IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1703.08781.html
   My bibliography  Save this paper

Emergence of world-stock-market network

Author

Listed:
  • M. Saeedian
  • T. Jamali
  • M. Z. Kamali
  • H. Bayani
  • T. Yasseri
  • G. R. Jafari

Abstract

In the age of globalization, it is natural that the stock market of each country is not independent form the other markets. In this case, collective behavior could be emerged form their dependency together. This article studies the collective behavior of a set of forty influential markets in the world economy with the aim of exploring a global financial structure that could be called world-stock-market network. Towards this end, we analyze the cross-correlation matrix of the indices of these forty markets using Random Matrix Theory (RMT). We find the degree of collective behavior among the markets and the share of each market in their structural formation. This finding together with the results obtained from the same calculation on four stock markets reinforce the idea of a world financial market. Finally, we draw the dendrogram of the cross-correlation matrix to make communities in this abstract global market visible. The dendrogram, drawn by at least thirty percent of correlation, shows that the world financial market comprises three communities each of which includes stock markets with geographical proximity.

Suggested Citation

  • M. Saeedian & T. Jamali & M. Z. Kamali & H. Bayani & T. Yasseri & G. R. Jafari, 2017. "Emergence of world-stock-market network," Papers 1703.08781, arXiv.org.
  • Handle: RePEc:arx:papers:1703.08781
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1703.08781
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Raj Kumar Pan & Sitabhra Sinha, 2007. "Collective behavior of stock price movements in an emerging market," Papers 0704.0773, arXiv.org, revised Nov 2007.
    2. A. Namaki & R. Raei & G. R. Jafari, 2011. "Comparing Tehran Stock Exchange As An Emerging Market With A Mature Market By Random Matrix Approach," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 371-383.
    3. Vasiliki Plerou & Parameswaran Gopikrishnan & Bernd Rosenow & Luis A. Nunes Amaral & H. Eugene Stanley, 1999. "Universal and non-universal properties of cross-correlations in financial time series," Papers cond-mat/9902283, arXiv.org.
    4. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871.
    5. Mobarhan, N.S. Safavi & Saeedi, A. & Roodposhti, F. Rahnamay & Jafari, G.R., 2016. "Network trending; leadership, followership and neutrality among companies: A random matrix approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 858-863.
    6. Plerou, V. & Gopikrishnan, P. & Rosenow, B. & Amaral, L.A.N. & Stanley, H.E., 2001. "Collective behavior of stock price movements—a random matrix theory approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 175-180.
    7. Namaki, A. & Jafari, G.R. & Raei, R., 2011. "Comparing the structure of an emerging market with a mature one under global perturbation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(17), pages 3020-3025.
    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. Hanie. Vahabi & Ali Namaki & Reza Raei, 2020. "Comparing the collective behavior of banking industry," Papers 2011.02026, arXiv.org.
    2. Manavi, Seyed Alireza & Jafari, Gholamreza & Rouhani, Shahin & Ausloos, Marcel, 2020. "Demythifying the belief in cryptocurrencies decentralized aspects. A study of cryptocurrencies time cross-correlations with common currencies, commodities and financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    3. Eterovic, Nicolas A. & Eterovic, Dalibor S., 2013. "Separating the wheat from the chaff: Understanding portfolio returns in an emerging market," Emerging Markets Review, Elsevier, vol. 16(C), pages 145-169.
    4. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2018. "Collective behavior of cryptocurrency price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 499-509.
    5. Kumar, Sushil & Kumar, Sunil & Kumar, Pawan, 2020. "Diffusion entropy analysis and random matrix analysis of the Indian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    6. Wang, Gang-Jin & Xie, Chi & Chen, Shou & Yang, Jiao-Jiao & Yang, Ming-Yan, 2013. "Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3715-3730.
    7. Chun-Xiao Nie, 2021. "Studying the correlation structure based on market geometry," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 411-441, April.
    8. Sharifi, S. & Crane, M. & Shamaie, A. & Ruskin, H., 2004. "Random matrix theory for portfolio optimization: a stability approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 335(3), pages 629-643.
    9. Muchnik, Lev & Bunde, Armin & Havlin, Shlomo, 2009. "Long term memory in extreme returns of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4145-4150.
    10. Michelle B Graczyk & Sílvio M Duarte Queirós, 2017. "Intraday seasonalities and nonstationarity of trading volume in financial markets: Collective features," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    11. Basnarkov, Lasko & Stojkoski, Viktor & Utkovski, Zoran & Kocarev, Ljupco, 2019. "Correlation patterns in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1026-1037.
    12. Pafka, Szilárd & Kondor, Imre, 2001. "Evaluating the RiskMetrics methodology in measuring volatility and Value-at-Risk in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 305-310.
    13. 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.
    14. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: I. Empirical facts," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 991-1012.
    15. Chen, Huan & Mai, Yong & Li, Sai-Ping, 2014. "Analysis of network clustering behavior of the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 360-367.
    16. Ouyang, F.Y. & Zheng, B. & Jiang, X.F., 2014. "Spatial and temporal structures of four financial markets in Greater China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 236-244.
    17. Civitarese, Jamil, 2016. "Volatility and correlation-based systemic risk measures in the US market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 459(C), pages 55-67.
    18. Nguyen, Q. & Nguyen, N.K.K., 2019. "Composition of the first principal component of a stock index — A comparison between SP500 and VNIndex," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    19. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    20. Christian Walter, 2020. "Sustainable Financial Risk Modelling Fitting the SDGs: Some Reflections," Sustainability, MDPI, vol. 12(18), pages 1-28, September.

    More about this item

    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:arx:papers:1703.08781. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.