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俄乌战争对国债市场层级结构的影响。

Impact of Russia-Ukraine war on the hierarchical structure of government bond markets.

作者信息

Yagli Ibrahim, Deviren Bayram

机构信息

Department Accounting & Finance, Nevsehir Haci Bektas Veli University, 50300 Nevsehir, Turkey.

Department of Physics, Nevsehir Haci Bektas Veli University, 50300 Nevsehir, Turkey.

出版信息

Eur Phys J Plus. 2023;138(3):291. doi: 10.1140/epjp/s13360-023-03901-w. Epub 2023 Mar 29.

DOI:10.1140/epjp/s13360-023-03901-w
PMID:37008753
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10054208/
Abstract

The current study investigates the impact of Russia-Ukraine war on topological properties of the international bond market by adopting econophysics methodologies, namely hierarchical structure methods (minimal spanning tree, (MST) and hierarchical tree, (HT)). We examine the network structure in bond markets by using daily data for 10-years government bond yields for 25 developed and developing economies including European countries as well as countries with largest bond market such as the United States, China, and Japan. We have also concentrated the co-movements among European Union (EU) member countries since most of them adopt the euro as common currency while few still use their local currency as an official currency. Our sample covers the period from beginning of January, 2015 to the end of August, 2022, which also include the Russia-Ukraine war. Hence, we have divided the period into two sub-periods to investigate the influence of Russia-Ukraine war on the structuring and clustering linkages in government bond markets. Our results indicate that the networks of relationships between EU government bond markets, using the Euro as an official currency, are closely connected to each other according to their economic tie. The countries with largest bond markets are not located at the center of the trees. It is also obtaining that the Russia-Ukraine war have affected network structure of the government bond markets.

摘要

本研究采用经济物理学方法,即层次结构方法(最小生成树,MST和层次树,HT),研究俄乌战争对国际债券市场拓扑性质的影响。我们使用25个发达和发展中经济体(包括欧洲国家以及美国、中国和日本等拥有最大债券市场的国家)10年期国债收益率的每日数据,考察债券市场的网络结构。我们还关注了欧盟成员国之间的共同变动情况,因为其中大多数国家采用欧元作为共同货币,而少数国家仍使用本国货币作为官方货币。我们的样本涵盖了2015年1月初至2022年8月底这段时间,其中也包括俄乌战争时期。因此,我们将这段时间分为两个子时期,以研究俄乌战争对国债市场结构和聚类联系的影响。我们的结果表明,以欧元作为官方货币的欧盟国债市场之间的关系网络,根据其经济联系彼此紧密相连。拥有最大债券市场的国家并不位于树的中心。研究还发现,俄乌战争影响了国债市场的网络结构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/dc2cc5279122/13360_2023_3901_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/c447b48e7c05/13360_2023_3901_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/effd7e9ef543/13360_2023_3901_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/83d18b9d3b22/13360_2023_3901_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/86d60bb26974/13360_2023_3901_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/8bb3b8bbb086/13360_2023_3901_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/dc2cc5279122/13360_2023_3901_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/c447b48e7c05/13360_2023_3901_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/effd7e9ef543/13360_2023_3901_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/83d18b9d3b22/13360_2023_3901_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/86d60bb26974/13360_2023_3901_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/8bb3b8bbb086/13360_2023_3901_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9811/10054208/dc2cc5279122/13360_2023_3901_Fig6_HTML.jpg

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本文引用的文献

1
An analysis of network filtering methods to sovereign bond yields during COVID-19.新冠疫情期间主权债券收益率的网络过滤方法分析。
Physica A. 2021 Jul 15;574:125995. doi: 10.1016/j.physa.2021.125995. Epub 2021 Apr 9.
2
Emergence of time-horizon invariant correlation structure in financial returns by subtraction of the market mode.通过减去市场模式,金融回报中出现时间跨度不变的相关结构。
Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Aug;76(2 Pt 2):026104. doi: 10.1103/PhysRevE.76.026104. Epub 2007 Aug 10.