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Stochastic mortality modeling for multiple populations
Skřivanová, Zuzana ; Mazurová, Lucie (advisor) ; Cipra, Tomáš (referee)
Title: Stochastic mortality modelling for multiple populations Abstract: This thesis deals with the possibilities of modelling and forecasting of age-specific mortality rates. The introductory part summarizes the basic terms from demo- graphy, which are related to mortality, and specifies elementary approaches to the mortality modelling. Subsequently there are in detail described the three most commonly used stochastic mortality models - Lee-Carter, Renshaw-Haberman and Cairns-Blake-Dowd. The fundamental part of this thesis deals with the possi- bilities of using these models for mortality modelling simultaneously in correlated populations. These theoretical bases are in the final part of this thesis numerically illustrated on the mortality models for populations of Czech and Slovak Republic. 1
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Investment Strategies for Financial Derivatives
Voráčková, Andrea ; Hurt, Jan (advisor) ; Cipra, Tomáš (referee)
This bachelor thesis deals with various methods of valuing options. First, the basic definitions and relations concerning options are introduced. The second part is focused on Black-Scholes and binomial model and the relation between these models is proved. The Cox-Ross-Rubinstein and Jarrow-Rudd methods are introduced as well as the approximate versions of these methods. The numerical part consists of applying aforesaid methods on data using software Mathematica. The strengths and weaknesses of these methods are described and outcomings are compared with thesis of Hull (2012) and Shaw (2002). Powered by TCPDF (www.tcpdf.org)
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Selected problems of financial time series modelling
Hendrych, Radek ; Cipra, Tomáš (advisor) ; Arlt, Josef (referee) ; Prášková, Zuzana (referee)
Title: Selected problems of financial time series modelling Author: Radek Hendrych Department: Department of Probability and Mathematical Statistics (DPMS) Supervisor: Prof. RNDr. Tomáš Cipra, DrSc., DPMS Abstract: The present dissertation thesis deals with selected problems of financial time series analysis. In particular, it focuses on two fundamental aspects of condi- tional heteroscedasticity modelling. The first part of the thesis introduces and discusses self-weighted recursive estimation algorithms for several classic univariate conditional heteroscedasticity models, namely for the ARCH, GARCH, RiskMetrics EWMA, and GJR-GARCH processes. Their numerical capabilities are demonstrated by Monte Carlo experiments and real data examples. The second part of the thesis proposes a novel approach to conditional covariance (correlation) modelling. The suggested modelling technique has been inspired by the essential idea of the multivariate orthogonal GARCH method. It is based on a suitable type of linear time-varying orthogonal transformation, which enables to employ the constant conditional correlation scheme. The correspond- ing model is implemented by using a nonlinear discrete-time state space representation. The proposed approach is compared with other commonly applied models. It demon- strates its...
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Econometric models for Czech insurance market
Vichr, Jaroslav ; Cipra, Tomáš (advisor) ; Pešta, Michal (referee)
Relationships between insurance variables representing the cash flows of the Czech insurance market can be effectively modeled using a dynamic system of linear simultaneous equations. The source of the underlying data to build such a model can be publicly available annual reports of the Czech Insurance Association. The resulting model can find its use mainly to predict the future development of financial flows based on historical observations and analysis of possible scenarios. It is this analysis of potential projections and their consequences which provides insight into how e.g. a future decrease of new insurance policies would affect the expected amount of claims costs and the volume of written premiums.
