IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v70y2024ics1062940823001870.html
   My bibliography  Save this article

Clustering effects and evolution of the global major 10-year government bond market structure: A network perspective

Author

Listed:
  • Zhuang, Yangyang
  • Zhang, Ditian
  • Tang, Pan
  • Peng, Hongjuan

Abstract

This paper takes the 10-year government bond yields of 40 important economies in the world as the research object, aiming to establish a global major government bond market network based on the graph approach and construct an evaluation system to understand the clustering effects of different economies in some important global financial events and the evolution of market structure. Based on the rich information provided by the minimum spanning tree and planar maximally filtered graph, our empirical research results indicate that economies in the government bond market network exhibit clustering effects due to geographical proximity and similar yield levels. The GIIPS economies in Europe formed a core cluster during the European debt crisis period and the initial stage of the COVID-19 outbreak and formed clustering effects with other high-yield economies. In the initial stage of Sino-US trade friction, the market formed the phenomenon of European-American clusters and Asia-Pacific clusters. We also observed that in the complete research interval from 2010 to 2021, Germany and Netherlands had the strongest centrality, while the two largest economies in the world, the United States and China, also maintained close connections with them in the network structure. Through the interdisciplinary graph network approach, we hope to provide an effective perspective to observe and monitor the operation of the global government bond market.

