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Coexceedance in financial markets of countries trying to join the European Union
Baranová, Zuzana ; Horváth, Roman (advisor) ; Dědek, Oldřich (referee)
This thesis analyses financial contagion between a reference EU market - Germany and markets of five countries which are actively seeking to become a part of European Union - Montenegro, Serbia, Turkey, Bosnia and Macedonia in the period of March 2006 to March 2018. We apply quantile regression framework to analyse contagion which we base on the occurrence and degree of coexceedances between the reference and analysed market. The results indicate that contagion between stock markets exists, however in different degree for each of the analysed markets. In addition we apply the regression framework specifically for period of financial crisis of 2008 to demonstrate that contagion is stronger during turbulent market periods. JEL Classification G01, G14, G15 Keywords coexceedance, quantile regression, contagion, stock markets Author's e-mail 80605682@fsv.cuni.cz Supervisor's e-mail roman.horvath@fsv.cuni.cz
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An Empirical Investigation of Wage Discrimination in Professional Football
Blaha, Jakub ; Kocourek, David (advisor) ; Jonášová, Júlia (referee)
Salary discrimination is a phenomenon that arises from ineffective behaviour of economic subjects. Even though its presence is incompatible with the the- ory of profit maximization, salary inequality still persists in the human society. Nevertheless, the investigation of this topic has been largely unheeded in the environment of professional football. In our empirical research, we use the most recent data to investigate the salary gap between white, African American and Hispanic players in the American Major League Soccer. Besides ordinary least squares method that focuses on the impact of ethnicity for the average player, we adopted the method of quantile regression to reveal wage gap between play- ers with below-average pays. Observing each player's performance for 3 seasons, we uncovered salary discrimination against African Americans and Hispanics in the lowest decile of the salary distribution that amounts to 18.9% and 15.3%, respectively. Furthermore, we utilized the difference-in-differences (DID) esti- mator to find no effect of the increasing level of invested money on the wage gap. JEL Classification J30, Z20, Z21, J71 J31 J15 Keywords discrimination, race inequality, football, quan- tile regression, OLS, wages, racism Author's e-mail kubablaha@seznam.cz Supervisor's e-mail kocourek.david@email.cz
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Co-exceedances in stocks and bonds between Southern European Countries and CEE Countries - Analysis of contagion
Pjontek, Matej ; Horváth, Roman (advisor) ; Baruník, Jozef (referee)
In this thesis, we analyse financial contagion between Southern European (Greek, Italian, Portuguese and Spanish) and Central Eastern European (Czech, Polish and Hungarian) stock markets respectively sovereign bond markets in the period from January 2001 to June 2016. A quantile regression framework is applied to analyse contagion based on measuring of occurrences and degrees of co-exceedances. We use conditional variance (volatility) of analysed markets to find direction of the contagion. Our results show that during the analysed period contagion between stock markets exists. Contagion between stock markets is stronger during the financial and sovereign debt crisis. Direction of contagion is from Southern European to Central Eastern European Countries. We do not find evidence of contagion between Sothern European and Central Eastern European sovereign bond markets. Our results show "flight to quality", but not "flight from quality".
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Analysis of contagion between energy and CEE financial markets
Kosar, Mariia ; Horváth, Roman (advisor) ; Geršl, Adam (referee)
This work analyzes the contagion effects between energy and CEE financial markets during the two crisis periods (global financial crisis 2008-2009 and energy market crisis 2014), using a sample of daily data from 2004 till 2015. We detect contagion by observing the degree and structure of two dummy variables for specified crisis periods included into the quantile regression models on the basis of a dependence measure called "coexceedances". Our results show that there are significant contagion effects present between the gasoil and CEE stock markets during the 2008-2009 period and mixed evidence of contagion between crude oil market and CEE stock markets. CEE stock markets do not appear to exhibit significant contagion effects with energy markets during the recent energy market crisis. These results substantially differ from those found in the developed European markets. In particular, our results indicate that energy markets and stock markets in developed Europe seem to display significant contagion effects during the 2014-2015 period. Keywords: Central and Eastern Europe, contagion, energy market, quantile regression
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Understanding systematic risk of assets at various quantiles of return distribution 
Rusý, Tomáš ; Baruník, Jozef (advisor) ; Avdulaj, Krenar (referee)
In this thesis, we deal with the application of quantile regression to the Capital Asset Pricing Model, which is derived in the thesis. We investigate a real dataset to determine if one of many implications - constant beta at different quantiles of return distribution, of the model is met. For that purpose, we use Khmaladze test which is perfectly suited for testing if asset's beta varies over return distribution. Before we run the test we introduce both quantile regression and the Khmaladze test to the reader in simple and clear notation as we do not expect the reader to be familiar with this regression technique. Powered by TCPDF (www.tcpdf.org)
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Modeling Liquidity Adjusted Value at Risk Using Quantile Regression Analysis
Nguyen Quang, Dung ; Baruník, Jozef (advisor) ; Burda, Martin (referee)
The master's thesis deals with modeling Value at Risk model adjusted by liquid- ity. For this purpose we use quantile regression analysis and liquidity proxies. We find out that Garman-Klass volatility estimator can be very useful in pe- riod 2000-2008 for the small and mid-size semiconductor companies but not in period 2008-2015. The NASDAQ composite Garman-Klass volatility is useful for all semiconductor companies for period 2008-2015. We might conclude that from the outbreak of the crisis returns of all semiconductor companies might depend on movement of NASDAQ composite index. We use Amihud and Roll measures as the liquidity proxies but the results are not persuasive regardless or size of companies and period we analyzed. JEL Classification G11, G14, G17, G18, G32 Keywords liquidity, value at risk, quantile regression Author's e-mail michalnd@gmail.com Supervisor's e-mail barunik@utia.cas.cz Abstrakt Diplomová práce se zabývá modelováním hodnoty v risku upravenou o likvid- itu. Pro tuto analýzu jsme použili kvantilovou regresi a proměnné indikující likviditu. Došli jsme k závěru, že Garman-Klass volatility estimator je velmi užitečný pro malé a středně velké firmy operující na trhu s polovodiči a to v ob- dobí 2000-2007, nikoliv však období 2008-2015. NASDAQ composite...
