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Príliv priamych zahraničných investíciíc do krajín V4
Chovanec, Miloslav
Chovanec, M. Determinants of foreign direct investments to the V4 countries. Bachelor thesis. Brno: Mendel University in Brno, 2020. The aim of this thesis is to identify the determinants of foreign direct investment to the V4 countries. The aim of the thesis is fulfilled through regression analysis of time data of selected variables in the period 1997 to 2019. The work also describes and evaluates the development of foreign direct investment inflows to individual countries. The identified indicators point to the diversity of results within the V4 countries. In the Slovak Republic, the most significant factors influencing the inflow of foreign direct investment are the factors inflation and infrastructure. For Czech Republic the main factor is infrastructure and corporate tax factor for Poland. For Hungary, no factor was found to be significant at the 1 % level of significance, but some factors are identified that affect the inflow of foreign direct investment to Hungary at 5 and 10 % of the level of significance, namely GDP per hour factor, inflation and action factor elections in a given year.
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Rozdíly ve výši příjmů a starobních důchodů u mužů a žen v ČR
Slanařová, Barbora
This diploma thesis deals with differences in income and pension between men and women in the Czech Republic. The target was to evaluate time series and panel data of income and pension of both sexes and to evaluate the existence of differences by using econometrics methods. From the performed analysis was forecast the future development for next three years and then was created the marketing recommendation for retail store regarding the focus on consumers in the pension in the end.
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Analysis of Impact of Covariates Entering Stochastic Optimization Problem
Volf, Petr
In the contribution we study consequences of imperfect information to precision of stochastic optimization solution. In particular, it is assumed that the characteristics of optimization problem are influenced by a set of covariates. This dependence is described via a regression model. Hence, the uncertainty is then caused by statistical estimation of regression parameters. The contribution will analyze several regression model cases, together with their application. Precision of results will be explored, both theoretically as well as with the aid of simulations.
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Models of changes in econometric time sequences
Strejc, Petr ; Hušková, Marie (advisor) ; Dvořák, Marek (referee)
This paper is concerned with change-point detection in parameters of econometric regression models when a training set of data without any change is available. There are presented two well- known sequential tests - CUSUM test for linear regression model and a test based on weighted residuals for an autoregressive time series - including their asymptotical properties under certain conditions. Two asymptotically equivalent variance estimators are compared in a finite sample situation using Monte Carlo simulations. There are also presented and compared critical value approximations using different bootstrapping methods and variance estimators. Finally, the weighted residual test is applied on S&P 500 historical data.
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Regression analysis and splines
Benko, Milan ; Bašta, Milan (advisor) ; Komárek, Arnošt (referee)
The aim of this Bachelor's thesis is to introduce the basic concepts of regression analysis and subsequently regression splines as parametric models for regression function. I have looked upon the main characteristics of regression splines (coherence, coherence of derivations, the choice of placement and a number of knots). Further on in the thesis I have studied two bases as the examples of regression splines (truncated power basis and B-spline basis). I have also presented a model of natural cubic splines and a suitable basis for its representation has been derived. In the other part of my thesis I have looked upon the use of natural splines in order to increases the appraisal precision of regression function, mean square error formula has been derived and I have been trying to find out and illustrate under what conditions the use of natural splines is applicable. The thesis is complemented with a Monte Carlo Simulation, contextualized into models of splines. The results show that the criteria commonly used for the choice of a model ($\R_{adj}^2$, $PRESS$ statistic, hypothesis testing) do not always enable us to choose the right model in order to achieve the greatest precision of the estimation of regression function. All the calculations are done in R software and are in the electronic attachment....
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Influence of Reduction of Habitat Suitability Curves on Aquatic Habitat Suitability
Doláková, Gréta ; Macura, Viliam ; Škrinár, Andrej ; Čistý, Milan
Previous research into the aquatic monitoring of microhabitat fish preferences in Slovakia contains detailed valuable hydro-morphological, topographic, and ichthyological measurements for complex analysis. Consequent hydrological modeling of the database compares biotic parameters, represented by habitat suitability curves, and abiotic parameters of streams, to investigate the fish preferences of aquatic microhabitats. The research discusses an option if subsequent influence of reduction of habitat suitability curves on aquatic habitat suitability is justified to improve methodology of habitat assessment by regression model. The research creates an optimal regression relationship to determine the degree of habitat suitability curves reduction on mountain and piedmont streams in Slovakia.
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The Model of the Cost Function of the Bulding Factory Standan s.r.o,
Jamborová, Daniela ; Oulehla, Jiří (referee) ; Luňáček, Jiří (advisor)
The main goal of the bachelor's thesis is to determine the cost functions of the contract of the construction company Standan s. r. o.. The sub-objectives of the thesis are to define the theoretical basis of the solution, to perform a classification analysis and to define the cost function of the order. The last partial objective is to identify the key parameters of the cost function and their relationship with the total price of the order through correlation and regression analysis.
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Possibilities of Using of Remote Detection Data for Convective Storms Intensity Nowcasting
Valachová, Michaela ; Žák, Michal (advisor)
Title: Possibilities of Using of Remote Detection Data for Convective Storms Intensity Nowcasting Author: Michaela Valachová Department: Department of Atmospheric Physics Supervisor: Mgr. Michal Žák, Ph.D., Department of Atmospheric Physics Abstract: Evolution of 60 isolated convective storms from 2016 and 2017, which formed in the region of Central Europe, is studied by means of multi-sensor observations. According to the reports from the European Severe Weather Da- tabase, two categories of storms are classified: severe and non-severe. Based on radar, lightning and satellite measurements, trends of storm characteristics are analyzed to ascertain their typical behavior. Lightning stroke rates and their change could well warn about the ability of the storm to become severe, therefore a Lightning jump algorithm was proposed within this work. From individual case studies follows that methods of remote sensing offer comprehensive information about convective storm life-cycles. In order to objectively determine crucial variables for estimating the storm se- verity, logistic regression models and regularized regressions (elastic net) are employed. In total 53 variables from the first 30, 60 and 90 minutes of the moni- tored storm lifetime are used to show their predictive skill. Results of the models indicate...
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Models of changes in econometric time sequences
Strejc, Petr
This paper is concerned with change-point detection in parameters of econometric regression models when a training set of data without any change is available. There are presented two well- known sequential tests - CUSUM test for linear regression model and a test based on weighted residuals for an autoregressive time series - including their asymptotical properties under certain conditions. Two asymptotically equivalent variance estimators are compared in a finite sample situation using Monte Carlo simulations. There are also presented and compared critical value approximations using different bootstrapping methods and variance estimators. Finally, the weighted residual test is applied on S&P 500 historical data.
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Significance of different financial ratios in predicting stock returns: NYSE - cross-industry analysis
Coufal, Matěj ; Mejstřík, Michal (advisor) ; Kurka, Josef (referee)
The goal of this research is to investigate the power of following seven variables to predict stock returns on the New York Stock Exchange: price to earnings ratio (P/E), dividend yield (DY), debt to equity ratio (D/E), book to market ratio (B/M), return on assets (ROA), return on equity (ROE) and market capitaliza- tion (MC). Companies selected for the analysis are divided into five industries (airlines, computers and software, financial services, food and beverages, energy) which enables to observe the difference between the sectors as far as the statistical significance of regressors is concerned. The ability of six financial ratios and MC to forecast stock returns is examined between February 2010 and February 2020, whereas three investment horizons are considered: three months, one year, three years. Panel data regression models reveal different significant variables for each industry and show that the strength of the relationship between these regressors and expected stock returns increases with a longer investment horizon.
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