NATURAL INTELLIGENCE as the basis of a trading system - page 2
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My question is formulated as follows:
Is it possible to train the brain (I say exaggeratedly) on historical data for predictive purposes? That is, learning what many programmers and mathematicians try to teach the ANN. Learning by the same methods (but on a different plane).
There are several forms of consciousness: physical, astral, mental, buddhic, neurvanic.
Only the first three forms of consciousness can be adequately considered; higher forms can only be named.
Each form of consciousness is based on a relationship with one's body and a relationship with the corresponding level of reality.
There are physical, astral, mental, etc. levels of reality. Each higher level of reality is a physical (cosmic) basis, a building material for the lower levels of reality. For example, the physical level is based on the astral level, which in turn is based on the mental level, etc.
Every normal person has a physical consciousness and adequately perceives his/her body. Physical consciousness is limited (fundamentally, by its essence) to a certain set of notions, within the framework of which one establishes relations with the physical reality.
The astral level of reality is a set of feelings and emotions. This definition is very unusual, so it may seem fictitious at first glance, but in fact feelings and emotions are part of the universe and are part of the universal objective reality.
Astral consciousness is one in which one is not aware of one's physical body and (depending on one's experience) perceives astral objects - the sensual, emotional side of them - to some extent adequately. Astral consciousness is very unstable. awareness of the physical body during astral awareness leads to transition to physical consciousness (99.9% of cases) or to mental consciousness (under condition of full control of the emotions, which is already a manifestation of the properties of mental consciousness).
Mental reality is thoughts and intentions. A man who has attained mental consciousness completely overcomes the contradictions between his mind and mental reality, and can freely (outside the constraints of physical consciousness and physical reality) perform any action at the physical level of reality (over physical reality). Such a high level of consciousness has not been achieved by almost anyone.
Anticipation is possible in astral consciousness (about 1-30 days), but astral consciousness is as if in antiphase with physical consciousness. I.e. in order to use the knowledge gained during AS, it is necessary to return to FS, but at the first signs of manifestation of FS the memory of the experience of AS immediately fades away (like sleep in the morning). For confident anticipation one needs MS, in which one adequately perceives his physical body, which can act as well as any other physical object.
If a person has achieved MS, then all sorts of nonsense like foreknowledge on Forex, for him are not even a small game, but simply the state of the environment, i.e. it is accessible in the same way as for a common man looking at a drawing on the fence or reading (direct perception). A person who has attained MS has qualitatively greater possibilities at his/her disposal.
Transition to a higher form of consciousness is achieved by breaking the contradictions with the environment and one's physical body. Closer, astral consciousness is more possible, because during sleep a man naturally breaks ties with his physical body (does not perceive it in any way). And the transition to mental consciousness is possible only by completely severing the contradictions with one's emotions and feelings (control over them). This means that before thinking about a transition to the mental consciousness, one has to completely get rid of the interests at the level of the physical consciousness (in the CC's terminology - clean the tonal). This process is similar to growing up. Before growing up (acquiring a new set of notions and values) a person has to lose interest in the current set of values and perceptions of the universe. For example, before one can drive a motorbike, one has to lose interest in the bucket with a spatula in the familiar sandbox.
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So...
In order to get confident results in forex, you have to go into mental consciousness. But an ordinary person cannot do it, because you have to give up (all!) your current interests (including and above all earnings on Forex).
It is not even money that we want in the long run, but a feeling of happiness. With physical consciousness this is possible only if both possibilities and properties of the physical consciousness itself are used to achieve happiness. Theoretically, if one completely restricts access of all superfluous information to the brain of the physical body, the brain will start working within the established limits and may produce some results. But those results will be less, the more extraneous information (thoughts of how to spend the earned income and feelings of earnings and failures) will be.
If we put it in simple terms, it would be to sit in front of the monitor 24 hours a day, do not think about anything else (forget about family, work, spring, friends, plans, stop worrying about your appearance, food, health ...).
You may get what you want now, but will you want what you get later, at that price...
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Positive.
Learning. To read, to be interested, to think, to develop.
The short answer is Yes. For the long answer, see Schwager's book The New Market Wizards. Conversations with the best traders in America. Part three. The silence of the "Turtles".
Secondly, I probably didn't phrase my question accurately enough.
I am interested in formalizing (I do not mean programming) the brain learning algorithm through visualization of data in its direct representation (in this case, in graphical form).
Let me cite as an example a quote from the book "Neurocomputer Engineering: Theory and Practice" by F. Wasserman:
"Cognitron and neocognitron.
People solve complex pattern recognition problems with disconcerting ease. A two year old child discerns without apparent effort the thousands of faces and other objects that make up its environment, despite changes in distance, rotation, perspective and lighting.
It might seem that the study of these innate abilities should make it a simple task to develop a computer that replicates the recognition abilities of humans. Nothing could be further from the truth. The similarities and differences in patterns that are obvious to humans have so far baffled even the most sophisticated computer recognition systems. Countless important applications in which computers can replace humans in dangerous, boring or unpleasant jobs thus remain beyond their current capabilities.
