|
|
Methods of dynamical analysis of portfolio composition
Meňhartová, Ivana ; Hanzák, Tomáš (advisor) ; Cipra, Tomáš (referee)
Title: Methods of dynamical analysis of portfolio composition Author: Ivana Meňhartová Department: Department of Probability and Mathematical Statistics Supervisor: Mgr. Tomáš Hanzák, KPMS, MFF UK Abstract: In the presented thesis we study methods used for dynamic analysis of portfolio based on it's revenues. The thesis focuses on Kalman filter and local- ly weighted regression as two basic methods for dynamic analysis. It describes in detail theory for these methods as well as their utilization and it discusses their proper settings. Practical applications of both methods on artificial data and real data from Prague stock-exchange are presented. Using artificial data we demonstrate practical importance of Kalman filter's assumptions. Afterwards we introduce term multicolinearity as a possible complication to real data applicati- ons. At the end of the thesis we compare results and usage of both methods and we introduce possibility of enhancing Kalman filter by projection of estimations or by CUSUM tests (change detection tests). Keywords: Kalman filter, locally weighted regression, multicollinearity, CUSUM test
|
|
|
Robustification of statistical and econometrical regression methods
Jurczyk, Tomáš ; Víšek, Jan Ámos (advisor) ; Hlávka, Zdeněk (referee) ; Malý, Marek (referee)
Title: Robustification of statistical and econometrical regression methods Author: Mgr. Tomáš Jurczyk Department: Department of probability and mathematical statistics Supervisor: prof. RNDr. Jan Ámos Víšek CSc., IES FSV UK Praha Abstract: Multicollinearity and outlier presence are two problems of data which can occur during the regression analysis. In this thesis we are interested mainly in situations where combined outlier-multicollinearity problem is present. We will show first the behavior of classical methods developed for overcoming one of these problems. We will investigate the functionality of methods proposed as robust multicollinearity detectors as well. We will prove that proposed two-step procedures (in one step typically based on robust regression methods) are failing in outlier detection and therefore also multicollinearity detection, if the strong multicollinearity is present in the majority of the data. We will propose a new one-step method as a candidate for the robust detector of multicollinearity as well as the robust ridge regression estimate. We will derive its properties, behavior and propose the diagnostic tools derived from that method. Keywords: multicollinearity, outliers, robust detector of multicollinearity, ro- bust ridge regression 1
|
|
|
Methods of dynamical analysis of portfolio composition
Meňhartová, Ivana ; Hanzák, Tomáš (advisor) ; Cipra, Tomáš (referee)
Title: Methods of dynamical analysis of portfolio composition Author: Ivana Meňhartová Department: Department of Probability and Mathematical Statistics Supervisor: Mgr. Tomáš Hanzák, KPMS, MFF UK Abstract: In the presented thesis we study methods used for dynamic analysis of portfolio based on it's revenues. The thesis focuses on Kalman filter and local- ly weighted regression as two basic methods for dynamic analysis. It describes in detail theory for these methods as well as their utilization and it discusses their proper settings. Practical applications of both methods on artificial data and real data from Prague stock-exchange are presented. Using artificial data we demonstrate practical importance of Kalman filter's assumptions. Afterwards we introduce term multicolinearity as a possible complication to real data applicati- ons. At the end of the thesis we compare results and usage of both methods and we introduce possibility of enhancing Kalman filter by projection of estimations or by CUSUM tests (change detection tests). Keywords: Kalman filter, locally weighted regression, multicollinearity, CUSUM test
|
|
|
Identifikace faktorů ovlivňujících objem průmyslové produkce
Hořavová, Andrea
Identification of factors affecting the volume of industrial production. Diploma thesis. Brno: Mendel University, 2015. Industry is among one of the most important sectors of the national economy in the Czech Republic. It belongs to the secondary sector. It is significant because it affects the development of the entire economy, labour productivity, employment, the volume of industrial production, businesses and the environment. This work deals with the identification of factors affecting the volume of industrial production. The aim of this thesis is to create an econometric model, identify factors affecting the volume of industrial production in the Czech Republic. Within the literature review will first characteristic industry and its distribution, followed by evaluation of the development of the industrial sector for the observed period. In the practical part will be constructed an econometric model that will be tested on assumptions of classical linear re-gression model.
|
|
|
Does campaign spending have any impact on election outcome ?
Dušek, Ondřej ; Hronza, Martin (advisor) ; Kovanda, Lukáš (referee)
This Thesis analyzes the impact of campaign spending of political parties on election outcome. The Thesis uses data from the Parliamentary library of the Chamber of Deputies of the Czech republic, annual reports of political parties and from the Czech Statistical Office. For the first estimation, a method of Ordinary Least Square is used, consequently the equation of the model is edited using instrumental variables, in order to eliminate endogeneity. A new regression is estimated using Two-Stage Least Squares method. After the editing, all the explanatory variables are corelated and insignificant, although, the model itself works. In the end, this work did not succeed in measuring a predicted positive impact of campaign spending on election outcome. This "non-result result" shows the importance of an extensive dataset, which would allow an alternative approach to modelling and eliminating strong multicollinearity in the model.
|
|
|
GRETL – Software for econometric courses support
Jindrová, Věra ; Sekničková, Jana (advisor) ; Školuda, Václav (referee)
The bachelor thesis aims to create a comprehensible user's manual for econometric software GRETL in the Czech language. It begins with the introduction of software GRETL and then acquaints the reader with a range of possible uses of the software when working with data. Thesis briefly describes the main characteristics of the possible linear regression model, such as multicollinearity, autocorrelation and heteroscedasticity, including possible testing in the particular software and evaluation of specific tests. The key part deals with defining and specifying data for their subsequent analysis in the software, compilation of a model, estimates of parameters of an econometric model using the least squares method, the weighted least squares method and the generalized least squares method. Furthermore, the thesis deals with hypotheses testing and confidence interval estimations, and also shows how to create and edit graphs in GRETL and explains each menu item in detail. All steps are supported by a graphical supplement and specific examples.
|
|
|
Dynamické modely inflace
Sodoma, Jan ; Hušek, Roman (advisor) ; Lejnarová, Šárka (referee)
In the first part, inflation is desribed theoretically. This part is about cost-push inflation, demand-pull inflation, galloping inflation, hyperinflation, monetarist and keneynesian view on inflation, issues in measuring inflation, effects of inflation and controlling inflation. Second part is empiric research. Inflation is endogenous variable. Price of petrol natural95 and monetary aggregate M2 are delayed exogenous variables. Object of analyse are relations between these variables: Correlation coefficient, F-test, t-tests, multicollinearity, autocorrelation.
|
guest ::
