{"title":"亥姆霍兹-霍奇-柯达伊拉分解法揭示的金融市场网络中的因果层次结构","authors":"Tobias Wand, Oliver Kamps, Hiroshi Iyetomi","doi":"arxiv-2408.12839","DOIUrl":null,"url":null,"abstract":"Granger causality can uncover the cause and effect relationships in financial\nnetworks. However, such networks can be convoluted and difficult to interpret,\nbut the Helmholtz-Hodge-Kodaira decomposition can split them into a rotational\nand gradient component which reveals the hierarchy of Granger causality flow.\nUsing Kenneth French's business sector return time series, it is revealed that\nduring the Covid crisis, precious metals and pharmaceutical products are causal\ndrivers of the financial network. Moreover, the estimated Granger causality\nnetwork shows a high connectivity during crisis which means that the research\npresented here can be especially useful to better understand crises in the\nmarket by revealing the dominant drivers of the crisis dynamics.","PeriodicalId":501172,"journal":{"name":"arXiv - STAT - Applications","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Causal Hierarchy in the Financial Market Network -- Uncovered by the Helmholtz-Hodge-Kodaira Decomposition\",\"authors\":\"Tobias Wand, Oliver Kamps, Hiroshi Iyetomi\",\"doi\":\"arxiv-2408.12839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Granger causality can uncover the cause and effect relationships in financial\\nnetworks. However, such networks can be convoluted and difficult to interpret,\\nbut the Helmholtz-Hodge-Kodaira decomposition can split them into a rotational\\nand gradient component which reveals the hierarchy of Granger causality flow.\\nUsing Kenneth French's business sector return time series, it is revealed that\\nduring the Covid crisis, precious metals and pharmaceutical products are causal\\ndrivers of the financial network. Moreover, the estimated Granger causality\\nnetwork shows a high connectivity during crisis which means that the research\\npresented here can be especially useful to better understand crises in the\\nmarket by revealing the dominant drivers of the crisis dynamics.\",\"PeriodicalId\":501172,\"journal\":{\"name\":\"arXiv - STAT - Applications\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - STAT - Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2408.12839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.12839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
格兰杰因果关系可以揭示金融网络中的因果关系。利用 Kenneth French 的商业部门收益时间序列,可以发现在科维德危机期间,贵金属和医药产品是金融网络的因果驱动因素。此外,估计的格兰杰因果网络在危机期间显示出高度的连通性,这意味着本文的研究通过揭示危机动态的主导驱动因素,对更好地理解市场中的危机特别有用。
Causal Hierarchy in the Financial Market Network -- Uncovered by the Helmholtz-Hodge-Kodaira Decomposition
Granger causality can uncover the cause and effect relationships in financial
networks. However, such networks can be convoluted and difficult to interpret,
but the Helmholtz-Hodge-Kodaira decomposition can split them into a rotational
and gradient component which reveals the hierarchy of Granger causality flow.
Using Kenneth French's business sector return time series, it is revealed that
during the Covid crisis, precious metals and pharmaceutical products are causal
drivers of the financial network. Moreover, the estimated Granger causality
network shows a high connectivity during crisis which means that the research
presented here can be especially useful to better understand crises in the
market by revealing the dominant drivers of the crisis dynamics.