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Influence of economical crises on weak efficiency of capital markets
Minařík, Štěpán ; Teplý, Petr (advisor) ; Vošvrda, Miloslav (referee)
In first part of my research a describe different ways of measuring weak efficiency of capital markets. In second part I explore economical crises in five various countries (Argentina, Malaysia, Mexico and Czech Republic) and I enounce hypothesis of effect of economical crises on weak capital market efficiency. In the end by using some tests (variance ratio test, run test, break event test) and discussion of results according to hypothesis I verify an availability of statement if crises has any influence on capital market weak efficiency. Powered by TCPDF (www.tcpdf.org)
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Yield Curve Modeling and the Effect of Macroeconomic Drivers: Dynamic Nelson-Siegel Approach
Patáková, Magdalena ; Šopov, Boril (advisor) ; Vošvrda, Miloslav (referee)
The thesis focuses on the yield curve modeling using the dynamic Nelson-Siegel approach. We propose two models of the yield curve and apply them on four currency areas - USD, EUR, GBP and CZK. At first, we distill the entire yield curve into the time-varying level, slope and curvature factors and estimate the parameters for individual currencies. Subsequently, we build a novel model investigating to what extent unobservable factors of the dynamic Nelson-Siegel model are determined by macroeconomic drivers. The main contribution of this thesis resides in the innovative approach to yield curve modeling with the application of advanced technical tools. Our primary objective was to increase the accuracy and the estimation power of the model. Moreover, we applied both models across different currency areas, which enabled us to compare the dynamics of the yield curves as well as the influence of the macroeconomic drivers. Interestingly, the results proved that both models we developed not only demonstrate strong validity, but also produce powerful estimates across all examined currencies. In addition, the incorporated macroeconomic factors contributed to reach higher precision of the modeling. JEL Classification: C51, C53, G17 Keywords: Nelson-Siegel, Kalman filter, Kalman smoother, Stace space formulation...
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Multifractal nature of financial markets and its relationship to market efficiency
Jeřábek, Jakub ; Vošvrda, Miloslav (advisor) ; Krištoufek, Ladislav (referee)
The thesis shows the relationship between the persistence in the financial markets returns and their efficiency. It interprets the efficient markets hypothesis and provides various time series models for the analysis of financial markets. The concept of long memory is broadly presented and two main types of methods to estimate long memory are analysed - time domain and frequency domain methods. A Monte Carlo study is used to compare the methods and selected estimators are then used on real world data - exchange rate and stock market series. There is no evidence of long memory in the returns but the stock market volatilities show clear signs of persistence.
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The Role of Advanced Option Pricing Techniques Empirical Tests on Neural Networks
Brejcha, Jiří ; Baruník, Jozef (advisor) ; Vošvrda, Miloslav (referee)
This thesis concerns with a comparison of two advanced option-pricing techniques applied on European-style DAX index options. Specifically, the study examines the performance of both the stochastic volatility model based on asymmetric nonlinear GARCH, which was proposed by Heston and Nandi (2000), and the artificial neural network, where the conventional Black-Scholes-Merton model serves as a benchmark. These option-pricing models are tested with the use of the dataset covering the period 3rd July 2006 - 30th October 2009 as well as of its two subsets labelled as "before crisis" and "in crisis" data where the breakthrough day is the 17th March 2008. Finding the most appropriate option-pricing method for the whole periods as well as for both the "before crisis" and the "in crisis" datasets is the main focus of this work. The first two chapters introduce core issues involved in option pricing, while the subsequent third section provides a theoretical background related to all of above-mentioned pricing methods. At the same time, the reader is provided with an overview of the theoretical frameworks of various nonlinear optimization techniques, i.e. descent gradient, quassi-Newton method, Backpropagation and Levenberg-Marquardt algorithm. The empirical part of the thesis then shows that none of the...
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Regime-Switching Models and Their Application in the Financial Markets
Fišerová, Tereza ; Vošvrda, Miloslav (advisor) ; Skuhrovec, Jiří (referee)
The thesis is divided into two parts. The theoretical part introduces the reader to the theory of ARCH-type models and their extensions which are represented by the Markov regime-switching models that allow for capturing of structural breaks in the data dynamics. In addition, the first part summarizes the current state of art. In the empirical part, the model of Klaassen (2002) is adopted to find evidence on the existence of two distinct volatility regimes in four of the Central European stock markets (Austria, the Czech Republic, Germany and Poland). The model is also used as a tool for economic crises identification. Analysis of the daily and weekly observations covering the period from January 3, 2000 to December 31, 2010 provides three remarkable results. First, MRS-GARCH(1,1) model is adequate for modelling stock market volatility in Central Europe. Second, the high volatility regime tends to be associated with a financial crisis. Third, the current crisis is exceptional in terms of its duration in comparison with previous works' conclusions.
