IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v58y2021ics106294082100084x.html
   My bibliography  Save this article

Identifying states of global financial market based on information flow network motifs

Author

Listed:
  • Xie, Wen-Jie
  • Yong, Yang
  • Wei, Na
  • Yue, Peng
  • Zhou, Wei-Xing

Abstract

Stock markets exhibit different states due to internal and external shocks. It is of great significance to identify the status of global financial markets. Based on 48 global stock indices from 1996 to 2018, we constructed a global stock index transfer entropy network, which represents the information flow between stock markets in different economies. By analyzing the triadic motifs in the transfer entropy network, we divided the global stock market into different market states based on the distribution of motifs. The characteristic structure of information flow was observed in different market states. We found that the information flow in the global stock market increases significantly during major financial events, indicating that the global stock index has a mutual influence and a close relationship with each other. In addition, stock indices in the Asia-Pacific, Middle East, and Africa are the main sinks of information, while stock indices in the Americas and Europe are the primary sources of information.

Suggested Citation

  • Xie, Wen-Jie & Yong, Yang & Wei, Na & Yue, Peng & Zhou, Wei-Xing, 2021. "Identifying states of global financial market based on information flow network motifs," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    • Handle: RePEc:eee:ecofin:v:58:y:2021:i:c:s106294082100084x
    DOI: 10.1016/j.najef.2021.101459
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S106294082100084X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2021.101459?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. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    2. Dimpfl Thomas & Peter Franziska Julia, 2013. "Using transfer entropy to measure information flows between financial markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 85-102, February.
    3. Mantalos Panagiotis, 2000. "A Graphical Investigation of the Size and Power of the Granger-Causality Tests in Integrated-Cointegrated VAR Systems," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(1), pages 1-18, April.
    4. Kwon, Okyu & Yang, Jae-Suk, 2008. "Information flow between composite stock index and individual stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2851-2856.
    5. Jinkyu Kim & Gunn Kim & Sungbae An & Young-Kyun Kwon & Sungroh Yoon, 2013. "Entropy-Based Analysis and Bioinformatics-Inspired Integration of Global Economic Information Transfer," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-10, January.
    6. Michael C. Munnix & Takashi Shimada & Rudi Schafer & Francois Leyvraz Thomas H. Seligman & Thomas Guhr & H. E. Stanley, 2012. "Identifying States of a Financial Market," Papers 1202.1623, arXiv.org.
    7. Chiou-Wei, Song Zan & Chen, Ching-Fu & Zhu, Zhen, 2008. "Economic growth and energy consumption revisited -- Evidence from linear and nonlinear Granger causality," Energy Economics, Elsevier, vol. 30(6), pages 3063-3076, November.
    8. Qiu, Lu & Yang, Huijie, 2020. "Transfer entropy calculation for short time sequences with application to stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    9. 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.
    10. Fujio Toriumi & Kazuki Komura, 2018. "Investment Index Construction from Information Propagation Based on Transfer Entropy," Computational Economics, Springer;Society for Computational Economics, vol. 51(1), pages 159-172, January.
    11. Seung Ki Baek & Woo-Sung Jung & Okyu Kwon & Hie-Tae Moon, 2005. "Transfer Entropy Analysis of the Stock Market," Papers physics/0509014, arXiv.org, revised Sep 2005.
    12. Lu, Feng-bin & Hong, Yong-miao & Wang, Shou-yang & Lai, Kin-keung & Liu, John, 2014. "Time-varying Granger causality tests for applications in global crude oil markets," Energy Economics, Elsevier, vol. 42(C), pages 289-298.
    13. Balcilar, Mehmet & Gungor, Hasan & Hammoudeh, Shawkat, 2015. "The time-varying causality between spot and futures crude oil prices: A regime switching approach," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 51-71.
