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EN
The article presents theoretical basis and practical applications of selected quantity methods that can be used in modeling financial time series, where elements of Elliott theory and fractal geometry are included. The aim of this work is to present models to support the investor in decision making, which includes new market tendencies. The process of investing into financial markets is a dynamic process depending on frequent changes, that direction and impact is difficult to predict in the long periods of time. This work shows theoretical basis of used methods and results of carried out empirical analyses.
EN
The aim of this work is to present models to support an investor in decision making, which includes new market tendencies. The process of investing into financial markets is a dynamic process depending on frequent changes, witch direction and impact is difficult to predict in the long periods of time. The article presents theoretical basis and practical applications of selected quantity methods that can be used in building investing strategy, where elements of fractal analyses and of classical statistics theories are included. The new approach to create a model of securities, based on fractal analysis with Hölder function is an alternative to classical models. The article consists of two basic parts. The first presents formulas and references as well as applied methods for data analyses; the other is of empiric character.
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EN
This article deals with problem of investment risk assessment by exploiting fractal dimension. In the first part of the article author presents the idea of treating fractal dimension of logarithmic cumulated returns as a risk measure. The relationship between fractal dimension and the riskiness of investment in case of its horizon tending to infinity is introduced. In the last part of the article results of empirical analysis confirming conclusions described are presented.
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