National Repository of Grey Literature 65 records found  beginprevious16 - 25nextend  jump to record: Search took 0.00 seconds. 
Combining multivariate volatility forecasts in portfolio optimization
Šípka, Stanislav ; Hendrych, Radek (advisor) ; Hudecová, Šárka (referee)
The selection of the best-performing model is always a challenge when solving financial-economic problems. The final model might prove to be suboptimal even after a short time if the economic climate changes suddenly. This thesis aims to construct a final model capable of estimating large-scale covariance matrices via the utilization of time-varying weights. A set of multivariate GARCH mod- els to be used as an input in the final combined estimate is used to introduce a weighting scheme based on the metrics of risk-adjusted return of the individ- ual model portfolios. As large-scale modeling often faces problems connected with the underlying dimensionality, the composite likelihood approach to model parameter estimation is proposed as a solution and compared to the standard maximum likelihood and its SVD modification. The resulting weighted covari- ance matrix prediction is used to construct optimal portfolios and their properties are compared in an empirical study. The thesis is concluded by noting the real-life limitation and possible improvements of the defined investing methodology. 1
Beta regression
Štěpán, Marek ; Hudecová, Šárka (advisor) ; Omelka, Marek (referee)
The thesis deals with a beta regression model suitable for analysing data whose range of values is the interval (0, 1). The model assumes a conditional beta distribution for the response given covariates, and its structure is similar to generalised linear models. The model is defined and its basic properties are investigated. The asymptotic distribution of the maximum likelihood estimates is provided. A possible extension to situations where the response in the data attains one of the boundary values is considered and referred to as c-inflated beta regression model. For both models, statistical inference and model diagnostics are discussed. The practical part of the thesis involves two Monte Carlo studies and two real data analyses. The first simulation study compares the performance of the global goodness-of-fit measures for link selection, while the second study explores various approaches to the analysis of the inflated beta distribution response. Alternative initial values are proposed for the cases where the algorithm did not converge. The practical usage of the model is illustrated on a model of proportions of tertiary educated people in European countries, and the proportion of household income spent on education in the Philippines. 1
ARFIMA time series models
Vdovičenko, Martin ; Hudecová, Šárka (advisor) ; Prášková, Zuzana (referee)
The thesis deal with long-memory processes which are defined by several ways. The main concern is dedicated to ARFIMA model, to its basic properties and its application. Next, graphical, semiparametric and parametric estimation methods of ARFIMA parameters are described in detail. Five selected R packages are introduced that are suitable for modeling long-memory processes. We discuss their basic functions with description of input arguments and output. Finally, the application of the packages on real data is discussed according to results of~each function. Data sample comes from the Nile River and represents its yearly minimal water levels. Powered by TCPDF (www.tcpdf.org)
Selected methods of time series analysis with STATISTICA
Indrová, Magdalena ; Hudecová, Šárka (advisor) ; Zichová, Jitka (referee)
This work deals with the use of STATISTICA software for the basic analysis of time series. The thesis is focused on time series decomposition, mainly on the trend elimination. First, the basic methods of the analysis are described theoretically, namely, trend modeling using mathematical curves (polynomial, exponential, logistic and Gompertz) and adaptive approach (moving averages, simple exponential smoothing and Holt's method). These methods are then applied to three selected data sets (unnamed bank's balance sheet from 1998 to 1993, ship construction trends between 1820 and 1997, and CZK/EUR Exchange rate from 1998 to 2012). All analytical procedures are described in detail and individual program outputs are thoroughly explained and commented.
Variance and Covariance Analysis with an application to financial data
Hájková, Anna ; Zichová, Jitka (advisor) ; Hudecová, Šárka (referee)
This Bachelor Thesis is dedicated to analysis variance and co- variance with and application to financial data. The aim of this thesis is to inform about multidimensional ANOVA and to show its connection with one- dimensional ANOVA, which is a part of standart statistical textbooks. Other part describes the analysis of covariance. For the better understanding, most of methods are applicated to financial data in the program Mathematica 8.0 1
Survival function estimation
Chrenko, Jakub ; Hudecová, Šárka (advisor) ; Komárek, Arnošt (referee)
Nazev prace: Odhady funkcr pfeziti Autor: Jakub Chrenko Kalodra: Katcdra pravdepodobnosti a mateinaticke statistiky Vedouci ba.ka.la.fske pra.ce: Mgr. Sarka Dosla e-mail vedouciho: dosla'ii'karlin.mff.cimi.cz Abstrakt: V pfedlozene pnici so zabyvame funkci pfeziti a jejuni odharly. Popsany jsou jak paramrtrirke, tak i neparamelrickc' pf ist upv. V obou piipa- deeh je pfihledimto k pfi'padncuiu ccnzorovanf clat. NoiJaramotricke rriotody iifkladon /adno pozadavky ua rozdrloni dat, a proto jsou uuiverzalne po- uzitcliic. Z tcchlo nictod uvadi'nir Z(^jmciH^ Ka,pkui-M(ucruv odhad fiinkcc pfcziti, jchoz zakladni vlastnosti jsou popsany. Ziiu'iiena je l.ra analyza ta- bulck unirtnosti. Parauietricke piist.upy j)rcdpokl;idaji koiikrntui tvar tno- rciickclio rozdeleiii sludovniio nahodric voliriny. Z nojcast.eji pouzivanycii rozdclonf Tivadinic oxporinucialui, Woilnilluvo a logaritniicko iioriualni. V za- vc.i'u prac'c; jsou tyt.o inctody poT'Oviiauy a ilustrovauy ua koukretui'm da- tovom souboru a poinoci simulaci. Klfcova slova: Fuiikcc })feziti, hazard, Kaplan-Mcicruv odhad, rouzorovana dat.n Title: Estiiua.tioii oi' Survivalship Function Author: Jakub Chronko Department: Department of Probability and Mathematical statistics Supervisor: Mgr. Snrka Dosla Supervisor's e-mail address: doslaCO'karliii.iiifl.ciuii.cz...
Bivariate Poisson distribution
Smolárová, Tereza ; Hudecová, Šárka (advisor) ; Hlubinka, Daniel (referee)
In the present thesis we deal with the bivariate Poisson distribution. A trivariate reduction method is used to define the bivariate Poisson dis- tribution. The theoretical characteristics of distribution, which this thesis deals with are the marginal distributions, covariance, a correlation coeffi- cient and the conditional distributions. A method of moments and a method of maximum likelihood are used to construct the point estimations of the parameters. Further, we focus on testing the goodness of fit by the index of dispersion test. A transforms of the sample correlation test is used to test the independence. Both methods for estimating the parameters and the statistic tests are applied to real data from the insurance field. 1
Survival analysis with STATISTICA
Kaderjáková, Zuzana ; Hudecová, Šárka (advisor) ; Hurt, Jan (referee)
Survival analysis is a separate statistical area. This paper discusses the~interpretation of basic concepts, principles and methods used and implemented in the software STATISTICA. First, we introduce censoring and ways of characterizing a distribution of survival time. We present Kaplan-Meier estimate of a survival function and also a method of mortality tables. Later, we discuss basic methods of comparison of the survival time distribution in two groups and their suitability for different situations. The paper also deals with application of the survival analysis methods in the financial sector, where we introduce Cox proportional hazards model. Finally, we apply theoretical knowledge to a real data set.

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