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Sovereign debt markets: Where does the Czech Republic stand?
Bludská, Věra ; Hausenblas, Václav (advisor) ; Serdarevič, Goran (referee)
This thesis deals with the relationship between yield spreads on the sovereign bonds and their determinants with a primary focus on the Czech Republic. First, a homogeneous panel of Visegrad group countries (V4) was investigated by the pooled mean group (PMG) method of Pesaran et al. (1998). It was found that debt-to-gdp ratio along with VIX, the "fear gauge", are the main factors driving the spread dynamics in the V4 group. Based on the results from PMG estimation, we estimate a three-dimensional vector autoregression (VAR) model and structural VAR (SVAR) model in order to observe spread reactions on external shocks. Among the V4 group countries, Hungary exhibits the largest spread response to a VIX shock. Overall, the (S)VAR results confirmed that countries with higher levels of yields before crisis had also a stronger reaction to the market disturbances during 2007-2009. Furthermore, it was found that for the period 2010-2013, the standard model (macroeconomic fundamentals plus global risk aversion factors) provided less reliable results. As a remedy, financial soundness indicators were incorporated into the VAR model. We conclude that it is important to take into account country's financial sector vulnerabilities when describing the spread dynamics since 2010.
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Sovereign debt markets: Where does the Czech Republic stand?
Bludská, Věra ; Hausenblas, Václav (advisor) ; Serdarevič, Goran (referee)
This thesis deals with the relationship between yield spreads on the sovereign bonds and their determinants with a primary focus on the Czech Republic. First, a homogeneous panel of Visegrad group countries (V4) was investigated by the pooled mean group (PMG) method of Pesaran et al. (1998). It was found that debt-to-gdp ratio along with VIX, the "fear gauge", are the main factors driving the spread dynamics in the V4 group. Based on the results from PMG estimation, we estimate a three-dimensional vector autoregression (VAR) model and structural VAR (SVAR) model in order to observe spread reactions on external shocks. Among the V4 group countries, Hungary exhibits the largest spread response to a VIX shock. Overall, the (S)VAR results confirmed that countries with higher levels of yields before crisis had also a stronger reaction to the market disturbances during 2007-2009. Furthermore, it was found that for the period 2010-2013, the standard model (macroeconomic fundamentals plus global risk aversion factors) provided less reliable results. As a remedy, financial soundness indicators were incorporated into the VAR model. We conclude that it is important to take into account country's financial sector vulnerabilities when describing the spread dynamics since 2010.
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White Test for the Least Weighted Squares
Bludská, Věra ; Víšek, Jan Ámos (advisor) ; Krištoufek, Ladislav (referee)
The Least Weighted Squares (LWS) is a robust method for computing coefficients in linear regression models. An inherent problem of LWS is the complexity of its estimator and, consequently, the lack of an analytical solution or fast exact algorithms for its evaluation. To remedy this situation a novel exact algorithm running in polynomial time has been proposed. The algorithm implemented in MATLAB programming language has been employed for testing computationally more efficient non-exact LWS methods. In addition to many potential uses of LWS in robust econometrics (e.g. outlier diagnostics) the method has been applied to the problem of regression estimation in the presence of heteroscedasticity. It has been demonstrated that the combined use of the LWS estimator and White's test for heteroscedasticity significantly improves the efficiency of the robust regression estimation.
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