National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Macroeconomic Analysis with Spatial Econometric Approaches
Macková, Simona ; Formánek, Tomáš (advisor) ; Tomanová, Petra (referee)
Spatial econometrics can bring a useful approach to macroeconomic analysis of regional data. This thesis delineates suitable cross-section data models regarding their geographical location. Neighbourhood relation is used for the analysis. The relation of neighbourhood among the regions is expressed using spatial weight matrix. We focus on spatial autocorrelation tests and introduce processes of finding a suitable spatial model. Further, we describe regression coefficients estimates and estimates of spatial dependence coefficients, especially method of maximum likelihood estimates. Besides illustrative examples we apply chosen basic spatial models on real macroeconomic data. We examine how they describe relation between household incomes, GDP and unemployment rate in western Europe. Results are compared with a linear regression model.
Diversification in Data Envelopment Analysis in finance
Macková, Simona ; Branda, Martin (advisor) ; Hurt, Jan (referee)
Title: Diversification in Data Envelopment Analysis in Finance Author: Simona Macková Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Martin Branda, Ph.D., Department of Probability and Ma- thematical Statistics Abstract: This thesis deals with an extension of data envelopment analysis and its application in finance. This method enables to evaluate the efficiency of cho- sen production units based on several inputs and outputs. Administrative fees or risk measures can be used as inputs and expected incomes of observed assets as outputs in financial application. We show basic traditional models in a form of a primary problem of linear programming and a dual problem as well and later compare with diversification models. It is suitable to deal with diversification which enables to consider dependencies between assets in case of finance and in- vestments. Than we get to nonlinear programming problem hence we introduce appropriate risk and return measures to make the problem solvable. Especially, we focus on the conditional value at risk. Next we introduce the model which deals with diversification. We use this on real data of chosen mutual funds. Keywords: Data envelopment analysis, Efficiency, Diversification, Conditional value at risk

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