    14. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality," Energy Economics, Elsevier, vol. 30(5), pages 2673-2685, September.
    15. He, Jiayi & Shang, Pengjian, 2017. "Comparison of transfer entropy methods for financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 772-785.
    16. Huang, Wei-Qiang & Zhuang, Xin-Tian & Yao, Shuang, 2009. "A network analysis of the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2956-2964.
    17. Okyu Kwon & Jae-Suk Yang, 2008. "Information flow between stock indices," Papers 0802.1747, arXiv.org.
    18. Dimpfl, Thomas & Peter, Franziska J., 2014. "The impact of the financial crisis on transatlantic information flows: An intraday analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 1-13.
    19. Warr, B.S. & Ayres, R.U., 2010. "Evidence of causality between the quantity and quality of energy consumption and economic growth," Energy, Elsevier, vol. 35(4), pages 1688-1693.
    20. Lee, Chien-Chiang, 2006. "The causality relationship between energy consumption and GDP in G-11 countries revisited," Energy Policy, Elsevier, vol. 34(9), pages 1086-1093, June.
    21. Peng Yue & Yaodong Fan & Jonathan A. Batten & Wei-Xing Zhou, 2020. "Information transfer between stock market sectors: A comparison between the USA and China," Papers 2004.07612, arXiv.org.
    22. Li, Ping & Wang, Bing-Hong, 2007. "Extracting hidden fluctuation patterns of Hang Seng stock index from network topologies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 519-526.
    23. Hammoudeh, Shawkat & Li, Huimin & Jeon, Bang, 2003. "Causality and volatility spillovers among petroleum prices of WTI, gasoline and heating oil in different locations," The North American Journal of Economics and Finance, Elsevier, vol. 14(1), pages 89-114, March.
    24. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-1167, July.
    25. Li Zhou & Lu Qiu & Changgui Gu & Huijie Yang, 2018. "Immediate Causality Network of Stock Markets," Papers 1802.02699, arXiv.org.
    26. Geweke, John, 1984. "Inference and causality in economic time series models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 19, pages 1101-1144, Elsevier.
    27. Tse, Chi K. & Liu, Jing & Lau, Francis C.M., 2010. "A network perspective of the stock market," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 659-667, September.
    28. Bilal Ahmed Memon & Hongxing Yao & Rabia Tahir, 2020. "General election effect on the network topology of Pakistan’s stock market: network-based study of a political event," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-14, December.
    29. Ghazi Shukur & Panagiotis Mantalos, 2000. "A simple investigation of the Granger-causality test in integrated-cointegrated VAR systems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(8), pages 1021-1031.
    30. Jizba, Petr & Kleinert, Hagen & Shefaat, Mohammad, 2012. "Rényi’s information transfer between financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(10), pages 2971-2989.
    31. Jan Bentzen, 2007. "Does OPEC influence crude oil prices? Testing for co-movements and causality between regional crude oil prices," Applied Economics, Taylor & Francis Journals, vol. 39(11), pages 1375-1385.
    32. Granger, C. W. J., 1980. "Testing for causality : A personal viewpoint," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 329-352, May.
    33. Gross, Christian, 2012. "Explaining the (non-) causality between energy and economic growth in the U.S.—A multivariate sectoral analysis," Energy Economics, Elsevier, vol. 34(2), pages 489-499.
    34. Lee, Chien-Chiang & Chang, Chun-Ping & Chen, Pei-Fen, 2008. "Energy-income causality in OECD countries revisited: The key role of capital stock," Energy Economics, Elsevier, vol. 30(5), pages 2359-2373, September.
    35. Qiu, Lu & Gu, Changgui & Xiao, Qin & Yang, Huijie & Wu, Guolin, 2018. "State network approach to characteristics of financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1120-1128.
    36. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    37. Zhang, Yue-Jun & Wei, Yi-Ming, 2010. "The crude oil market and the gold market: Evidence for cointegration, causality and price discovery," Resources Policy, Elsevier, vol. 35(3), pages 168-177, September.
