National Repository of Grey Literature 111 records found  previous11 - 20nextend  jump to record: Search took 0.00 seconds. 
Measuring credit risk for portfolios with heavy-tailed risk factors
Jablonský, Petr ; Vošvrda, Miloslav (advisor) ; Janda, Karel (referee)
Measuring and managing credit risk constitute one of the most important processes within bank risk management. Classical credit risk models assume multivariate normality for distribution of underlying risk factors. Resulting methods offer analytical simplicity and computational efficiency but disregard of extreme joint events since their probability is too small. Recently several studies have doubted multivariate normality assumption saying that if we accept this assumption we might seriously underestimate downside risk of given credit portfolio. The master thesis provides with an insight into the problem of modelling credit risk under assumption of heavy tailed risk factors. We first present necessary mathematical preliminaries of copula functions which stand for an alternative method of modelling multivariate dependence structures. Next we introduce a credit risk model for bond portfolio with heavy tailed risk factors. At last we carry out several simulations on portfolios of different riskiness and compare to what extent the results from both mentioned models differ.
Asset price bubbles and monetary policy reactions
Kazaziová, Gledis ; Dědek, Oldřich (advisor) ; Vošvrda, Miloslav (referee)
This thesis' intent is to analyze stock market bubbles - to bring forward their causes, characteristics and possible aftermath. Hereinafter is this work aimed at presentation of possible monetary policy reactions, its influence on bubble development and impact. I will also present arguments in relation to central bank interventions. The principal point of this thesis is an application of theoretical framework onto actual examples. Therefore have I selected 17th century Tulipmania, Black Monday (October 1987) and Japanese Bubble in the '80s? Closing part is focusing on Black Monday and Japanese Bubble comparison, which are considered to be typical benign and malign crash examples, and on evaluation of relevant monetary policy reactions. Powered by TCPDF (www.tcpdf.org)
Wavelet-based Realized Variation and Covariation Theory
Baruník, Jozef ; Vošvrda, Miloslav (advisor) ; Kočenda, Evžen (referee) ; Di Matteo, Tiziana (referee) ; Veredas, David (referee)
English Abstract The study of volatility and covariation has become one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This dissertation contains a complete theory for realized variation and covariation estima- tion, generalizing current knowledge and taking the estimation into the time-frequency domain for the first time. The first part of the theory presents a wavelet-based realized variation theory, while the second part introduces its multivariate counterpart, a wavelet- based realized covariation theory. The results generalize the popular realized volatility framework by bringing robustness to noise as well as jumps and the ability to measure realized variation and covariation not only in the time domain, but also in the frequency domain. The theory is also tested in a numerical study of the small sample performance of the estimators and compared to other popular realized variation estimators under dif- ferent simulation settings with changing noise as well as jump level. The results reveal that our wavelet-based theory is able to estimate the realized measures with the greatest precision. Another notable contribution lies in the application of the presented theory. Our time-frequency estimators not only produce more efficient...
Estimating the Euro effect with Synthetic Control Method for Eastern Europe
Janota, Martin ; Teplý, Petr (advisor) ; Vošvrda, Miloslav (referee)
Estimating the Euro effect with Synthetic Control Method for Eastern Europe Abstract This thesis estimates the effect of Euro adoption on newest Eurozone members using synthetic control method. The effect is estimated on income per capita and GDP growth. Estimates indicate overall indecisive effect for Slovakia and Malta, neutral effect for Estonia and negative effect for Slovenia and Cyprus. The cost of Euro for Cyprus is estimated to be as high as 1/3 of GDP per capita. In some cases the direction of the effect changed before and after the financial crisis. The quality of inference suffers from low number of observations. Methodological assumptions are discussed, concluding that quality of Eastern European time series likely causes substantial bias in the results.
Estimate of the Capital Assets Pricing Models by means of Kalman filter
Pařenicová, Petra ; Netuka, Martin (advisor) ; Vošvrda, Miloslav (referee)
The Capital Assets Pricing Model (CAPM), which was published by W. F. Sharpe and J. Linter in the middle of the sixties, has since that time grown to one of the piers of foundation of the financial economics. During the time it used to be empirically tested for several times, but these tests in most of the cases contradicted its validity - especially (since as early as the seventies) rose the doubt about the time stability of the coefficient. Hence many economists have tried hard to find a new model, which could concisely express the progress of this coefficient. In have focused on three basic models in my thesis - they are the Model with Random Coefficients, the Random Walk and the Mean Reverting Model. I estimated these models for selected share issues from Prague Stock Exchange and New York Stock Exchange by Kalman filter and, finally, I tried to make a confrontation of all those models mentioned above. It is quite clear, that as for the sequel from empirical estimation, there always exists at the least one model with variable parameters, which better (in quite a concise way) describes to behaviour of the coefficient than the standard model CAPM with constant parameters.
On the predictibility of Central European stock returns: Do Neural Networks outperform modern economic techniques?
Baruník, Jozef ; Žikeš, Filip (advisor) ; Vošvrda, Miloslav (referee)
In this thesis we apply neural networks as nonparametric and nonlinear methods to the Central European stock markets returns (Czech, Polish, Hungarian and German) modelling. In the first two chapters we define prediction task and link the classical econometric analysis to neural networks. We also present optimization methods which will be used in the tests, conjugate gradient, Levenberg-Marquardt, and evolutionary search method. Further on, we present statistical methods for comparing the predictive accuracy of the non-nested models, as well as economic significance measures. In the empirical tests we first show the power of neural networks on Mackey-Glass chaotic time series followed by real-world data of the daily and weekly returns of mentioned stock exchanges for the 2000:2006 period. We find neural networks to have significantly lower prediction error than classical models for daily DAX series, weekly PX50 and BUX series. The lags of time-series were used, and also cross-country predictability has been tested, but the results were not significantly different. We also achieved economic significance of predictions with both daily and weekly PX-50, BUX and DAX with 60% accuracy of prediction. Finally we use neural network to learn Black-Scholes model and compared the pricing errors of...
A New Keynesian General Equilibrium Model for the Czech Economy
Dudík, Andrej ; Vošvrda, Miloslav (advisor) ; Baruník, Jozef (referee)
The work focuses on the development of a smaller-scale non-linear Dynamic Stochastic General Equilibrium model with typical New Keynesian features, which is subsequently applied for modelling the Czech economy business cycle. To this end, the model is estimated using maximum likelihood Bayesian method with the Kalman filter and the Metropolis-Hastings algorithm. Special care is paid to the the issues of derivation and approximation of the model, in order to retain its non-linear nature. Although some of the properties of the estimated model are not fully satisfactory, the estimated model can be considered an useful approximation of the Czech economic reality.
Multifractal nature of financial markets and its relationship to market efficiency
Jeřábek, Jakub ; Vošvrda, Miloslav (advisor) ; Krištoufek, Ladislav (referee)
The thesis shows the relationship between the persistence in the financial markets returns and their efficiency. It interprets the efficient markets hypothesis and provides various time series models for the analysis of financial markets. The concept of long memory is broadly presented and two main types of methods to estimate long memory are analysed - time domain and frequency domain methods. A Monte Carlo study is used to compare these methods and selected estimators are then used on real world data - exchange rate and stock market series. There is no evidence of long memory in the returns but the stock market volatilities show clear signs of persistence.

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