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Stock Markets Analysis Using New Genetic Annealed Neural Network
Verner, Robert ; Baruník, Jozef (advisor) ; Vošvrda, Miloslav (referee)
The presented master thesis is focused on the stock markets returns analysis using a new type of neural network. First chapter of the thesis describes the underlying theory of the financial time series prediction, Efficient Market Hypothesis and conventional forecasting models. Following part illustrates biological framework, basic principles, functioning of neural networks, their architecture and several well-known learning algorithms such as Gradient descent, Levenberg-Marquardt algorithm or Conjugate gradient. It also mentions certain disadvantages which influence the performance and effectiveness of neural networks. Third chapter is devoted to two applied metaheuristic techniques, i.e. genetic algorithms and simulated annealing that were integrated into neural networks framework to eliminate above mentioned drawbacks. Next chapter describes details of presented hybrid network, whereas the last section is aimed at evaluation of overall results of all models. It shows that on the examined sample hybrid network clearly outperformed standard techniques as well as ordinary neural networks and in most cases achieved the least mean squared error among all explored methods. Keywords: stock returns analysis, neural networks, genetic algorithms, simulated annealing, hybrid networks JEL classification:...
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Stochastic Catastrophe Model Cusp
Voříšek, Jan ; Vošvrda, Miloslav (advisor) ; Lukáš, Ladislav (referee) ; Lachout, Petr (referee)
Title: Stochastic Catastrophe Model Cusp Author: Jan Voříšek Department: Department of Probability and Mathematical Statistics Supervisor: Prof. Ing. Miloslav Vošvrda, CSc., Czech Academy of Sciences, Institute of Information Theory and Automation Abstract: The goal of this thesis is to analyze the stochastic cusp model. This task is divided into two main topics. The first of them concentrates on the stationary density of the cusp model and statistical testing of its bimodality, where power and size of the proposed tests are simulated and compared with the dip test of unimodality. The second main topic deals with the transition density of the stochastic cusp model. Comparison of approximate maximum likelihood approach with traditional finite difference and numerical simulations indicates its advantage in terms of speed of estimation. An approximate Fisher information matrix of general stochastic process is derived. An application of the cusp model to the exchange rate with time-varying parameters is estimated, the extension of the cusp model into stochastic bimodality model is proposed, and the measure of probability of intrinsic crash of the cusp model is suggested. Keywords: stochastic cusp model, bimodality testing, transition density ap- proximation
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Fish wars : dynamic externality in fishing
Fiala, Tomáš ; Gregor, Martin (advisor) ; Vošvrda, Miloslav (referee)
The dramatic state of world fish stock is often attributed to the open-access nature of fishing grounds. In this thesis we investigate the consequences of unrestricted access to fisheries by adopting game theoretic framework. We describe the situation of fish appropriation by dynamic model and find some of its Nash equilibria. We show that one of the possible results of the nonexclusive nature of fisheries is overexploitation. Moreover, we find that other outcomes are possible as well. The tragedy of commons is, thus, not inevitable.
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Fractality of Stock Markets: A Comparative Study
Krištoufek, Ladislav ; Baruník, Jozef (advisor) ; Vošvrda, Miloslav (referee)
The main focus of the thesis is the introduction of new method for interpretation of fractality aspects of financial time series together with its application. We begin with description of various techniques of estimation of Hurst exponent - rescaled range, modified rescaled range and detrended fluctuation analysis. Further on, we present original theoretical results based on simulations of three mentioned procedures which have not been presented in literature yet. The results are then used in the new method of time-dependent Hurst exponent with confidence intervals developed in this thesis. Moreover, we show important advantage of using the mentioned techniques together to clearly distinguish between independent, trending, short-term dependent and long-term dependent properties of the time series. We eventually apply the proposed procedure on 13 different world stock indices and come to interesting results. To the author's best knowledge, the thesis presents the broadest application of timedependent Hurst exponent on stock indices yet.
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