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Cost planning of PPP projects in the Czech Republic
Ehrenberger, Marek ; Teplý, Petr (advisor) ; Chytilová, Julie (referee)
English The thesis explores the topic of cost planning of Public-Private-Partnership (PPP) projects in the Czech Republic, especially with respect to institutional settings and road infrastructure. First, the PPP concept is introduced from a theoretical perspective and compared to traditional public procurement. Then the financing of PPP projects is discussed in the context of project finance and the European PPP market. The main part of the thesis focuses on public procurement of road infrastructure and the advantages of the PPP organizational structure. Initially, flaws of the procurement institutions are identified and a number of solutions suggested. The solutions cover four main areas: improvement of procurement laws, better qualifications of public officials, strategic planning of needed roads and asset management perspective on the existing infrastructure. The question whether Czech institutions are hindering the potential of PPP projects is answered positively. Follows a thorough empirical analysis of a World Bank PPP model for highways through a Monte Carlo simulation. A particular case of R35 motorway is evaluated as a PPP project and key drivers of public and private NPV are identified and compared across three different scenarios. Heavyweight traffic intensity, its toll revenue and...
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Fractal Dimension and Efficient Markets
Máková, Barbora ; Krištoufek, Ladislav (advisor) ; Víšek, Jan Ámos (referee)
The efficient market hypothesis is one of the most important propositions in finance theory and has been subjected to years of rigorous empirical testing. We examine power of a new tool for evaluating market efficiency, fractal dimension. Characteristics and abilities of fractal dimension measure are explored through extensive Monte Carlo simulations. We prove that it provides an accurate evaluation of market's efficiency and its changes. This approach is highly innovative and creates new possibilities for examination of markets. The uniqueness of fractal dimension is in its ability to assign a numerical ranking to examined series describing the level of (in)efficiency; it is accurate for small samples of observations and quickly reflects changes in market efficiency structure. Powered by TCPDF (www.tcpdf.org)
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Sequential Monte Carlo Methods
Sobková, Eva ; Zikmundová, Markéta (advisor) ; Prokešová, Michaela (referee)
Monte Carlo methods are used for stochastic systems simulations. Sequential Monte Carlo methods take advantage of the fact that observations are coming sequentially. This allows us to refine our estimate sequentially in time We introduce a State Space Model as a Hidden Markov Model. We describe Perfect Monte Carlo Sampling, Importance Sampling, Sequential Importance Sampling and discuss advantages and disadvantages of these methods. This discussion brings us to add a resampling step in Sequential Importance Sampling and introduce Particle Filter and Particle Marginal Metropolis-Hastings algorithm. We choose a Hidden Markov Model used for stochastic volatility modeling and make a simulation study in Wolfram Mathematica, version 8.
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Diffuse x-ray scattering from GaN epitaxial layers
Barchuk, Mykhailo ; Holý, Václav (advisor) ; Caha, Ondřej (referee) ; Pietsch, Ulrich (referee)
Real structure of heteroepitaxial GaN and AlGaN layers is studied by diffuse x-ray scattering. A new developed method based on Monte Carlo simulation enabling to determine densities of threading dislocations in c-plane GaN and stacking faults in a-plane GaN is presented. The results of Monte Carlo simulations are compared with ones obtained by use of other conventional techniques. The advantages and limitations of the new method are discussed in detail. The methods accuracy is estimated as about 15%. We have shown that our method is a reliable tool for threading dislocations and stacking faults densities determination.
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Option pricing under stochastic volatility
Khmelevskiy, Vadim ; Fičura, Milan (advisor) ; Janda, Karel (referee)
This master's thesis focuses on the problem area of option pricing under stochastic volatility. The theoretical part includes terms that are essential for understanding the problem area of option pricing and explains particular models for both option pricing under stochastic volatility and those under constant volatility. The application of described models is performed in the practical part of the thesis. After that particular models are compared to the real data.
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Valuation of PEBAL s.r.o.
Turza, Vladimír ; Brabenec, Tomáš (advisor) ; Keselý, Ladislav (referee)
The thesis aims to determine the equity value of the company PEBAL s. r. o. as of January 1st 2016. It is not separated into theoretical and practical part, because it is considered as fake appraisal of an expert. That is the reason why the whole thesis is practical with occasional theoretical background explanations. In the first part there is basic information provided about the appraised company along with its characteristics. Then financial analysis is carried out which will provide an overall picture of financial health of the company along with determination of competitors. Followed by strategical analysis which deals with the market as whole and predicts its future development as well as development of sales of the valued company. The next part consists of analysing and predicting value drivers and the overall financial plan. Result of the last part is the valuation itself applying discounted cash flow (DCF) method using discounts rate calculated earlier in the chapter. The final chapter also contains market valuation using method of comparable companies along with Monte Carlo simulation, that provides probability distribution of the value of the company.