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Statistical inference based on saddlepoint approximations
Sabolová, Radka
Title: Statistical inference based on saddlepoint approximations Author: Radka Sabolová Abstract: The saddlepoint techniques for M-estimators have proved to be very accurate and robust even for small sample sizes. Based on these results, saddle- point approximations of density of regression quantile and saddlepoint tests on the value of regression quantile were derived, both in parametric and nonpara- metric setup. Among these, a test on the value of regression quantile based on the asymptotic distribution of averaged regression quantiles was also proposed and all these tests were compared in a numerical study to the classical tests. Finally, special case of Kullback-Leibler divergence in exponential family was studied and saddlepoint approximations of the density of maximum likelihood estimator and sufficient statistic were also derived using this divergence. 1
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Modeling Conditional Quantiles of Central European Stock Market Returns
Burdová, Diana ; Baruník, Jozef (advisor) ; Krištoufek, Ladislav (referee)
Most of the literature on Value at Risk concentrates on the unconditional nonparametric or parametric approach to VaR estimation and much less on the direct modeling of conditional quantiles. This thesis focuses on the direct conditional VaR modeling, using the flexible quantile regression and hence imposing no restrictions on the return distribution. We apply semiparamet- ric Conditional Autoregressive Value at Risk (CAViaR) models that allow time-variation of the conditional distribution of returns and also different time-variation for different quantiles on four stock price indices: Czech PX, Hungarian BUX, German DAX and U.S. S&P 500. The objective is to inves- tigate how the introduction of dynamics impacts VaR accuracy. The main contribution lies firstly in the primary application of this approach on Cen- tral European stock market and secondly in the fact that we investigate the impact on VaR accuracy during the pre-crisis period and also the period covering the global financial crisis. Our results show that CAViaR models perform very well in describing the evolution of the quantiles, both in abso- lute terms and relative to the benchmark parametric models. Not only do they provide generally a better fit, they are also able to produce accurate forecasts. CAViaR models may be therefore used as a...
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Modelling Conditional Quantiles of CEE Stock Market Returns
Tóth, Daniel ; Baruník, Jozef (advisor) ; Kukačka, Jiří (referee)
Correctly specified models to forecast returns of indices are important for in- vestors to minimize risk on financial markets. This thesis focuses on conditional Value at Risk modeling, employing flexible quantile regression framework and hence avoiding the assumption on the return distribution. We apply semi- parametric linear quantile regression (LQR) models with realized variance and also models with positive and negative semivariance which allows for direct modelling of the quantiles. Four European stock price indices are taken into account: Czech PX, Hungarian BUX, German DAX and London FTSE 100. The objective is to investigate how the use of realized variance influence the VaR accuracy and the correlation between the Central & Eastern and Western European indices. The main contribution is application of the LQR models for modelling of conditional quantiles and comparison of the correlation between European indices with use of the realized measures. Our results show that linear quantile regression models on one-step-ahead forecast provide better fit and more accurate modelling than classical VaR model with assumption of nor- mally distributed returns. Therefore LQR models with realized variance can be used as accurate tool for investors. Moreover we show that diversification benefits are...
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Statistical inference based on saddlepoint approximations
Sabolová, Radka ; Jurečková, Jana (advisor) ; Hlávka, Zdeněk (referee) ; Picek, Jan (referee)
Title: Statistical inference based on saddlepoint approximations Author: Radka Sabolová Abstract: The saddlepoint techniques for M-estimators have proved to be very accurate and robust even for small sample sizes. Based on these results, saddle- point approximations of density of regression quantile and saddlepoint tests on the value of regression quantile were derived, both in parametric and nonpara- metric setup. Among these, a test on the value of regression quantile based on the asymptotic distribution of averaged regression quantiles was also proposed and all these tests were compared in a numerical study to the classical tests. Finally, special case of Kullback-Leibler divergence in exponential family was studied and saddlepoint approximations of the density of maximum likelihood estimator and sufficient statistic were also derived using this divergence. 1
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