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Who Is the Far-Right Voter in Slovakia Today?
Kocábek, Pavel ; Kubátová, Hana (advisor) ; Hájek, Lukáš (referee)
This thesis deals with far-right parties in Slovakia. The objective is to compare them based on selected factors in order to answer the question: Who is the far-right voter in Slovakia today? For this purpose, the most successful far-right parties in recent years were chosen: the Slovak National Party (SNS), the People's Party Our Slovakia (ĽSNS), and a new formation called Republic. The factors adopted are characteristics and genesis, electorate and geographic support definition, and electoral volatility. The paper is divided into four parts. The first part concerns the far-right in Eastern Europe and Slovakia especially. In the second part, the focus is placed on the milestones that shaped and changed the Slovak political environment. Specifically, these are the Slovak state, the transformation period, Mečiar and anti-Hungarian politics, the fall of Mečiar, Fico and a government with the SNS, and the murder of Ján Kuciak. The third chapter analyses individual parties according to the factors mentioned above. Finally, the comparison itself is approached, where differences are identified but particularly parallels. Based on these findings, the author subsequently answers the research question.
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Risk Analysis of Selected Cryptocurrencies in Personal Finance
Strouhal, Tomáš ; Stroukal,, Dominik (referee) ; Karpíšek, Zdeněk (advisor)
This diploma thesis deals with cryptocurrency’s risk regarding other investment opportunities, such as funds. The aim of the work is to present a simple indicator of risk and reward in order to place cryptocurrencies in the context of other investments. First, selected cryptocurrencies are described, then their characteristics are compared with the funds. Synthetic risk and reward indicator is used as a tool to compare risk and reward of cryptocurrencies with the funds. This indicator is modified to match the cryptocurrency’s characteristics and still have a narrative value. After this modification, it is used to calculate the risk and reward of the S&P 500, Allianz Global Artificial Intelligence, Binance Coin, Bitcoin, Cardano, Ethereum, Solana, Tether, USD Coin and XRP. The results show that the original range of the indicator is insufficient given the higher volatility of cryptocurrencies, which it is unable to reflect. Conversely, the adjusted indicator is already very good at calculating with higher volatility in cryptocurrencies and assigning them to a higher risk class.
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Portfolio Proposal of the Fund of Hedge Funds
Fischer, Karel ; Brauner, Roman (referee) ; Rejnuš, Oldřich (advisor)
Diploma thesis deals with the portfolio creation of the fund of hedge funds. Theoretical part describes investment concepts, the theoretical and legislative parts of hedge funds and decription of the various methods used in practical part. The practical part is focused on the selection, analysis and comparison of the hedge funds. Proposal part contains investment recommendations of the portfolio of funds which meet requirements of the management of ABC fund.
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Volume - volatility relation across different volatility estimators
Kvasnička, Tomáš ; Krištoufek, Ladislav (advisor) ; Avdulaj, Krenar (referee)
The main objective of this thesis is to analyze whether traded volume increases predictive power of volatility. We are mostly focused on Garman-Klass volatility estimator, which is more efficient than squared returns. Both univariate (AR, HAR, ARFIMA) and multivariate models (VAR, VAR-HAR) are used to find out if traded volume improves volatility forecasting. Furthermore, GARCH(1,1) both with and without traded volume is carried out and forecasted. All these methods are estimated on a basis of rolling window and during each step 1-day ahead forecast is computed. Final assessment is based on MAPE, RMSE and Mincer-Zarnowitz test of the out-of-sample forecasts, which are compared with the realized volatility. It turns out that traded volume slightly improves predictive power of the scrutinized models in case of FTSE 100 and IPC Mexico, contrary to Nikkei 225 and S&P 500 when a decrease of the predictive power is detected. Moreover, we observe that only HAR and VAR-HAR models are able to produce an unbiased forecast. As the evidence of the improvement is not conclusive and to maintain model parsimony, HAR model fitted by Garman-Klass volatility appears to be the best alternative in case of missing the realized volatility.