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Application of Monte Carlo simulations in banking
Boruta, Matěj ; Teplý, Petr (advisor) ; Fučík, Vojtěch (referee)
Currently, banking is exposed to huge market risks. One of those risks is occurrence of negative interest rates in the EU. Nowadays, it is important to use sophisticated and modern measurement tools and approaches to measure and manage banking risks. One of those methods is Monte Carlo simulation. This bachelor thesis is aimed at analysis and prediction of 3-month maturity Prague Interest Offer Rate (PRIBOR) for 3, 6 and 12 months with using Monte Carlo simulations. It was found that this method is suitable for prediction market variables with low volatility. If anybody uses this method, it is necessity to have in mind all pitfalls and assumptions, that this method includes, as an adequate random generated number of scenarios, approximation of correct probability distribution, independence of dataset and not least, as far as possible, to focus on factors generating randomness of market variable and not the prices, that express rather consequences of randomness than its cause. Further, the Monte Carlo prediction was compared with prognosis of the Czech Nation Bank and it was found that Monte Carlo prediction is more accurate for short term predictions. 12-month prediction of Monte Carlo simulation discovered also possible occurrence of negative interest rate at 0,05% level of probability in compare to the Czech National Bank prognosis, where was no negative interest rate predicted.
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Robustní testy normality a jejich využití při ověřování slabé formy efektivnosti akciového trhu
Střelec, Luboš
Submitted dissertation is focused on methods of robust normality testing and applications of robust tests in verifying hypothesis of the weak form of efficiency in stock markets. In the dissertation, theory of efficient markets and approaches to verifying the weak form of market efficiency and normality assumption are being discussed. Novel robust testing procedures of testing normality are proposed in this work to overcome shortcomings of classical normality tests in the field of financial data, which are typical with occurrence of remote data points and additional types of deviations from normality. Results of power simulation study of classical and robust tests of normality against several types of alternative distributions, i.e. symmetric heavy-tailed, symmetric light-tailed, asymmetric heavy-tailed, asymmetric light-tailed, selected mixtures of normal distributions and outlier models, are presented. Based on outcome of the power simulation study, selected normality tests were consequently used to verify the weak form of efficiency in stock markets in the Czech Republic, Hungary, Austria, Germany, Slovakia, United States and Japan during years 2000-2009. In addition to selected classical and robust normality tests, Ljung-Box portmanteau test was also used. In conclusion, there is a discussion and comparison of results carried out and future trends of these markets are outlined.
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Coulomb Interactions in Electron Beams in the Vicinity of a Schottky and Cold Field Emission Sources
Liška, Ivo ; Kotačka, Libor (referee) ; Radlička, Tomáš (referee) ; Lencová, Bohumila (advisor)
Dizertační práce se zabývá problematikou výpočtu vlivu coulombovských interakcí částic na parametry emitovaného elektronového svazku v blízkosti Schottkyho a studené katody. Práce poskytuje základní předhled o problematice, popisuje vytvořené modely emisních zdrojů a metodu simulace Monte Carlo. Představuje novou metodu generování vstupních dat, která klade větší důraz na přesnou simulaci emisního procesu. Pozornost je zde věnována zejména vlivu interakcí na energiovou šířku, velikost virtuálního zdroje a jas katody v závislosti na velikosti poloměru hrotu a emisním proudu. Sledováním vývoje energiové šířky bylo zjištěno, že naprostá většina interakcí se odehrává v prostoru do několika mikrometrů od hrotu katody. Závislost spočtené celkové energiové šířky na úhlové intenzitě je ve shodě s dostupnými experimentálními daty. Spočtené energiové rozšíření vlivem coulombovských interakcí bylo srovnáno s hodnotami vypočtenými pomocí vzorců založených na analytických přiblíženích. Bylo zjištěno, že některé z nich přijatelně předpovídají trendy ale nemohou být použity pro kvantitativní odhad.
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A comparison of effective and functional connectivity methods in fMRI
Gajdoš, Martin ; Schwarz, Daniel (referee) ; Jan, Jiří (advisor)
Functional magnetic resonance imaging (fMRI) is recent important method, used in neuroimaging. The aim of this thesis is to develop software tool for comparison of two methods for functional and effective connectivity estimation. In this thesis are described the basics of magnetic resonance imaging, fMRI, basic terms of fMRI experiments and generally are described methods of functional and effective connectivity. Then are more detailed mentioned methods of dynamic causal modeling (DCM), Granger causal modeling (GCM) and independent component analysis (ICA). Practical implementation of DCM in toolbox SMP and ICA in toolbox GIFT is also mentioned. In purpose to describe behavior of DCM and GCM in dependence on several parameters are performed Monte Carlo simulations. Then the concept and realization of software tool for simulating connectivity and comparison of DCM and GCM are described. Finally results of DCM and GCM comparison and results of Monte Carlo simulations are discussed.
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