    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. Nie, Chun-Xiao, 2023. "Time-varying characteristics of information flow networks in the Chinese market: An analysis based on sector indices," Finance Research Letters, Elsevier, vol. 54(C).
    2. Leonidas Sandoval Junior & Asher Mullokandov & Dror Y. Kenett, 2015. "Dependency Relations among International Stock Market Indices," JRFM, MDPI, vol. 8(2), pages 1-39, May.
    3. Banerjee, Ameet Kumar & Akhtaruzzaman, Md & Dionisio, Andreia & Almeida, Dora & Sensoy, Ahmet, 2022. "Nonlinear nexus between cryptocurrency returns and COVID-19 news sentiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    4. Theo Diamandis & Yonathan Murin & Andrea Goldsmith, 2018. "Ranking Causal Influence of Financial Markets via Directed Information Graphs," Papers 1801.06896, arXiv.org.
    5. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    6. Nicoló Andrea Caserini & Paolo Pagnottoni, 2022. "Effective transfer entropy to measure information flows in credit markets," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 729-757, October.
    7. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    8. Lim, Kyuseong & Kim, Sehyun & Kim, Soo Yong, 2017. "Information transfer across intra/inter-structure of CDS and stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 118-126.
    9. Qiu, Lu & Yang, Huijie, 2020. "Transfer entropy calculation for short time sequences with application to stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    10. Dergiades, Theologos & Martinopoulos, Georgios & Tsoulfidis, Lefteris, 2013. "Energy consumption and economic growth: Parametric and non-parametric causality testing for the case of Greece," Energy Economics, Elsevier, vol. 36(C), pages 686-697.
    11. Smyth, Russell & Narayan, Paresh Kumar, 2015. "Applied econometrics and implications for energy economics research," Energy Economics, Elsevier, vol. 50(C), pages 351-358.
    12. Shao, Ying-Hui & Yang, Yan-Hong & Shao, Hao-Lin & Stanley, H. Eugene, 2019. "Time-varying lead–lag structure between the crude oil spot and futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 723-733.
    13. Leonidas Sandoval Junior, 2014. "Dynamics in two networks based on stocks of the US stock market," Papers 1408.1728, arXiv.org, revised Aug 2014.
    14. Dimpfl, Thomas & Peter, Franziska J., 2014. "The impact of the financial crisis on transatlantic information flows: An intraday analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 1-13.
    15. Shahateet, Mohammed Issa & Al-Majali, Khalid Ali & Al-Hahabashneh, Fedel, 2014. "Causality and Cointegration between Economic Growth and Energy Consumption: Econometric Evidence from Jordan," MPRA Paper 59067, University Library of Munich, Germany, revised Oct 2014.
    16. Neto, David, 2022. "Examining interconnectedness between media attention and cryptocurrency markets: A transfer entropy story," Economics Letters, Elsevier, vol. 214(C).
    17. Stern, David I. & Enflo, Kerstin, 2013. "Causality between energy and output in the long-run," Energy Economics, Elsevier, vol. 39(C), pages 135-146.
    18. Lu, Jingen & Chen, Xiaohong & Liu, Xiaoxing, 2018. "Stock market information flow: Explanations from market status and information-related behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 837-848.
    19. Gross, Christian, 2012. "Explaining the (non-) causality between energy and economic growth in the U.S.—A multivariate sectoral analysis," Energy Economics, Elsevier, vol. 34(2), pages 489-499.
    20. Dima, Bogdan & Dima, Ştefana Maria & Barna, Flavia, 2014. "The signaling effect of tax rates under fiscal competition: A (Shannonian) transfer entropy approach," Economic Modelling, Elsevier, vol. 42(C), pages 373-381.

    More about this item

    Keywords

    Global stock market; Market state; Information flow; Network motifs; Clustering;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • P4 - Political Economy and Comparative Economic Systems - - Other Economic Systems
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

    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:58:y:2021:i:c:s106294082100084x. 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.