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Quantitative Methods of Risk Control
Marcinek, Daniel ; Hurt, Jan (advisor) ; Hendrych, Radek (referee)
This thesis deals with stock modelling using ARCH and GARCH time series. Important aspect of stock modelling is to capture volatility correctly. Volatility in finance is usually defined as a standard deviation of asset returns. Many different models, which are summarized in the first part of this thesis, are used to model volatility. This thesis focus on multivariate volatility models including multivariate GARCH models. An approach to constructing a conditional maximum likelihood estimate to these methods is given. Discussed theory is applied on real financial data. In numeric application there is a construction of a volatility estimates for two specific stocks using models described in the first part of this thesis. Using the same financial data various bivariate models are compared. Based on comparison using maximum likelihood a specific model for these stocks is recommended. Powered by TCPDF (www.tcpdf.org)
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Commodity Connectedness: Short-run Versus Long-run
Jurka, Vojtěch ; Baruník, Jozef (advisor) ; Buzková, Petra (referee)
Commodity Connectedness: Short-run Versus Long-run Vojtěch Jurka Bachelor Thesis, IES FSV UK, 2018 The thesis contributes to empirical literature that studies volatility spillovers among the commodity and equity market, focusing on short-term and long-term linkages between them. Studying the persistence of volatility transmission is helpful for understanding the information flow, which is crucial for risk management and regulators. The persistence of volatility linkages represents how quickly information can be processed by markets. In this work, we explain the theoretical background of connectedness measures proposed by Diebold and Yilmaz (2012) and show the relationship with measures defined in the frequency domain by Baruník and Křehlík (2018), that allows us to distinguish between short and long persistent shocks in volatility of markets. We continue with the analysis of volatility transmission among stock market and key commodities which represents various sectors of the commodity market. Our first key finding is that in the period 1993- 2015 spillovers among markets more than doubled and persistence of connections have increased. Using a rolling sample over 250 days, we evaluate rich dynamics of connections between equity and commodity sectors. The dynamic analysis reveals that the global financial...
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Extreme value theory: Empirical analysis of tail behaviour of GARCH models
Šiml, Jan ; Šopov, Boril (advisor) ; Kocourek, David (referee)
This thesis investigates the capability of GARCH-family models to capture the tail properties using Monte Carlo simulation in framework of Conditional Extreme Value Theory. Analysis is carried out for three different GARCH-type models: GARCH, EGARCH, GJR-GARCH using Normal and Student's t-distributed innovations on four well-known stock market indices: S&P 500, FTSE 100, DAX and Nikkei 225. After conducting 3000 simulations of every estimated model, the Hill estimate of shape parameter implied by the GARCH-type models will be calculated and the models' performance will be assessed based on histograms, descriptive statistics and Root Mean Squared Error of simulated Hill estimates. Interesting results and im- plications for further research have been identified. Firstly, we highlight the Normal distribution's inappropriate nature in this case and its inability to capture the tail properties. Furthermore, GJR-GARCHT with t-distributed innovations is identified to be the best model, closely followed by other t-distributed GARCH-type models. Finally, a pattern in all Q-Q plots forecasting the simulation study results is appar- ent, with the exception of the DAX. This anomalous behaviour therefore necessitated further analysis and a significant right tail influence was recorded. Even though Hill estimates...
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Modeling of Long Memory in Volatility Using Wavelets
Kraicová, Lucie ; Baruník, Jozef (advisor) ; Adam, Tomáš (referee)
ii Abstract This thesis focuses on one of the attractive topics of current financial literature, the application of wavelet-based methods in volatility modeling. It introduces a new, wavelet-based estimator (wavelet Whittle estimator) of a FIEGARCH model, ARCH- family model capturing long-memory and asymmetry in volatility, and studies its properties. Based on an extensive Monte Carlo experiment, both the behavior of the new estimator in various situations and its relative performance with respect to two more traditional estimators (maximum likelihood estimator and Fourier-based Whittle estimator) are assessed, along with practical aspects of its application. Possible solutions are proposed for most of the issues detected, including suggestion of a new specification of the estimator. This uses maximal overlap discrete wavelet transform instead of the traditionally used discrete wavelet transform, which should improve the estimator performance in all its applications, not only in the case of FIEGARCH model estimation. The thesis concludes that, after optimization of the estimation setup, the wavelet-based estimator may become an attractive robust alternative to the traditional methods.
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Efficiency of the prediction markets: case of Intrade
Brandejs, David ; Dózsa, Martin (advisor) ; Benčík, Daniel (referee)
1 Abstract Bachelor thesis confirms weak market efficiency hypothesis for political events, which took place on Intrade prediction market and finished between 1. October and 31. December 2012. Three unit root tests, ADF GLS, KPSS and Lo-Mackinlay test proved on 5% confidence level, that 140 of 191 tested political events is weakly market efficient, which means high relative market efficiency (73,3%). Testing out-of-political markets shows significantly lower market efficiency. Logit model rejected on 5% confidence level the assumption, that total volume of traded shares is significant parameter for the estimation of market efficiency. Keywords Prediction market, Intrade, efficiency market hy- pothesis, relative market efficiency, ADF test, KPSS test Author's e-mail David.Brandejs@seznam.cz Supervisor's e-mail Martin@Dozsa.cz
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