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Komparácia vývoja nezamestnanosti v jednotlivých krajoch Českej republiky
Kucharovicová, Zuzana
Kucharovicová, Z. The comparison of unemployment trends in the regions of the Czech Republic. Bachelor thesis. Brno: Mendel University, 2017. This bachelor thesis examines unemployment trends in the regions of the Czech Republic for the period of 2010 to 2015 and provides the comparison of these trends. Three regions - South Moravian Region, Karlovy Vary Region and Moravian-Silesian Region - have been chosen for this purpose. The indicator of unemployment called the percentage of unemployed persons has been used for this study. Time series of this indicator are analysed by using the additive decomposi-tion of time series and regression analysis. Based on this study, unemployment trends in the chosen regions are apparently identical to each other. Nevertheless, there are some regional disparities which result in diverse unemployment.
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Analysis of relation between macroeconomic indicators and economic results of a company
Scigel, Pavel ; Dlouhá, Zuzana (advisor) ; Formánek, Tomáš (referee)
The Czech Republic's economic performance is measurable by some macroeconomic indicators which have made variable progress in recent years. Based on general economic conditions, economic development has impacted upon economic results of companies. Over time their progress is recorded by economic time series, which describe it. Through the agency of economic time series, economic development and mutual dependences among indicators can be researched. This problem can be solved by applying the methodology which helps describe and quantify relations among quantities. For the purpose of expression of a single time series, stochastic linear modelling is used, and for quantifying the strength of relation among time series, regression analyses and Granger causality testing are used.
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Fractal analysis of economic time series
Krýcha, Josef ; Tichý, Vladimír (advisor) ; Smrčka, Pavel (referee)
This thesis focuses on fractal analysis of economic time series. Chapter One introduces fractal analysis as a method of exploring time series and gathers information about progress and current state of understanding in this field. Chapter Two focuses on design and development of computer software, which will calculate selected fractal indices. Chapter Three is experimental and shows the results and discussion of economic time series (popular stock market indexes and currency exchange rate) analysis that have been obtained from the software developed in Chapter Two.
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