National Repository of Grey Literature 265 records found  beginprevious147 - 156nextend  jump to record: Search took 0.00 seconds. 
Econometric Analysis of Financial Data
Baniar, Matúš ; Zichová, Jitka (advisor) ; Cipra, Tomáš (referee)
Econometric Analysis of Financial Data Author: Matúš Baniar Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Jitka Zichová, Dr. Abstract: In some occasions, financial data can be represented as a combination of cross-sectional and time-series information. Hence it could be convenient to consider a system of econometric equations for modeling such data sets. At the beginning of this thesis, we describe general definitions and we talk about different types of variables from the perspective of exogeneity. Later, we describe some specific cases of these equations: SUR system, simultaneous equation models and the model of vector autoregression. For selected models, we also discuss estimation methods and their properties. In the final section, the described approach is applied to real financial data making use of appropriate software. Keywords: exogeneity, SUR system, simultaneous equations, VAR
Estimations of risk with respect to monthly horizon based on the two-year time series
Myšičková, Ivana ; Houfková, Lucia (advisor) ; Zichová, Jitka (referee)
The thesis describes commonly used measures of risk, such as volatility, Value at Risk (VaR) and Expected Shortfall (ES), and is tasked with creating models for measuring market risk. It is concerned with the risk over daily and over monthly horizons and shows the shortcomings of a square-root-of-time approach for converting VaR and ES between horizons. Parametric models, geometric Brownian motion (GBM) and GARCH process, and non-parametric models, historical simulation (HS) and some its possible improvements, are presented. The application of these mentioned models is demonstrated using real data. The accuracy of VaR models is proved through backtesting and the results are discussed. Part of this thesis is also a simulation study, which reveals the precision of VaR and ES estimates.
Autocorrelation and decomposition methods in economic time series analysis
Filka, Jakub ; Zichová, Jitka (advisor) ; Cipra, Tomáš (referee)
The goal of this bachelor thesis is to give a basic theoretical background for working with time series with the usage of autocorrelation and decomposition methods, as well as to apply these methods on real data in selected software. The interpretation of the results is closely related to the comparison of advantages and disadvantages of the methods. We have used the software Wolfram Mathematica and NCSS. The main contribution of the thesis is the connection of both theoretical and practical approach, which was not performed similarly in Czech or Slovak literature in the time of elaborating the thesis. Keywords: time series, autocorrelation methods, decomposive methods, Wolfram Mathematica Powered by TCPDF (www.tcpdf.org)
Means testing with an application to economic data
Došel, Jan ; Zichová, Jitka (advisor) ; Hlávka, Zdeněk (referee)
Title: Means testing with an application to economic data Author: Jan Došel Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Jitka Zichová, Dr., Department of Probability and Mathema- tical Statistics Abstract: The bachelor thesis deals with multivariate analysis of variance as a sta- tistical tool for comparing means of several random samples. In theoretical part, basic terms are described. Furthermore, a test statistic is derived from likelihood functions. The method is demonstrated by a simulation study in practical part. Keywords: analysis of variance, hypothesis testing, multivariate normal distribu- tion, likelihood function 1
Dependence analysis of categorical data from banking
Khýr, Miroslav ; Zichová, Jitka (advisor) ; Mazurová, Lucie (referee)
Title: Dependence analysis of categorical data from banking Author: Miroslav Khýr Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Jitka Zichová, Dr., Department of Probability and Mathema- tical Statistics Abstract: The aim of this work is describing in detail the theory of the log - linear expansion and graphical models for random vectors with a discrete distribution. Such vector can be used for modeling categorical variables for example in a po- pulation of borrowers by a bank . We show how to estimate the probability of an individual category. We use a log - likelihood function. Independence graph can represent conditional independence of discretely distributed random variables. Using this theory, especially using deviance as test statistics, we can examine whether same data correspond to the selected graphical model. At the end of this work we apply the described theory to real data and determine the graphical mo- del best fitting the dependence structure in a database from banking. From this graph we can deduce which variables are dependent and which are independent. Keywords: Log - linear expansion, graphical model, log - likelihood function ,de- viance.
Financial time series modelling with trend
Studnička, Václav ; Zichová, Jitka (advisor) ; Prášková, Zuzana (referee)
Various models can be used for the analysis of financial time series. This thesis focuses mainly on two models; non-linear trend model and linear trend model. First chapter is theoretial, there is an introduction to the theory of time series and to the autoregressive process. Second chapter is also theoretical and it focuses on a description of both non-linear and linear trend model including derivations of im- portant properties of these models; moreover, it contains theory for the modelling of financial time series and predictions. Last chapter contains simulations of two mentioned models and estimations of their parameters, Wolfram Mathematica is used for all simulations. 1
Some modifications of models ARCH for financial time series
Nekvinda, Matěj ; Cipra, Tomáš (advisor) ; Zichová, Jitka (referee)
This work deals with modelling time series, especially their volatility, by methods based on the ARCH model. In the beginning, we describe the general features of financial time series, afterwards we focus on the ARCH model modifications. The described modifications are GARCH, EGARCH, GJR-GARCH and briefly GARCH-M, IGARCH, FIGARCH and QGARCH. Along with the models, there is a description of their behaviour, which frequently reflects some features of financial time series. We also mention the process of practical financial time series analysis. In the end, we demonstrate the application of GARCH, EGARCH and GJR-GARCH models for modelling values of FTSE 100 index together with diagnostic tests and prediction. Powered by TCPDF (www.tcpdf.org)
Probability distributions of financial losses
Vacek, Lukáš ; Hurt, Jan (advisor) ; Zichová, Jitka (referee)
In this bachelor thesis, selected probability distributions which might appear useful for financial losses modelling are presented. Losses, risk measures and an example with a normality assumption are defined in the first part. Among others, the following distributions are presented in the second part: asymmetric Laplace distribution, skew normal distribution and generalized hyperbolic distribution. We present selected theoretical properties of these distributions. Procedures of a derivation of two asymmetric distributions from their symmetric cases are discribed. The asymmetric Laplace distribution is described more in detail, we also listed the maximum likelihood estimation with its implementation in software Wolfram Mathematica 10. The third part is a short numerical study, where an application of selected distributions is presented on real market data. Test of randomness and goodness of fit tests are performed. Powered by TCPDF (www.tcpdf.org)
Valuatuion of interest rates derivatives through LIBOR market model
Nistorová, Ružena ; Myška, Petr (advisor) ; Zichová, Jitka (referee)
In this thesis, the interest rates derivatives and their valuation based on the future development of interest rates are presented. The Hull-White model focusing on the modeling of the instantaneous spot rates is described in detail. The model is calibrated to the market caplet volatilities and is used to evaluate various interest rates derivatives. The main emphasis is put on the LIBOR market model describing the development of set of forward rates. There are presented and in detail discussed results of the calibration of LMM model on the market swaption volatilities. At the end the two models are compared.
Nonlinear parametric models for financial time series
Krnáčová, Simona ; Zichová, Jitka (advisor) ; Hudecová, Šárka (referee)
The thesis is dedicated to study of nonlinear parametric models for financial time series. It contains the summary of basic terms of this issues in brief. The next part is dedicated to the survey of different linear and nonlinear models with description of their basic features. Threshold autoregressive model and bilinear model are presented in details. For these two models, basic features, tests for linearity and estimations are introduced. The practical part is based on the theory described in previous chapters. Particular tests for linearity for both models and estimated instruments are analysed on simulated and real data.

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