation, all links of the previous generation have to be replaced by a reduced formative element. The curve of n-th generation at any finite n is called pre-fractal. The figure represents five generations of the curve. When n tends to infinity the Koch curve becomes a fractal object.
Construction of the Harter-Heitway "dragon".
To obtain another fractal object we have to change the rules of construction. Let the forming element be two equal segments connected at right angles. In zero generation replace the unit segment with this formative element so that the angle is on top. This substitution results in an offset of the middle of the link. The following generations follow the rule: the first leftmost link is replaced with a formative element so that the middle of the link is shifted to the left of the movement direction, and when replacing the following links, the directions of shift of the segments' midpoints must alternate. The figure shows several first generations and the 11th generation of the curve built according to the above principle. The limit fractal curve (with n tending to infinity) is called the Harter-Heitway dragon .
Algebraic fractals.
This is the largest group of fractals. They are obtained by non-linear processes in n-dimensional spaces. Two dimensional processes are the most studied.
Nonlinear dynamical systems have several stable states. The state the dynamic system finds itself in after a certain number of iterations depends on its initial state. So every stable state (or as they say - an attractor) has some area of initial states from which the system necessarily gets to the considered final states. Thus, the phase space of the system is divided into regions of attractor attraction. If the phase space is two-dimensional, then coloring the attractor regions with different colours will produce a colour phase portrait of this system (iterative process). By varying the algorithm for colour selection, complex fractal patterns with bizarre multicoloured patterns can be obtained.
Using primitive algorithms, it is possible to generate very complex non-trivial structures like the Mandelbrot set.
SEE FIGURE 2.
[img]https://c.mql5.com/mql4/forum/2006/08/%D0%E8%F1.2_1.GIF [/img]
The algorithm of Mandelbrot set is simple enough, it is based on iterative expression: Z[i+1] = Z[i] * Z[i] + C, where Zi and C are complex variables. Iterations are performed for each starting point C of a rectangular or square area, a subset of the complex plane. The iteration process continues until Z[i] leaves the circle of radius 2, the centre of which lies at (0,0), (which means that the attractor of the dynamical system is at infinity), or until after a sufficiently large number of iterations (for example 200-500) Z[i] converges to some point of the circle. Depending on the number of iterations during which Z[i] remains inside the circle, you can set the colour of point C (if Z[i] remains inside the circle during a sufficiently large number of iterations, the iteration process stops and that point of the image is colored black).
The above algorithm gives an approximation to the so-called Mandelbrot set. The Mandelbrot set belongs to the points which, for an infinite number of iterations, do not go to infinity (points which are black). The points belonging to the boundary of the set (it is there that complex structures appear) go to infinity for a finite number of iterations while the points lying outside the set go to infinity after a few iterations (white background).
Stochastic fractals.
A typical representative of this class of fractals is Plasma.
SEE FIGURE 3.
[img]https://c.mql5.com/mql4/forum/2006/08/%D0%E8%F1.3_1.GIF [/img]
To the right is the transformed Dow Jones index, it is depicted as a stochastic fractal with colour gradation using the plasma representation.
Iterated function systems.
This is coding of images using fractals.
Fractal Geometry and Markets.
Wherever chaos, turbulence, living systems and disorder meet, fractal geometry is applicable.
As mentioned above, fractal means fractal dimension.
SEE FIGURE 4.
[img]https://c.mql5.com/mql4/forum/2006/08/%D0%E8%F1.4_1.GIF [/img]
The figure shows a computer-generated fractal tree. Each branch of the tree is split into two to create a fractal dome in the end. The illustration on the left represents six iterations or branches. In the fifteenth iteration (right) the tree takes on a more realistic appearance. Recursive modelling can generate different kinds of trees by changing the fractal number. Fractal trees illustrate the fact that fractal geometry is a measure of change.
Applications of fractals.
First of all, fractals are an area of amazing mathematical art, where the simplest formulas and algorithms are used to create pictures of extraordinary beauty and complexity. Fractals constructed by nature make up landscapes pleasing to our eye.
SEE FIGURE 5.
[img]https://c.mql5.com/mql4/forum/2006/08/%D0%E8%F1.5_1.GIF [/img]
Natural fractal processes.
SEE FIGURE 6.
[img]https://c.mql5.com/mql4/forum/2006/08/%D0%E8%F1.6_2.GIF [/img]
Example of processes occurring in nature: appearance of frost patterns on windows, formation of various kinds of fungi, metal corrosion process, etc., etc.
Quite accidentally I have paid attention to some similarity of self-similar fractals modelled on computer with "mysterious" circles on fields,
Computer-modelled self-similar fractals, SEE FIGURE 7.
[img]https://c.mql5.com/mql4/forum/2006/08/%D0%E8%F1.7_1.GIF [/img]
Photo of figures found in wheat and corn fields around the world.
These photos were taken from an aeroplane, this is to represent their real scale.
See FIGURES 8, 9 and 10.
[img]https://c.mql5.com/mql4/forum/2006/08/%D0%E8%F1.8_3.GIF [/img]
[img]https://c.mql5.com/mql4/forum/2006/08/%F0%E8%F1.9.GIF [/img]
[img]https://c.mql5.com/mql4/forum/2006/08/%F0%E8%F1.10.GIF [/img]
The figures in the margins are not made by humans. At the moment the number of formations fixed in the world has exceeded ten thousand.
Complex and large-scale figures, appear almost within the boundaries of settlements in a matter of seconds, and without any witnesses.
12 For whoever has, to him will be given, and he will have abundance, but whoever does not have, from him will be taken away even that which he has;
13 Therefore I speak to them in parables, because seeing they do not see, and hearing they do not hear, neither do they understand;
14 And the prophecy of Isaiah is fulfilled concerning them, which says, 'By hearing you shall hear, and shall not understand; and by eyes shall you look, and shall not see'.
I know it's off-topic, but maybe someone would be interested, see link.
[img] http://ufolog.nm.ru/krug1.htm [/img]