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Econometric systems of simultaneous equations in life insurance
Hendrych, Radek ; Prášková, Zuzana (referee) ; Cipra, Tomáš (advisor)
In present work we deal with theoretical and practical issues related to econometric systems of (linear) simultaneous equations. In the first chapter we introduce to theoretical aspects of this problem. We devote considerable space to estimation procedures and comparisons of their properties, mention questions of identification, an inconsistency of OLS-estimates for the simultaneous modeling, tests of hypotheses specific to this area, dynamic systems and constructions of forecasts in models. In the second chapter we introduce selected basic concepts relevant to life insurance. In the third chapter we show the practical application of theoretical knowledge in the event of an econometric model of financial flows in the life insurance company operating on the Czech market. We compare ordinary estimation procedures (2SLS and 3SLS approach), perform some tests, which serve us to verify selected information on the studied model. We show the possibility of using residual bootstrap, including examples of use in the construction of confidence intervals. Finally we analyze several predictions of the estimated model of the life insurance company for predetermined scenarios for the development of selected variables, which is very important from practical point of view.
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Modelling financial time series
Holubářová, Šárka ; Cipra, Tomáš (referee) ; Zichová, Jitka (advisor)
This diploma thesis deals with modelling nancial time series and especially the changing volatility of nancial returns, which is characteristic for them. The theoretical part of the thesis describes several processes with non-constant conditional variance, which form an alternative to the classical ARMA approach to modelling time series. The focus is mainly on two types of processes - lognormal autoregressive process for conditional variance as an example of process where the conditional variance is independent of past returns, and on ARCH processes which to the contrary are based on dependence of the conditional variance on past returns. The properties of described models are veri ed and demonstrated in a simulation study carried out in Mathematica. Final part of the thesis is dedicated to application of the models to real data and modelling volatility of time series of returns of shares and currency rates. The parameters of the models are estimated and forecasts calculated in Mathematica with partial use of programme XploRe.
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Annuities under random interest rates
Sviteková, Zuzana ; Mazurová, Lucie (referee) ; Cipra, Tomáš (advisor)
The thesis describes accumulated values of annuities with yearly payments under independent random interest rates. The thesis focuses on general annuities with payments varying in arithmetic and geometric progressions which are important varying annuities. Mean and variance formulae of the final values of the annuities are derived in the thesis. In the beginning (chapter 2) the formulae of the final values of the annuities under xed rates of interest are shown. Chapter 3 is the main part of the thesis. The mean and variance formulae of the final values of the annuities under random rates of interest are proofed here. The thesis is based on the article [4] and [1]. It is especially focused on the article [1] which corrects main outcome of the article [4]. In the end (chapter 4) special cases of the annuites with numerical and graphical solutions are shown.
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Decomposition methods for time series with irregular observations
Hanzák, Tomáš ; Prášková, Zuzana (referee) ; Cipra, Tomáš (advisor)
This work deals with extensions of classical exponential smoothing type methods for univariate time series with irregular observations. Extensions of simple exponential smoothing, Holt method, Holt-Winters method and double exponential smoothing which have been developed in past are presented. An alternative method to Wright's modification of simple exponential smoothing for irregular data, based on the corresponding ARIMA process, is suggested. Exponential smoothing of order m for irregular data as a generalization of simple and double exponential smoothing is derived. A similar method using a DLS (discounted least squares) estimation of polynomial trend of order m is derived as well. In all cases the recursive character of these methods is preserved making them easy to implement and high computationally effective. A program in which most of the methods presented here are available is a part of the work. Some numerical examples of their application are also included.
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