Suggested Citation

  • Zhuang, Yangyang & Zhang, Ditian & Tang, Pan & Peng, Hongjuan, 2024. "Clustering effects and evolution of the global major 10-year government bond market structure: A network perspective," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
  • Handle: RePEc:eee:ecofin:v:70:y:2024:i:c:s1062940823001870
    DOI: 10.1016/j.najef.2023.102064
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940823001870
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.najef.2023.102064?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. repec:bla:pacecr:v:23:y:2018:i:1:p:109-126 is not listed on IDEAS
    2. Hammoudeh, Shawkat & Ajmi, Ahdi Noomen & Mokni, Khaled, 2020. "Relationship between green bonds and financial and environmental variables: A novel time-varying causality," Energy Economics, Elsevier, vol. 92(C).
    3. Salvatore Dell’Erba & Emanuele Baldacci & Tigran Poghosyan, 2013. "Spatial spillovers in emerging market spreads," Empirical Economics, Springer, vol. 45(2), pages 735-756, October.
    4. Flavin, Thomas J. & Morley, Ciara E. & Panopoulou, Ekaterini, 2014. "Identifying safe haven assets for equity investors through an analysis of the stability of shock transmission," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 137-154.
    5. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    6. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    7. Kolokolova, Olga & Lin, Ming-Tsung & Poon, Ser-Huang, 2020. "Too big to ignore? Hedge fund flows and bond yields," Journal of Banking & Finance, Elsevier, vol. 112(C).
    8. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    9. Fernández-Rodríguez, Fernando & Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2015. "Volatility spillovers in EMU sovereign bond markets," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 337-352.
    10. Cao, Guangxi & Zhang, Qi & Li, Qingchen, 2017. "Causal relationship between the global foreign exchange market based on complex networks and entropy theory," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 36-44.
    11. Gilmore, Claire G. & Lucey, Brian M. & Boscia, Marian W., 2010. "Comovements in government bond markets: A minimum spanning tree analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4875-4886.
    12. James D. Hamilton & Jing Cynthia Wu, 2012. "The Effectiveness of Alternative Monetary Policy Tools in a Zero Lower Bound Environment," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(s1), pages 3-46, February.
    13. Dene Hurley, 2009. "Linkages among US Interest Rates and East Asian Purchases of US Treasury Securities," Global Economic Review, Taylor & Francis Journals, vol. 38(4), pages 397-408.
    14. Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Hammoudeh, Shawkat M., 2017. "Main driving factors of the interest rate-stock market Granger causality," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 260-280.
    15. Matheson, Troy & Stavrev, Emil, 2014. "News and monetary shocks at a high frequency: A simple approach," Economics Letters, Elsevier, vol. 125(2), pages 282-286.
    16. Maruska Vizek, 2019. "The Sovereign Bond Markets Return And Volatility Spillovers," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, vol. 28(2), pages 597-610, december.
    17. Stavros Degiannakis & George Filis & Stefanos Tsemperlidis, 2019. "Economic announcements and the 10-year U.S. Treasury: Surprising findings without the surprise component," Applied Economics Letters, Taylor & Francis Journals, vol. 26(15), pages 1269-1273, September.
    18. Smales, L.A. & Apergis, N., 2017. "Understanding the impact of monetary policy announcements: The importance of language and surprises," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 33-50.
    19. Vissing-Jorgensen, Annette, 2021. "The Treasury Market in Spring 2020 and the Response of the Federal Reserve," Journal of Monetary Economics, Elsevier, vol. 124(C), pages 19-47.
    20. Avdoulas Christos & Bekiros Stelios & Lucey Brian, 2020. "The term structure of Eurozone peripheral bond yields: an asymmetric regime-switching equilibrium correction approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-23, September.
    21. Claeys, Peter & Vašíček, Bořek, 2014. "Measuring bilateral spillover and testing contagion on sovereign bond markets in Europe," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 151-165.
    22. Hong, Zhiwu & Niu, Linlin & Zhang, Chen, 2022. "Affine arbitrage-free yield net models with application to the euro debt crisis," Journal of Econometrics, Elsevier, vol. 230(1), pages 201-220.
    23. Román Ferrer & Syed Jawad Hussain Shahzad & Adrián Maizonada, 2019. "Nonlinear and extreme dependence between long-term sovereign bond yields and the stock market: A quantile-on-quantile analysis," Economics Bulletin, AccessEcon, vol. 39(2), pages 969-981.
    24. Broto, Carmen & Lamas, Matías, 2020. "Is market liquidity less resilient after the financial crisis? Evidence for US Treasuries," Economic Modelling, Elsevier, vol. 93(C), pages 217-229.
    25. Raymond Ka-Kay Pang & Oscar Granados & Harsh Chhajer & Erika Fille Legara, 2020. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Papers 2009.13390, arXiv.org, revised Feb 2021.
    26. Goda, Thomas & Lysandrou, Photis & Stewart, Chris, 2013. "The contribution of US bond demand to the US bond yield conundrum of 2004–2007: An empirical investigation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 113-136.
    27. Daniel L. Thornton, 2018. "Greenspan's Conundrum and the Fed's Ability to Affect Long‐Term Yields," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 513-543, March.
    28. Keskin, Mustafa & Deviren, Bayram & Kocakaplan, Yusuf, 2011. "Topology of the correlation networks among major currencies using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 719-730.
    29. Hamid Baghestani, 2010. "Forecasting the 10‐year US treasury rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(8), pages 673-688, December.
    30. Mizrach, Bruce & Neely, Christopher J., 2008. "Information shares in the US Treasury market," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1221-1233, July.
    31. Balduzzi, Pierluigi & Elton, Edwin J. & Green, T. Clifton, 2001. "Economic News and Bond Prices: Evidence from the U.S. Treasury Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(4), pages 523-543, December.
