|
|
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
|
|
|
Hypotheses Testing in Financial Time Series
Kubů, Jan ; Zichová, Jitka (advisor) ; Jonáš, Petr (referee)
Financial data often take the form of time series. In such cases, their analysis is performed using statistical methods for time series. The thesis describes selected parametric and nonparametric tests of random walk hypothesis. Tests are designed against common mutual correlation alternatives but also against trend and cyclic data structure alternatives. The thesis provides the theoretical basis of these tests and their application to real financial data.
|
|
|
Technical analysis based on trade volumes and their effectivity from the point of view of future price movements
Chval, David ; Bašta, Milan (advisor) ; Zichová, Jitka (referee)
This Bachelor Thesis studies methods of technical analysis based on trade volume. The first two chapters are theoretical. They describe financial markets, their functions, properties and methods used in analysis of financial instrument. In the next section is described efficient market hypothesis, forms of efficiency and tests of this hypothesis. The third chapter is analytical. The idea that extreme trading activity predict future increase, or decrease of stock prices is investigated. Here is described methodology, data aquisition, analysis results and comparison with other similar research.
|
|
|
Nonlinear nonparametric models for financial time series
Klačanská, Júlia ; Zichová, Jitka (advisor) ; Cipra, Tomáš (referee)
The thesis studies nonlinear nonparametric models used in time series analy- sis. It gives basic introduction to the time series and states different nonlinear nonparametric models including their estimates. Special attention is paid to three of them, CHARN, FAR and AFAR model. Their properties and esti- mation techniques are presented. We also show techniques that select values of the parametres used further in estimation methods. The properties of time series models are investigated in simulation and real data studies. 1
|
|
|
Software products for financial time series analysis
Vlasáková, Romana ; Zichová, Jitka (advisor) ; Cipra, Tomáš (referee)
The present work deals with selected methods suitable to work with financial time series. Firstly, univariate linear models ARMA are introduced, followed by the description of volatility models ARCH and their generalization to GARCH models. There are many modifications of standard GARCH models designed with respect to the nature of financial data, some of which are presented. Another part of the work dealing with multiple time series focuses on VAR models and bivariate GARCH models. The most important part of the work are practical examples of building the theoretically described models in various types of software with built-in procedures for time series analysis. We apply five different types of commercial and non-commercial software, namely EViews, Mathematica, R, S-PLUS and XploRe. The used software products are presented and compared in terms of their capabilities and the results obtained for particular methods.
|
|
|
Data Envelopment Analysis with financial application
Marcinek, Daniel ; Branda, Martin (advisor) ; Zichová, Jitka (referee)
This thesis deals with various methods of Data Envelopment Analysis and their use in finance. Efficiency is measured by a ratio of weighted outputs to weighted inputs. From this model, a fractional programming problem is formed, which is then transformed into a linear programming problem. We derive a dual problem for that one. We also introduce another methods of Data Envelopment Analysis. We explain difference between a constant return to scale and a variable return to scale. We deal with a risk measures, which are considered as the inputs together with the management fees. We use gross returns as the single input. We apply these models to 15 mutual funds, determine efficiency of these mutual funds and compare these methods with another one. At the end we determine how the efficiency changes if we use only the risk measures as the inputs.
|
|
|
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.
|
|
|
Financial functions in Mathematica
Stacho, Michal ; Hurt, Jan (advisor) ; Zichová, Jitka (referee)
The Mathematica software contains a fully integrated environment for a large number of instruments used in classical and modern finance. One of it`s basic capabilities is an advanced evaluation of the time value of money, then pricing of financial instruments such as bonds or financial derivatives and finally financial mapping with advanced library of technical indicators. Mathematica also provides immediate access to a large field of financial and economic data through external servers and offers financial tools for working with external data. This thesis deals with descriptions of the functions implemented in Mathematica, explaining the principle of their operation and application to real data.
|
|
|
Non-standard approaches to financial time series analysis
Zbyňovský, Tomáš ; Zichová, Jitka (advisor) ; Hurt, Jan (referee)
Standard procedures for parameter estimation in autoregressive models use maximum likelihood method based on normal random error distribution assumption. However, this thesis is focused on non-standard approaches for parameter estimation in non-negative time series based on the assumption of exponential probability distribution. Both standard and non-standard approaches were tested on forex time series and the results summarized in the thesis.
|
|
|
Quantitative methods in finance
Zboňáková, Lenka ; Hurt, Jan (advisor) ; Zichová, Jitka (referee)
In the present thesis we deal with the quantitative risk measures estimating the influence of market risk on the investments to the financial instruments. The most commonly used measure is Value at Risk which we introduce with its characteristics and modifications. Applying the methods to real data we deal with the problem of approximation of its distribution, especially in the multidimensional cases when the risk factors are dependent on each other. This leads us to explore copula functions that are in the thesis used to include the dependence structures of the risk factors to calculation of the risk measures. Chosen methods of approximation and evaluation of the risk measures are applied to real data and stated with outputs and their comparison.
|
guest ::
RSS feed.