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Volatility Spillovers in New Member States: A Bayesian Model
Janhuba, Radek ; Horváth, Roman (advisor) ; Červinka, Michal (referee)
Volatility spillovers in stock markets have become an important phenomenon, especially in times of crises. Mechanisms of shock transmission from one mar- ket to another are important for the international portfolio diversification. Our thesis examines impulse responses and variance decomposition of main stock in- dices in emerging Central European markets (Czech Republic, Poland, Slovakia and Hungary) in the period of January 2007 to August 2009. Two models are used: A vector autoregression (VAR) model with constant variance of resid- uals and a time varying parameter vector autoregression (TVP-VAR) model with a stochastic volatility. Opposingly of other comparable studies, Bayesian methods are used in both models. Our results confirm the presence of volatility spillovers among all markets. Interestingly, we find significant opposite trans- mission of shocks from Czech Republic to Poland and Hungary, suggesting that investors see the Central European exchanges as separate markets. Bibliographic Record Janhuba, R. (2012): Volatility Spillovers in New Member States: A Bayesian Model. Master thesis, Charles University in Prague, Faculty of Social Sciences, Institute of Economic Studies. Supervisor: doc. Roman Horváth Ph.D. JEL Classification C11, C32, C58, G01, G11, G14 Keywords Volatility spillovers,...
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Volatility spillovers between crude oil and food commodities
Hrycej, Martin ; Krištoufek, Ladislav (advisor) ; Janda, Karel (referee)
In this thesis, we analyze volatility spillovers between crude oil and food commodities. The principal hypothesis assumes crude oil to behave as a production factor of the agricultural food commodities, thence we are looking for appropriate price effects. We mainly employ wavelet coherence and partial wavelet coherence, which provide us with valuable insight into the commodities nexus, without any strict restraints and assumptions levied on our data. Secondly, we build a DCC-GARCH model in order to model the presumed volatility spillovers. We also perform several simple benchmark analyses, in particular we test for Granger causality and we compute the Pearson correlation coefficients. Our data sample, including 10 commodities and 2 indices, covers the latest decade, significantly widening the existing contextual literature. Our results are mostly compliant with related literature, especially regarding the crude oil-fuels bundle and food commodities bundle, respectively. Considering the main research question of volatility spillovers between food commodities and crude oil, our results are indicating reasonably strong relationships with crude oil for soybeans and corn, leaving cotton and wheat rather on the verge of strong relationship and finding cattle to be completely unrelated. Main merits of the thesis...
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Effects of the Financial Crisis on Stock Market of the Czech Republic and Spain
Titizov, Toško ; Avdulaj, Krenar (advisor) ; Princ, Michael (referee)
The paper analyzes effects of the financial crisis on stock market of the Czech Republic and Spain. We employ BEKK-GARCH model in order to study volatility spillovers and transmissions from the US stock market to stock markets of the Czech Republic and Spain. The multivariate GARCH models results show statistically significant, but relatively small, almost irrelevant volatility spillovers from the US stock market to stock markets of the Czech Republic and Spain. The Czech stock market exhibits higher conditional correlation coefficient than the Spanish stock market.
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Volatility Spillovers in New Member States: A Bayesian Model
Janhuba, Radek ; Horváth, Roman (advisor) ; Červinka, Michal (referee)
Volatility spillovers in stock markets have become an important phenomenon, especially in times of crises. Mechanisms of shock transmission from one market to another are important for the international portfolio diversification. Our thesis examines impulse responses and variance decomposition of main stock indices in emerging Central European markets (Czech Republic, Poland, Slovakia and Hungary) in the period of January 2007 to August 2009. Two models are used: A vector autoregression (VAR) model with constant variance of residuals and a time varying parameter vector autoregression (TVP-VAR) model with a stochastic volatility. Opposingly of other comparable studies, Bayesian methods are used in both models. Our results confirm the presence of volatility spillovers among all markets. Interestingly, we find significant opposite transmission of shocks from Czech Republic to Poland and Hungary, suggesting that investors see the Central European exchanges as separate markets. Powered by TCPDF (www.tcpdf.org)
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Volatility Spillovers in New Member States: A Bayesian Model
Janhuba, Radek ; Horváth, Roman (advisor) ; Červinka, Michal (referee)
Volatility spillovers in stock markets have become an important phenomenon, especially in times of crises. Mechanisms of shock transmission from one mar- ket to another are important for the international portfolio diversification. Our thesis examines impulse responses and variance decomposition of main stock in- dices in emerging Central European markets (Czech Republic, Poland, Slovakia and Hungary) in the period of January 2007 to August 2009. Two models are used: A vector autoregression (VAR) model with constant variance of resid- uals and a time varying parameter vector autoregression (TVP-VAR) model with a stochastic volatility. Opposingly of other comparable studies, Bayesian methods are used in both models. Our results confirm the presence of volatility spillovers among all markets. Interestingly, we find significant opposite trans- mission of shocks from Czech Republic to Poland and Hungary, suggesting that investors see the Central European exchanges as separate markets. Bibliographic Record Janhuba, R. (2012): Volatility Spillovers in New Member States: A Bayesian Model. Master thesis, Charles University in Prague, Faculty of Social Sciences, Institute of Economic Studies. Supervisor: doc. Roman Horváth Ph.D. JEL Classification C11, C32, C58, G01, G11, G14 Keywords Volatility spillovers,...
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