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Claims reserving within the panel data framework
Gerthofer, Michal ; Pešta, Michal (advisor) ; Cipra, Tomáš (referee)
In the presented thesis the issue of dependency between response variables within the subjects in the generalized linear models framework is investigated. Reserving in non-life insurance is a key factor for the financial position of a company. The text introduces the basic actuarial notation, terminology and methods. The main part is focused on panel data framework, especially Generalized Linear Mixed Models (GLMM) as well as Generalized Estimating Equations (GEE), and their application on claims reserving. The aim of this thesis is to show the advantages, disadvantages, limitations and the comparison of these approaches on representative datasets, which were chosen according to results obtained from whole database analysis. Significant focus is on model selection and diagnostics used for this purpose. Finally, the obtained results are summarized in tables, figures and the comparison of the methods is provided. Powered by TCPDF (www.tcpdf.org)
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Generalized Leontiev models
Hála, Petr ; Kopa, Miloš (advisor) ; Cipra, Tomáš (referee)
"his thesis de-ls with veontiev¡s input -nd output model of the e onomy -nd its potenti-l extensionsF et the eginning of the thesis -si formul-tions -nd h-r- teristi s of the veontiev¡s model -re summ-rized with emph-sis on its solv- ilityF sn the third -nd fourth h-pterD we present the simplest modi( -tions with -ddition-l restri tions or o je tive fun tionF sn the sixth h-pter - dyn-mi model with dis rete time is derivedD -g-in with emph-sis on the formul-tion of the onditions of existen e of solutionF "he l-st h-pter presents - sto h-sti gener-liz-tion of the veontiev¡s model using pro - ilisti onstr-ints -nd the s en-rio -ppro- hF "he thesis is - omp-nied y its own ex-mple of veontiev¡s sto h-sti modelF
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Methods for periodic and irregular time series
Hanzák, Tomáš ; Cipra, Tomáš (advisor) ; Arlt, Josef (referee) ; Prášková, Zuzana (referee)
Title: Methods for periodic and irregular time series Author: Mgr. Tomáš Hanzák Department: Department of Probability and Mathematical Statistics Supervisor: Prof. RNDr. Tomáš Cipra, DrSc. Abstract: The thesis primarily deals with modifications of exponential smoothing type methods for univariate time series with periodicity and/or certain types of irregularities. A modified Holt method for irregular times series robust to the problem of "time-close" observations is suggested. The general concept of seasonality modeling is introduced into Holt-Winters method including a linear interpolation of seasonal indices and usage of trigonometric functions as special cases (the both methods are applicable for irregular observations). The DLS estimation of linear trend with seasonal dummies is investigated and compared with the additive Holt-Winters method. An autocorrelated term is introduced as an additional component in the time series decomposition. The suggested methods are compared with the classical ones using real data examples and/or simulation studies. Keywords: Discounted Least Squares, Exponential smoothing, Holt-Winters method, Irregular observations, Time series periodicity
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Pensions from the point of view of utility theory
Kudlík, Michal ; Cipra, Tomáš (advisor) ; Zichová, Jitka (referee)
This work deals with pensions from the perspective of utility theory. We list several basic principles, characteristics of pensions and their classification. Part of the work is also the utility theory from the ordinal point of view of utility theory as well as in terms of cardinal utility functions. Afterwards, we formulate the tasks for the selected utility functions, which we will try to optimize by using utility functions. We transfer the task of maximizing objective function to the task with extreme bound corresponding to various annuity markets which we will solve by theory of Lagrange multipliers. Final result of the work should be calculation of annuity equivalent wealth per common utility function Constant relative risk aversion (CRRA) using different relative risk aversions and showing the optimum consumption strategy for pensioners calculated based on mortality tables for Czech republic from 2012. 1
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Seasonal state space modeling
Suk, Luboš ; Cipra, Tomáš (advisor) ; Zichová, Jitka (referee)
State space modeling represents a statistical framework for exponential smoo- thing methods and it is often used in time series modeling. This thesis descri- bes seasonal innovations state space models and focuses on recently suggested TBATS model. This model includes Box-Cox transformation, ARMA model for residuals and trigonometric representation of seasonality and it was designed to handle a broad spectrum of time series with complex types of seasonality inclu- ding multiple seasonality, high frequency of data, non-integer periods of seasonal components, and dual-calendar effects. The estimation of the parameters based on maximum likelihood and trigonometric representation of seasonality greatly reduce computational burden in this model. The universatility of TBATS model is demonstrated by four real data time series.
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Credibility models for claim frequency
Biolek, Jiří ; Mazurová, Lucie (advisor) ; Cipra, Tomáš (referee)
The work deals with estimation of unknown risk parameters of a driver. Risk parameter indicates how many times more accidents we may expect from this driver compared with the average insurance group to which the driver is assigned according to the precarious classification. Risk parameter is a random variable, which is depending on the damage share of this driver. The second and third chapters describe the derivation of the estimates that minimize the quadratic and exponential loss function. It also compares the level of these estimates and the convergence rate. In chapter four there are several simulations performed and tables with estimates for any specific data created. 1
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