Consumer function is a standard instrument of quantitative economic analysis to examine the relationship between consumer expenditure and income or other influencing factors such as liquid assets, interest rates or various demographic and social factors. In this thesis are presented the most frequently used methods in econometric analysis of consumption function. Attention is paid to the hypothesis of absolute income, relative income, life cycle, permanent income, rational expectations and consumption function based on the error correction model. Furthermore, the suitability of individual models for the current economic situation in the Czech Republic is assessed. Subsequently an empirical model of consumption function for the Czech Republic is designed and tested. Furthermore, the estimates of each consumption function model for the period before and after economic crisis of 2008-2009 are performed and compared. Finally, a short-term prediction of the consumption of Czech households is made.

This diploma thesis focuses on modeling volatility in financial time series. The main approach to modelling volatility is using GARCH models which can capture the variability of conditional volatility of time series. For modelling a conditional mean value in time series are used ARMA models. In the series there are usually not fulfilled the assumption of earnings normality, therefore, are the earnings in most cased characterized by the leptokurtic shape of distribution. The thesis introduces some more distribution types, which can be more easily used for the earnings distribution - above all the Students t distribution. The aim of the thesis in the first part is to present the topic of financial time series and description of the GARCH models including their further modification. There are used e.g. IGARCH or other models capturing asymmetric impact of shocks such as GJR-GARCH. The second part deals with generated data, where are more in detail explored the volatility models and their behavior in corresponding financial time series. The third part focuses on the volatility estimation and forecasting for the financial time series. Firstly this concerns development of stock index MICEX secondly currency pair Russian Ruble to Czech Crown and eventually price development of the Brent crude oil. The goal of the third part is to present the impacts on volatility of chosen time series applied on the example of economic sanctions against Russia after annexation of the Crimea peninsula which happened in the first quarter 2014.

This diploma thesis deals with the analysis of the birth rate and fertility rate in dependence on the economic conditions of the Czech Republic. The aim of this thesis is to analyze relations between selected socio-economic indicators and total fertility rate on the basis of available data and to evaluate changes related to birth and fertility in the Czech Republic, which occurred in the period 1993-2015. The thesis is divided into two main parts - theoretical and analytical. In the theoretical part are described the basic methods of calculating the characteristics for the analysis of the level of birthrate and fertility, as well as the development of selected socio-economic indicators. An important part of the first part of the diploma thesis is specification of used methods within time series. The second part is practically focused on cointegration analysis and subsequent assembly of single-row models from which error correction models were obtained by transformation. These can be used to describe short and long term relationships between time series. Explained variables are aggregate fertility in all assembled models, the explanatory variables are GDP, average gross monthly wage, final consumption expenditure for households, child allowances, parental allowance and household loans per capita.

This thesis deals about using models of neural networks like alternative of time series model based on Box-Jenkins methodology. The work is divided into two parts according to the model construction method. Each of the parts contains a theory that explains the individual processes and the progress of the model construction. This is followed by two experiments demonstrating the difference in approach to the design of a given model and creating a forecast by estimated values. for the following year. The last part expertly evaluates the quality of the predictions and considers the use of neural networks against prediction models as an alternative to Box-Jenkins methodology based models

A traditional printed newspaper is being replaced by an online one. This is one of the reasons why I in this thesis focus just on internet journalism. The online journalism servers I present in a relation to other periodicals -- newspapers, broadcast and television. The thesis describes and analyses main development trends in the Czech media market. It puts an emphasis on economic sections of general news and it also compares these sections with specialized economic servers. An important part of the thesis is focused on an analysis of reader's attendance which results in a rank of the most popular news servers. The model of the time series analysis is set up for two websites and it predicts future development trend in the number of real users of online news. The aim of this thesis is to provide a general view on the contemporary situation and also to describe the developmental tendency of online reporting. The result of the dissertation is the prediction of future development trend of online reporting servers.

The thesis analyses determinants of shopping centre sales and its attendance demand; it is based on data of the specific shopping centre from the years 2007 -- 2011. Based on a five-year monthly time series, two sales models are created. One model tracks sales per customer, the other deals with the shopping centre sales which are compared with the sales index of retailers. On the other hand, a model of the shopping centre attendance demand uses figures of a five-year daily time series. Independent variables with significant effect on dependent variables are identified in the theoretical part. The models are estimated using the Ordinary Least Squares estimation. In all models, seasonal influences proved to be a significant determinant. In the sales models, hypotheses of the competition effect have been verified. Furthermore, in case of the attendance demand model, weather and marketing effects were estimated as important. Surprisingly, the economic variables proved themselves to be insignificant, which could be caused by the relatively short observation period. The limiting factor of all models is also the fact that the dataset consists of one shopping centre only. It prevents the author from conducting a comprehensive examination of other important determinants of shopping centre sales and attendance.

The goal of this work is to analyze the evolution of household consumption of the states in the EU. The consumption will be researched in the view of classification COICOP, which is the classification of individual consumption by purpose. After mapping of this evolution the estimation of future values will be done from known time series. This estimation will be performed by two different ways. First one will respect the composition of household consumption in sections of classification COICOP. The second one will only work with time series of average consumption for all sections together. To compare the states cluster analysis will be done. This analysis will be done by two ways again. First one will be aimed to analyze the current situation and the second one will be aimed to analyze the evolution of household consumption. Instead of Microsoft Excel STATGRAPHICS X64 CENTURION and SPSS will be used in this thesis. Household consumption prognosis is the main benefit of this thesis. This prognosis is made for all sections of COICOP. Analysis has shown, that the consumption should rise in future. There are few exceptions, mainly countries with not good economic situation as Greece.

This diploma thesis disserts mainly on the software application development created through language Visual Basic for Application, which serves to creation of macros and automation of work in Microsoft Excel. The Application is made specially for company PENTACO, spol. s.r.o. The software allows to calculate complete financial analysis of company for last 8 years. Statistical methods are used for prediction of future indicators. The financial analysis will reveal the weaknesses and strengths of the company and on their basis will be suggested solutions for fixing of problems and company situation.

The diploma thesis evaluates the economic situation of BPS Bicycle Industrial s. r. o. time series analysis. The theoretical part describes financial indicators, time series analyzes and regression and correlation analysis. Based on the analyzes, suggestions were made to improve the current situation of the company. BPS has proven to be financially sound. Shortcomings to improvement were identified from the analyzes. For example, share of equity and debt, use of surplus funds and turnover of receivables and payables. This ratio needs to be addressed through greater use of debt. The system of sanctions is solution for problem the turnover of receivables and the use of surplus funds by investing in shares.

This thesis aims to analyze accounting and financial indicators using time series methods and interval regression analysis for Rudolf Jelínek, a.s. In this thesis are analyzed development trends of individual indicators. Based on the obtained data, the company deals with the risks of the company based on analyzes and their solutions.