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Non-linear models for financial time series and software tools for their analysis
Fučík, Jan ; Zichová, Jitka (advisor) ; Hendrych, Radek (referee)
This thesis deals with some time series models applicable in finance. First, the basic concepts are introduced and the linear AR models are presented. Afterwards, the reader becomes familiar with the nonlinear ARCH volatility models including their properties and the model-building. The generalized GARCH models are briefly mentioned. Another part of the thesis shows the usage of these models to real data in two available software products - R and Mathematica. The programs are compared from the point of the obtained results and the usability for the analysis of financial time series via the explained models. The description of the procedures and the attached CD with the outputs of the programs allow the reader to apply the models on his or her own data.
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Root system development in the early phases of plant ontogeny
Mašková, Tereza ; Weiser, Martin (advisor) ; Šmilauer, Petr (referee)
Root system development in the early phases of plant ontogeny Seed germination and subsequential developement of the root system is a critical stage of life of a newly rising plant. The plant must recognise and suitably and quickly find an answer to the environmental conditions in which it finds itself. However, the way in which the root system develops and its final architecture depends not only on the environmental conditions but also on the plant itself. In addition, responses to different conditions may vary among different plant species. This work examines the developement of a root system in the first four weeks of a plant's life. It observes the dependence on the amount of available nutrients in the substrate and on the amount of available nutrients the seed is given by the mother plant. It also briefly touches on the relations between seed germination, seed size and the amount of available nutrients. No differences relating to the amount of available nutrients were found in seed germination. However, differences in germination speeds were found between plant species. Plant biomass increases with the increasing amount of available nutrients in the substrate. This increase is relatively greater for plant species with a small seed size. Plant species with a big seed size invest relatively more...
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MHC and KIR genotyping of macaques in HIV infection research
Matula, Jan ; Maděránková, Denisa (referee) ; Sedlář, Karel (advisor)
Modern research of viral diseases relies on genomic data processing. Not only is the sequence of a virus important, genomic sequence of specific receptors in affected organisms also plays an important role. In this paper, a novel package for processing of next generation sequencing data in infectious disease written using R/Bioconductor language is proposed. Functionality of the package, including implementation of advanced SSAHA algorithm for fast database searches, is demonstrated using genotyping of genes for MHC and KIR receptors of HIV positive macaques.
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Cluster Analysis Czech 100 Companies on the Basis of Financial Statements
Langer, Tomáš ; Král, Jiří (referee) ; Novotná, Veronika (advisor)
The diploma thesis called Cluster Analysis Czech 100 Companies on the Basis of Financial Statements deals with the testing of two hypotheses using a multidimensional statistical method - cluster analysis. The input data for the application of statistical methods are financial statements of selected companies for the years 2014 and 2015 which are publicly available. These data are digitized and subjected to methods of financial analysis.
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Whole genome alignment using suffix trees
Klouba, Lukáš ; Sedlář, Karel (referee) ; Maděránková, Denisa (advisor)
The aim of this thesis is to create an algorithm that allows the alignment of the genome of two organisms by means of suffix structures and to implement it into the programming language environment R. The thesis deals with the description of the construction of the suffix structures and the methods of whole genome alignment. The result of the thesis is a functional algorithm for whole genome alignment by means of suffix structures implemented in the software environment R and its comparison with similar programs for the whole genome alignment.
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Pupil with disorder of learning in primary school
Šustrová, Eliška ; Linková, Marie (advisor) ; Křivánek, Zdeněk (referee)
This thesis deals with specific learning disabilities on the first level of primary education. The theoretical part is devoted to the definition of the basic concepts, to the etiology of the occurrence of specific learning disabilities and to the classification of their manifestation. It draws up the possibilities of the diagnostics and of the follow-up re-education. It describes the possibilities of educating students with disabilities at basic schools or individually. The practical part of this thesis focuses on exploring the issue of specific learning disabilities on the first level of primary education, namely, in the third and fourth grade. Three case reports whose results most visibly pointed to a problem are also present here.
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Long-term memory detection with bootstrapping techniques: empirical analysis
Albert, Branislav ; Krištoufek, Ladislav (advisor) ; Avdulaj, Krenar (referee)
A time series has long range dependence if its autocorrelation function is not absolutely convergent. Presence of long memory in a time series has important consequences for consistency of several time series estimators and forecasting. We present a self-contained theoretical treatment of time series models necessary for study of long range dependence and survey a large list of parametric and semiparametric estimators of long range dependence. In a Monte Carlo study, we compare size and power properties of four estimators, namely R/S, DFA, GPH and Wavelet based method, when relying on asymptotic normality of the estimators and distributions obtained from the moving block bootstrap. We find out that the moving block bootstrap can improve the size of the R/S estimator. In general however, the moving block bootstrap did not perform satisfactorily for other estimators. GPH and Wavelet estimators offer the most reliable asymptotic confidence intervals.
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