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Основная цель данного исследования заключается в daily forex analysis predictions методов прогнозирования будущих цен финансовых активов, основанных на концепции фрактальной структуры и долгосрочной памяти финансовых рынков.

Фракталы на финансовых рынках интерпретируются либо как инвесторы с различными инвестиционными горизонтами, либо как различные конфигурации движения прошлых цен на графике. В данной статье рассматривается фрактальная структура финансовых рынков, нелинейные методы анализа финансовых рынков, новые подходы к прогнозированию цен daily forex analysis predictions активов, которые позволяют устранить недостатки линейной парадигмы.

Результаты исследования, проводимые на валютном рынке и рынке ценных бумаг, подтвердили наличие долгосрочной памяти финансовых рынков.

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Ключевые слова: Fractals in the financial markets are interpreted either as investors with different investment horizons or as a configuration of the price movement on chart. This article examines the fractal structure of financial markets, nonlinear methods of analysis of financial markets, plasticity and long-term memory to long-term investment horizons of financial markets, fractal analysis of financial markets, daily forex analysis predictions approaches to forecast prices of financial assets, which eliminate shortcomings of the linear paradigm.

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The results of research conducted in the foreign exchange market and securities market, confirmed the existence of long-term memory of the financial markets. Introduction Today, the methods for the analysis and prediction of financial market behavior are borrowed from neuroeconomics and have become extremely popular. Many economists believe neuroeconomics as an interdisciplinary field in its broadest sense is a neurobiology of decision-making decision neuroscience [1].

It combines neuroscience, economics, psychology, and other disciplines to form the basis of new knowledge about mechanisms of decision-making and helps to simulate the behavior of humans and animals.


An analogue of a neuron in the financial market is a fractal — the price of a financial asset. Therefore, from the mathematic point of view, fractal is a plurality with a fractional fractal dimension.

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The fractal dimension characterizes the way how an object or a time series fills space. In addition, it describes the structure of an object when the zoom factor is changing or while zooming the subject. Under zoom factor escalating is meant. For physical or geometric fractals, such conversion occurs in space.

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The fractal dimension of the time series measures how rugged is the time series itself. The time series of asset prices is a jagged line.

It is not one-dimensional as it is not a direct line; simultaneously, it is not two-dimensional since it does not fill the plane daily forex analysis predictions. Thus, the dimension of a financial range is located between figure one and two.

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According to expectations, the fractal dimension of a random time series is золотой клон как быстро заработать. Fractal is an attractor a limit and a goal for the movement of the chaotic system. Why are these notions identical? In a strange attractor as well daily forex analysis predictions in a fractal while increasing it reveals more details i.

As much as the size of the attractor is changed it is always in the same proportion.

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The time series is considered fractal when it exhibits a statistical self-similarity; daily forex analysis predictions, this property is enjoyed by all ranks of financial assets quotations. The self-similarity could be seen during reading ordinary graphs.

For instance, it is impossible to distinguish minute, hourly, and daily charts of any product because they daily forex analysis predictions similar and monotonous.

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An additional idea rooted in fractality regards non-integer dimensions which are usually referred to as a one-dimensional, two-dimensional, or three-dimensional integer world. However, there may be a non-integer dimension such as 2.

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Mandelbrot called such dimensions fractals. In order to describe complex objects, other measurements should exist.

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Such measurement of incorrect fractal shapes introduces the concept of a fractal dimension. From the point of view of classical Euclidean geometry, a crumpled sheet of paper will be a three-dimensional sphere. However, in reality it is still only a two-dimensional sheet of paper even if it is crumpled. Hence, it can be assumed that the new object will have a dimension greater than two but less than three.

It hardly fits the Euclidean geometry, but can be well described by fractal geometry which argues that the new object will be located in the fractal dimension equal approximately to 2.

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The physical meaning of this dimension is very simple in that in the classical three-dimensional space, some parts remain empty because of gaps and holes naturally presented in a crumpled sheet of paper. When applying this theory to the financial markets, we can assume that markets are characterized by various degrees of daily forex analysis predictions defined as the capacity to take and retain form.

This definition means that markets can be molded to various degrees in terms of their shapes and functions, and that they are able, to various daily forex analysis predictions to retain such changes in their properties even after the molding effort ceases. Thus, plasticity is a dual construct since it requires both fluidity defined as the capacity to take form, and stability defined as the capacity to retain form.

All markets are plastic even though their degree of plasticity can change. Therefore, the interplay between fluidity and stability helps us understand market dynamics in more detail.

There are two important consequences of the plastic character of markets as defined above. First, the ability to retain form allows markets to give form to other entities by, for example, affecting the shape of a particular exchange object, the mode of a specific economic exchange, or the characteristics of an exchange agent.

Second, the ability to take form allows markets to host multiple forms simultaneously. It was suggested by the hydrologist Harold Edwin Hurst who in the midth century worked at the Nile dam project.

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The Hurst index could be also used as a measure of volatility of the data series. If to deal with market as a stochastic process, in this case the use of standard deviation as the main characteristics of risk values is justifiable enough. If to admit that market is not stochastic, but chaotic, fractal dimension as a measure of non-linearity of price movements is much better suited. Why does an effect of the price inertia in relation to the previous motion appear in the financial markets?

This fact can be explained based on the psychology of human memory.

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The Hurst index of over 0. Those who calculate the Hurst index, based on market prices, often stand the arising question of what ranks to explore — data series or data changes. For instance, it could be the logarithm of the current value to the previous one which is usually used in the analysis of market quotations. Analysis has shown that the normalized logarithmic scale of random series of changes is much smaller than the scale of the normalized logarithmic linear rising or falling series changes.

As the result, the Hurst index calculated on the logarithms of linear series changes reach huge quantities.

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