National Repository of Grey Literature 25 records found  beginprevious16 - 25  jump to record: Search took 0.00 seconds. 
Clouds and Hills Generation Using Fractal Geometry
Tůma, Petr ; Zuzaňák, Jiří (referee) ; Venera, Jiří (advisor)
This work is concerned with generation of landscape objects using fractal geometry. In this work is explained what the fractal is and terms associated with them. The other parts describe basic theoretical ideas and implementation of these algorithms. The Capital theme is generation of models clouds and hills in values of input parameters, their presentation and date media saved there. The project includes my algorithm extension for hills generation of course. At the conclusion of this work are summarized tendencies of next development and my results.
Analysis and Prediction of Foreign Exchange Markets by Chaotic Attractors and Neural Networks
Pekárek, Jan ; Dostál, Petr (referee) ; Budík, Jan (advisor)
This thesis deals with a complex analysis and prediction of foreign exchange markets. It uses advanced artificial intelligence methods, namely neural networks and chaos theory. It introduces unconventional approaches and methods of each of these areas, compares them and uses on a real problem. The core of this thesis is a comparison of several prediction models based on completely different principles and underlying theories. The outcome is then a selection of the most appropriate prediction model called NAR + H. The model is evaluated according to several criteria, the pros and cons are discussed and approximate expected profitability and risk are calculated. All analytical, prediction and partial algorithms are implemented in Matlab development environment and form a unified library of all used functions and scripts. It also may be considered as a secondary main outcome of the thesis.
The Use of Artificial Intelligence on Stock Market
Barjak, Maroš ; Budík, Jan (referee) ; Dostál, Petr (advisor)
The thesis deals with design, implementation and optimization of a model based on artificial intelligence and neural networks, which is able to predict future time series prices on a stock market. Main goal is to create an object oriented application for successful future trend prediction of financial derivatives with the use of cooperating methods such as Hurst exponent evaluation and automated market simulation.
The Use of Artificial Intelligence on Stock Market
Brnka, Radim ; Budík, Jan (referee) ; Dostál, Petr (advisor)
The thesis deals with the design and optimization of artificial neural networks (specifically nonlinear autoregressive networks) and their subsequent usage in predictive application of stock market time series.
Capital Asset Price Modelling: Concept VAPM
Kuklik, Robert G. ; Janda, Karel (advisor) ; Kodera, Jan (referee) ; Lukáš, Ladislav (referee)
The key objective of this thesis is the outline of an alternative capital market modeling framework, the Volatility Asset Pricing Model, VAPM, inspired by the innovative dual approach of Mandelbrot and Hudson using the method based on synthesis of two seemingly antagonistic factors -- the volatility of market prices and their serial dependence determining the capital markets' dynamics. The pilot tests of this model in various periods using the market index as well as a portfolio of selected securities delivered generally satisfactory results. Firstly, the work delivers a brief recapitulation regarding the concepts of a consumer/investor choice under general conditions of hypothetical certainty. Secondly, this outline is then followed by a description of the "classical" methodologies in the risky environment of uncertainty, with assessment of their corresponding key models, i.e. the CAPM, SIM, MIM, APTM, etc., notwithstanding results of the related testing approaches. Thirdly, this assessment is based on evaluation of the underlying doctrine of Efficient Market Hypothesis in relation to the so called Random Walk Model. Fourthly, in this context the work also offers a brief exposure to a few selected tests of these contraversial concepts. Fifthly, the main points of conteporary approaches such as the Fractal Dimension and the Hurst Exponent in the dynamic framework of information entropy are subsequently described as the theoretical tools leading to development of the abovementioned model VAPM. The major contribution of this thesis is considered its attempt to apply the abovementioned concepts in practice, with the intention to possibly inspire a further analytical research.
Evaluating the Efficient Market Hypothesis by means of isoquantile surfaces and the Hurst exponent
Ivanková, Kristýna ; Krištoufek, Ladislav ; Vošvrda, Miloslav
This article extends our previous work on applications of isoquantile (formerly isobar) surfaces to market analysis. The approach is applied to lagged returns of selected stock market indices and compared to various estimations of the Hurst exponent. We evaluate the Efficient Market hypothesis by means of the two aforementioned approaches for the ASPI, BET, BUX, JSX, NASDAQ, PX and S&P500 indices. The more does a time series satisfy the EMH, the closer it resembles Brownian motion. In this case isoquantile surfaces form a circle and the Hurst exponent approaches 1/2.
Hurst Exponent and Randomness in Time Series
Zeman, Martin ; Trešl, Jiří (advisor) ; Hušek, Roman (referee)
The main goal of this thesis is to test the ability of the Hurst exponent to recognise some processes with deterministic signal as nonrandom and to test the randomness of daily stock returns of three stocks traded in BCPP. Critical values to determine the critical region of a randomness hypothesis test were set for this purpose. Another goal of the thesis is the description of the Hurst exponent estimation by means of Rescaled Range Analysis and outline some problems accompanying this estimation if the Hurst exponent would be used as a randomness indicator. Within the frame of Rescaled Range Analysis was constructed another method that showed to be successful in recognising some series that contain deterministic signal.
Výběrové vlastnosti Odhadů Hurstova exponentu na datech s težkými chvosty
Baruník, Jozef ; Krištoufek, Ladislav
We show how the sampling properties of Hurst exponent methods of estimation change with the presence of heavy tails in the data.
Application of R/S Analysis at Financial Markets
Vilhanová, Vanda ; Trešl, Jiří (advisor) ; Kodera, Jan (referee)
The aim of this graduation thesis is the descriptiton of R/S analysis and it's aplication on chosen time series of share prices and exchange rates. Some main models of financial time series will be mentioned in the second chapter. There will described basic linear models of stationary and non stationary time series and models of volatility. Then we will focus on the main theme of this thesis, R/S analysis. The algorithm of R/S analysis and the interpretation of the Hurst exponent will be described in the forth chapter. In the fifth chapter, the R/S analysis will by applied on real data sets. There will be two data sest of share prices of Telefónica O2 and Philip Morris and two data sets of exchange rates CZK/EUR and CZK/USD. The results will be interpreted and compared.
Fractal Market Hypothesis and R/S analysis of the Czech capital market
Barkhanskyy, Kostyantyn ; Korbel, Jiří (advisor)
This work is aimed at the modern theory of the capital market -- Fractal Market Hypothesis. The content of my work includes both basic theoretical assumptions of the hypothesis and aplication of R/S analysis on the Czech capital market. The goal of this bachelor's thesis is to confirm Czech capital market nonlinear structure with determination it's fractal features and set the memory period by R/S analysis output.

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