Computer pattern recognition is more of an art; the science is limited to the availability of a few techniques with relatively little use in practice. An engineer designing a generic pattern recognition system usually starts with print recognition. These techniques are often inadequate to the task, and the developer's efforts are quickly reduced to developing algorithms that are narrowly specific to the task at hand.
Usually the goal of designing pattern recognition systems is to optimize its performance over a sample set of patterns. Very often the developer completes this task by finding a new, approximately similar image, which leads to unsuccessful completion of algorithms. This process can go on indefinitely, never resulting in a stable solution sufficient to replicate the human perceptual process evaluating the quality of the system's functioning.
Fortunately, we have existing evidence that the problem can be solved: this is the human perceptual system. Given the limited successes achieved by the pursuit of self-invention, it seems quite logical to go back to biological models (exactly biological models, Implx) and try to determine how they function so well... (and not only define them, but use them for certain purposes, Implx)."
Although the text cited refers to ANNs and methods of their development (in particular biological models are seen as the object of study), there is a thought in the text regarding the human brain and its capabilities. If this paper considers the brain as a model for modelling (however, not fully modelled and unlikely to be able to do so any time soon (due to its complexity)), then why not take advantage of the potential it offers?
Thanks.
Rebus- what is meant by "two-level logic"? That the neuron either works or it doesn't?
Unfortunately (or vice versa :), neural networks have not found a decent application for a very simple reason. The fact is that recent research has shown that the human brain neuron works according to a five-level logic. Earlier it was believed (and it formed a basis for development of NS) that logic is two-level. But only spinal cord works with two-level logic. As a result, all hitherto designed computers will forever remain at the level of spinal cord intelligence. The same applies to two-level NS.
So let's wait for five-level developments :)
But it is still useful to read books :)
Is it possible to train the brain (I say exaggeratedly) on historical data for predictive purposes? That is, learning what many programmers and mathematicians try to teach the ANN. Training with the same methods (but on a different plane).
Exactly. If you read the first sentence carefully. There's a comparison with the ANN. Then the counter-question is: Which brain to train? The brain or the spinal cord? That's exactly what I mean. Just taking a broader view :)
The basic learning algorithm is repetition.
If this is the main algorithm, what are the "non-mainstream" algorithms?
The basic learning algorithm is repetition.
If this is the main algorithm, what are the "non-mainstream" algorithms?
Let's start by using human language)) I understand that you want to learn how to memorize long numerical series?
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Let's start by using human language)) I understand that you want to learn how to memorise long number series?
Considering the wording of your login and the graphic representation of your avatar, we can conclude that you might be a programmer. Then I don't understand why I express myself in a "non-human language", using such common notions as "formalization", "algorithm". Who, if not you, should be crystal clear about all this?
I have created this theme exclusively from consideration of an opportunity to consider a question of applicability of theoretical knowledge in practice for the purpose of finding truth (or approaching to it) by... (by what, you know yourself).
About "learning to memorise long numerical series". No. Unfortunately, memorising numbers can do little (in relation to our topic), though maybe I'm wrong.
I am not referring to the ability to memorise numbers, but to the ability to approximate number series. However, it is unlikely that a sequence of numbers in its direct representation, can be approximated by the brain. Some kind of graphic representation of numbers is necessary, because for system of perception of man initially it seems more natural that he learned to know through visual images from his childhood. Numbers do not carry any additional information in their graphical representation (I mean unchanging printed text and one symbol), and learning to extract this information from a series of numbers, in which, depending on the series itself, this additional information certainly exists, is likely to be difficult.
Therefore a more promising method, it seems to me, is the approximation of the graphical representation of numbers.
Again I will quote from a famous book:
"In the visual cortex, nodes have been found to respond to elements such as lines and angles of a certain orientation. At higher levels nodes respond to more complex and abstract images such as circles, triangles and rectangles. At still higher levels the degree of abstraction increases until nodes responding to faces and complex shapes are identified. In general, nodes at higher levels receive input from a group of low-level nodes and hence respond to a wider area of the visual field. The responses of higher level nodes are less position dependent and more resistant to distortion..."
Visual perception of specifically graphical information is, in my opinion, the most natural to the human nervous system. Another issue is the way in which this information is approximated.
Thank you.
In my opinion, successful trading does not require approximation of data, but identification of moments in which the probability of a successful entry is higher than 50%. A successful entry is understood as obtaining a positive expected payoff in a series of trials, i.e., 80/20 systems are not always (or rather rarely) profitable.
How do you identify points at which the probability of a successful entry is above 50%? Is it not by approximation and then applying the results? If not, then there is an assumption that you are using stereotypes or something similar (opinions, guesses, hypotheses, speculations, judgments, views, assumptions, theories, attitudes, beliefs, teachings, concepts, doctrines, positions, principles, points of view, etc. (I mean someone else's, not my own)) for successful trading. Then the concept of successful trading cannot arise in principle (in my humble opinion).