Time-scale analysis of sovereign bonds market co-movement in the EU
Thesis title in Czech: | Analýza vzájemné závislosti výnosů z vládních dluhopisů v EU |
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Thesis title in English: | Time-scale analysis of sovereign bonds market co-movement in the EU |
Key words: | Vzájemná Závislost, Waveletová Transformace, Dluhová Krize, Výnosy z Vládních Dluhopisů, Eurozóna |
English key words: | Co-movement, Wavelet Transformation, Sovereign Debt Crisis, Sovereign Bond Yields, Eurozone |
Academic year of topic announcement: | 2014/2015 |
Thesis type: | rigorosum thesis |
Thesis language: | angličtina |
Department: | Institute of Economic Studies (23-IES) |
Supervisor: | Mgr. Lukáš Vácha, Ph.D. |
Author: | hidden - assigned by the advisor |
Date of registration: | 20.07.2015 |
Date of assignment: | 20.07.2015 |
Date and time of defence: | 21.07.2015 00:00 |
Date of electronic submission: | 20.07.2015 |
Date of proceeded defence: | 21.07.2015 |
Opponents: | prof. PhDr. Ladislav Krištoufek, Ph.D. |
References |
1) Percival D. & Walden A. (2000). “Wavelet Methods for Time Series Analysis”,
Cambridge University Press, first edition, 622p The textbook is utilized in methodology part to explain DWT and especially MODWT plus their pyramid algorithms in detail. 2) Gencay, R., Selçuk, F. & Whitcher, B. J. (2002). An introduction to wavelets and other filtering methods in finance and economics, Academic press. The textbook is the cornerstone of wavelet-based estimation of correlation and cross-correlation. It describes and in detail explains procedure of point estimate of wavelet correlation as well as its confidence intervals. The thesis intensively uses R package “waveslim” written by Whitcher based on the textbook. 3) Grinsted A., Moore, J.C. & Jevrejeva S. (2004), Application of the cross wavelet transform and wavelet coherence to geophysical time series, Nonlin. Processes Geophys., 11, 561–566 The article describes wavelet coherence and its application on time series. My thesis uses Matlab package written by the authors used in the paper. 4) Aguiar-Conraria, L., Martins, M. M. & Soares M. J. (2012). The yield curve and the macro-economy across time and frequencies. Journal of Economic Dynamics and Control, 36(12), 1950-1970. The work uses wavelet coherence to analyze relationship between yield curve and various macroeconomic variables (GDP, M2, …). Although it is not connected with my topic, it gives excellent insight into usage of the methodology and its interpretation. 5) Inoue, T., Masuda, A. & Oshige, H. (2013). The contagion of the Greek fiscal crisis and structural changes in the Euro sovereign bond markets. Public Policy Review, 9(1), 171-202 In this paper DCC-GARCH is applied on sovereign bond yields and showed that co-movement changed in the crisis. In the thesis its results are frequently compared with the results of mine. 6) Fernández-Macho, J.,(2012) Wavelet multiple correlation and cross-correlation: A multiscale analysis of Eurozone stock markets. Physica A: Statistical Mechanics and its Applications, Elsevier, 391(4), pages 1097-1104. The author proposes estimator of wavelet multiple correlation, which allows me to model whole groups of the states together and then test the differences. I will employ the same R package „wavemulcor“, which was developed by the same author. 7) Gallegati, M. (2012). A wavelet-based approach to test for financial market contagion., Computational Statistics & Data Analysis, 56(11), 3491-3497. The paper utilizes bivariate wavelet correlation to detect contagion between the stock markets all around the world in the crisis. In my thesis this approach and rationale behind is applied too. 8) Barunik, J., Kocenda, E., & Vacha, L. (2013). Gold, oil, and stocks. arXiv preprint arXiv:1308.0210. The authors tested heterogeneity of the results across the scales by years. My thesis modifies the approach and creates a simple index of heterogeneity of the estimates. 9) Dias, J. (2012). Sovereign debt crisis in the European Union: A minimum spanning tree approach. Physica A: Statistical Mechanics and its Applications, 391(5), 2046-2055. The paper uses minimum spanning tree analysis to model co-movement of the sovereign bonds yields. The author showed that the crisis caused segmentation on the sovereign bond market in the EU. 10) Gómez-Puig, M. & Sosvilla-Rivero, S. (2014). Causality and contagion in EMU sovereign debt markets. International Review of Economics & Finance, 33, 12-27. The authors employed Granger causality. According to the results in the crisis time the relationship between the yields are more intensive. 11) Claeys, P., & Vašíček, B. (2014). Measuring Bilateral Spillover and Testing Contagion on Sovereign Bond Markets in Europe. Journal of Banking & Finance. The last paper uses factor augmented VAR and identified significant changes in shock transmissions on the sovereign bonds market. |
Preliminary scope of work |
Práce analyzuje vzájemnou závislost mezi denními výnosy desetiletých vládních
dluhopisů jedenácti zemí EU (Řecka, Španělska, Portugalska, Itálie, Francie, Německa, Nizozemska, Velké Británie, Belgie, Švédska a Dánska) rozdělených do tří skupin (Jádro Eurozóny, Periférie Eurozóny, země mimo Eurozónu). V centru pozornosti jsou změny vzájemné závislosti v období krize, zejména blízko dvou významných událostí - pádu Lehman Brothers a veřejného ohlášení zvýšení řeckého deficitu. Hlavní přínost práce tkví ve využití alternativní techniky - waveletové transformace. Tato metoda dovoluje zkoumat, jak se liší vzájemná závislost výnosů na jednotlivých škálách (frekvencích). Ke zkoumání je použita waveletová koherence a korelace. Práce přináší tři hlavní zjištění: (1) vzájemná závislost se signifikantně snížila v období krize, avšak jsou zde vidět rozdíly mezi Jádrem a Periférií, (2) vzájemnou závislost se signifikantně liší napříč škálami, ale heterogenita výsledků je v období krize menší,(3) u obou zmíněných událostí bylo detekováno signifikatní snížení waveletové korelace napříč nižšími škálami. |
Preliminary scope of work in English |
The thesis analyses co-movement of daily 10Y sovereign bond yields of 11 EU
members (Greece, Spain, Portugal, Italy, France, Germany, Netherlands, Great Britain, Belgium, Sweden and Denmark) divided into the three groups (the Core of the Eurozone, the Periphery of the Eurozone, the states outside the Eurozone). In the center of attention are changes of co-movement in the crisis period, especially near the two significant dates - the fall of Lehman Brothers (15.9.2008) and the day, when increase of Greek public deficit was announced (20.10.2009). Main contribution of the thesis is usage of alternative methodology - wavelet transformation. It allows to research how co-movement changes across scales (frequencies) and through time. Wavelet coherence is used as well as wavelet bivariate and multiple correlation. The thesis brings three main findings: (1) co-movement significantly decreased in the crisis period, but the results differ in the groups, (2) co-movement significantly differs across scales, but its heterogeneity decreased in the crisis period, (3) near to the examined dates sharp and significant decrease of wavelet correlation was observable across lower scales in some states. |