National Repository of Grey Literature 4 records found  Search took 0.00 seconds. 
Studie teoretické predikovatelnosti extremálních rozdělení pro přírodní katastrofy
Sabolová, Radka ; Zimmermann, Pavel (advisor) ; Kladívko, Kamil (referee)
The thesis deals with natural disasters from the statistical point of view and treats them as extremal observations. Basics of classical extreme value theory will be summarized and new approach based on maximum entropy principle will be proposed. Both methods will be used in order to analyze real discharge data observed at the river Vltava.
Analysis of time series of greenhouse gases emissions in the EU 27 during the period from 1990 to 2011
Sabo, Juraj ; Helman, Karel (advisor) ; Kladívko, Kamil (referee)
Global climate change is one of the most serious environmental issues. According to current scientific knowledge, the global climate change is caused by the production of greenhouse gases. In response to this ongoing climate change the Kyoto Protocol to the United Nations Framework Agreement on Climate Change was adopted. This bachelor thesis is focused on the analysis of time series of total greenhouse gases emissions in the EU 27 during the period from 1990 to 2011. The aim is to obtain information about the behavior of the analyzed time series in the reporting period, verify the objectives of the Kyoto Protocol of reducing emitted greenhouse gases and forecast the future development of greenhouse gases emissions in EU 27. All data was obtained from public databases of Eurostat. Tools for achieving the objectives of the thesis are basic characteristics of time series and methods for modelling trend component through the selected trend functions and adaptive methods. This thesis consists of two main parts. The theoretical part is devoted to the description of the statistical methods and practical part is dedicated to the analysis of time series.
Analysis of monthly precipitation totals from selected monitoring stations in Europe
Krause, Patrik ; Helman, Karel (advisor) ; Kladívko, Kamil (referee)
This thesis is focused on analysis of time series of monthly precipitation totals for four European stations for the years 1913 to 2012. The data were obtained from European database of ECA&D. The aim of this thesis is to find out development of time series and predict precipitation for the year 2013. Prediction of future development of time series is made by using regression modeling of seasonality and Box-Jenkins methodology and the results obtained by the two methods are then compared. The thesis is divided into theoretical and practical parts.
Modely finančních časových řad a jejich aplikace
Kladívko, Kamil ; Arlt, Josef (advisor) ; Witzany, Jiří (referee) ; Cipra, Tomáš (referee)
I study, develop and implement selected interest rate models. I begin with a simple categorization of interest rate models and with an explanation why interest rate models are useful. I explain and discuss the notion of arbitrage. I use Oldrich Vasicek's seminal model (Vasicek; 1977) to develop the idea of no-arbitrage term structure modeling. I introduce both the partial di erential equation and the risk-neutral approach to zero-coupon bond pricing. I briefly comment on affine term structure models, a general equilibrium term structure model, and HJM framework. I present the Czech Treasury yield curve estimates at a daily frequency from 1999 to the present. I use the parsimonious Nelson-Siegel model (Nelson and Siegel; 1987), for which I suggest a parameter restriction that avoids abrupt changes in parameter estimates and thus allows for the economic interpretation of the model to hold. The Nelson-Siegel model is shown to fit the Czech bond price data well without being over-parameterized. Thus, the model provides an accurate and consistent picture of the Czech Treasury yield curve evolution. The estimated parameters can be used to calculate spot rates and hence par rates, forward rates or discount function for practically any maturity. To my knowledge, consistent time series of spot rates are not available for the Czech economy. I introduce two estimation techniques of the short-rate process. I begin with the maximum likelihood estimator of a square root diff usion. A square root di usion serves as the short rate process in the famous CIR model (Cox, Ingersoll and Ross; 1985b). I develop and analyze two Matlab implementations of the estimation routine and test them on a three-month PRIBOR time series. A square root diff usion is a restricted version of, so called, CKLS di ffusion (Chan, Karolyi, Longsta and Sanders; 1992). I use the CKLS short-rate process to introduce the General Method of Moments as the second estimation technique. I discuss the numerical implementation of this method. I show the importance of the estimator of the GMM weighting matrix and question the famous empirical result about the volatility speci cation of the short-rate process. Finally, I develop a novel yield curve model, which is based on principal component analysis and nonlinear stochastic di erential equations. The model, which is not a no-arbitrage model, can be used in areas, where quantification of interest rate dynamics is needed. Examples, of such areas, are interest rate risk management, or the pro tability and risk evaluation of interest rate contingent claims, or di erent investment strategies. The model is validated by Monte Carlo simulations.

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