    32. Moessner, Richhild, 2015. "Reactions of US government bond yields to explicit FOMC forward guidance," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 217-233.
    33. Ehrmann, Michael & Fratzscher, Marcel, 2017. "Euro area government bonds – Fragmentation and contagion during the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 26-44.
    34. Yuki Toyoshima & Shigeyuki Hamori, 2012. "Panel cointegration analysis of co-movement between interest rate swap and treasury markets," Applied Economics Letters, Taylor & Francis Journals, vol. 19(15), pages 1483-1486, October.
    35. de Goeij, P. C. & Marquering, W., 2006. "Macroeconomic announcements and asymmetric volatility in bond returns," Other publications TiSEM bc4389f3-bad2-4e5b-b996-3, Tilburg University, School of Economics and Management.
    36. Cletus C. Coughlin & Daniel L. Thornton, 2022. "Further Evidence on Greenspan’s Conundrum," Review, Federal Reserve Bank of St. Louis, vol. 104(1), pages 70-77.
    37. Jang, Wooseok & Lee, Junghoon & Chang, Woojin, 2011. "Currency crises and the evolution of foreign exchange market: Evidence from minimum spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 707-718.
    38. Alexandros Kontonikas & Charles Nolan & Zivile Zekaite & Michael Lamla, 2019. "Treasuries variance decomposition and the impact of monetary policy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1506-1519, October.
    39. Sanjay Kumar Rout & Hrushikesh Mallick, 2022. "Sovereign Bond Market Shock Spillover Over Different Maturities: A Journey from Normal to Covid-19 Period," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(4), pages 697-734, December.
    40. Yi Fang & Yanru Wang & Yingyu Zhao, 2022. "Risk Spillover of Global Treasury Bond Markets in the Time of COVID-19 Pandemic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 58(15), pages 4309-4320, December.
    41. Sérgio C. Lagoa & Emanuel R. Leão & Diptes P. Bhimjee, 2022. "Dynamics of the public-debt-to-gdp ratio: can it explain the risk premium of treasury bonds?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 49(4), pages 1089-1122, November.
    42. Tsang, Andrew & Yiu, Matthew S. & Nguyen, Huy Toan, 2021. "Spillover across sovereign bond markets between the US and ASEAN4 economies," Journal of Asian Economics, Elsevier, vol. 76(C).
    43. Mizuno, Takayuki & Takayasu, Hideki & Takayasu, Misako, 2006. "Correlation networks among currencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 336-342.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Ditian & Zhuang, Yangyang & Tang, Pan & Han, Qingying, 2022. "The evolution of foreign exchange market: A network view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P2).
    2. Danau, Daniel, 2020. "Prudence and preference for flexibility gain," European Journal of Operational Research, Elsevier, vol. 287(2), pages 776-785.
    3. Tan T. M. Le & Franck Martin & Duc K. Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Economics Working Paper Archive (University of Rennes & University of Caen) 2018-04, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    4. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Correlations between biofuels and related commodities before and during the food crisis: A taxonomy perspective," Energy Economics, Elsevier, vol. 34(5), pages 1380-1391.
    5. Xin Yang & Shigang Wen & Zhifeng Liu & Cai Li & Chuangxia Huang, 2019. "Dynamic Properties of Foreign Exchange Complex Network," Mathematics, MDPI, vol. 7(9), pages 1-19, September.
    6. Dias, João, 2012. "Sovereign debt crisis in the European Union: A minimum spanning tree approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(5), pages 2046-2055.
    7. Kazemilari, Mansooreh & Mardani, Abbas & Streimikiene, Dalia & Zavadskas, Edmundas Kazimieras, 2017. "An overview of renewable energy companies in stock exchange: Evidence from minimal spanning tree approach," Renewable Energy, Elsevier, vol. 102(PA), pages 107-117.
    8. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    9. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Relationship Between Prices of Food, Fuel and Biofuel," 131st Seminar, September 18-19, 2012, Prague, Czech Republic 135793, European Association of Agricultural Economists.
    10. Trancoso, Tiago, 2014. "Emerging markets in the global economic network: Real(ly) decoupling?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 499-510.
    11. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.
    12. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    13. Výrost, Tomas & Lyócsa, Štefan & Baumöhl, Eduard, 2019. "Network-based asset allocation strategies," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 516-536.
    14. Lee, Junghoon & Youn, Janghyuk & Chang, Woojin, 2012. "Intraday volatility and network topological properties in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1354-1360.
    15. Dias, João, 2013. "Spanning trees and the Eurozone crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5974-5984.
    16. Deviren, Seyma Akkaya & Deviren, Bayram, 2016. "The relationship between carbon dioxide emission and economic growth: Hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 429-439.
    17. Pang, Raymond Ka-Kay & Granados, Oscar M. & Chhajer, Harsh & Legara, Erika Fille T., 2021. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    18. Wang, Gang-Jin & Xie, Chi & Han, Feng & Sun, Bo, 2012. "Similarity measure and topology evolution of foreign exchange markets using dynamic time warping method: Evidence from minimal spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(16), pages 4136-4146.
    19. Mansooreh Kazemilari & Ali Mohamadi, 2018. "Topological Network Analysis Based on Dissimilarity Measure of Multivariate Time Series Evolution in the Subprime Crisis," IJFS, MDPI, vol. 6(2), pages 1-16, May.
    20. Raymond Ka-Kay Pang & Oscar Granados & Harsh Chhajer & Erika Fille Legara, 2020. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Papers 2009.13390, arXiv.org, revised Feb 2021.

    More about this item

    Keywords

    10-year government bond yield; Minimum spanning tree; Planar maximally filtered graph; Clustering effects · Evolution;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:70:y:2024:i:c:s1062940823001870. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.