IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v387y2008i21p5205-5210.html
   My bibliography  Save this article

Multidimensional minimal spanning tree: The Dow Jones case

Author

Listed:
  • Brida, Juan Gabriel
  • Risso, Wiston Adrián

Abstract

This paper introduces a new methodology in order to construct Minimal Spanning Trees (MST) and Hierarchical Trees (HT) using the information provided by more than one variable. In fact, the Symbolic Time Series Analysis (STSA) approach is applied to the Dow Jones companies using information not only from asset returns but also for trading volume. The US stock market structure is obtained, showing eight clusters of companies and General Electric as a central node in the tree. We use different partitions showing that the results do not depend on the particular partition. In addition, we apply Monte Carlo simulations suggesting that the tree is not the result of random connections.

Suggested Citation

  • Brida, Juan Gabriel & Risso, Wiston Adrián, 2008. "Multidimensional minimal spanning tree: The Dow Jones case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5205-5210.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:21:p:5205-5210
    DOI: 10.1016/j.physa.2008.05.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437108004299
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2008.05.009?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. 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.
    2. Bonanno, Giovanni & Lillo, Fabrizio & Mantegna, Rosario N., 2001. "Levels of complexity in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 16-27.
    3. Morgan, I G, 1976. "Stock Prices and Heteroscedasticity," The Journal of Business, University of Chicago Press, vol. 49(4), pages 496-508, October.
    4. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    5. Westerfield, Randolph, 1977. "The Distribution of Common Stock Price Changes: An Application of Transactions Time and Subordinated Stochastic Models," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(5), pages 743-765, December.
    6. G. Bonanno & G. Caldarelli & F. Lillo & S. Micciché & N. Vandewalle & R. Mantegna, 2004. "Networks of equities in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 363-371, March.
    7. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    8. Rogalski, Richard J, 1978. "The Dependence of Prices and Volume," The Review of Economics and Statistics, MIT Press, vol. 60(2), pages 268-274, May.
    9. Halinen, Aino & Törnroos, Jan-Åke, 1998. "The role of embeddedness in the evolution of business networks," Scandinavian Journal of Management, Elsevier, vol. 14(3), pages 187-205, March.
    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. Brida, Juan Gabriel & Matesanz, David & Seijas, Maria Nela, 2016. "Network analysis of returns and volume trading in stock markets: The Euro Stoxx case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 751-764.
    2. Juan Gabriel Brida & W. Adrian Risso, 2009. "Dynamic and Structure of the Italian stock market based on returns and volume trading," Economics Bulletin, AccessEcon, vol. 29(3), pages 2417-2423.
    3. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    4. Chaido Dritsaki, 2014. "The Dynamic Relationship between Stock Volatility and Trading Volume from the Athens Stock Exchange," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 3(3), pages 152-165.
    5. Ugwu Ugwu & Sule & Kehinde Oluwatoyin & Emerole & Gideon Ahamuefula, 2011. "Stock Returns and Trading Volume Relationship of the Nigerian Banking Sector: An Empirical Assessment," Journal of Social and Development Sciences, AMH International, vol. 2(1), pages 5-13.
    6. Moosa, Imad A. & Al-Loughani, Nabeel E., 1995. "Testing the price-volume relation in emerging Asian stock markets," Journal of Asian Economics, Elsevier, vol. 6(3), pages 407-422.
    7. Wright, Calvin & Swidler, Steve, 2023. "Abnormal trading volume, news and market efficiency: Evidence from the Jamaica Stock Exchange," Research in International Business and Finance, Elsevier, vol. 64(C).
    8. Coletti, Paolo, 2016. "Comparing minimum spanning trees of the Italian stock market using returns and volumes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 246-261.
    9. Ferreira, Paulo, 2019. "Assessing the relationship between dependence and volume in stock markets: A dynamic analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 90-97.
    10. Sarika Mahajan & Balwinder Singh, 2013. "Return, Volume and Volatility Relationship in Indian Stock Market: Pre and Post Rolling Settlement Analysis," Global Business Review, International Management Institute, vol. 14(3), pages 413-428, September.
    11. Bajzik, Josef, 2021. "Trading volume and stock returns: A meta-analysis," International Review of Financial Analysis, Elsevier, vol. 78(C).
    12. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    13. Aki-Hiro Sato & Takaki Hayashi & Janusz Hołyst, 2012. "Comprehensive analysis of market conditions in the foreign exchange market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 167-179, October.
    14. Kausik Chaudhuri & Alok Kumar, 2015. "A Markov-Switching Model for Indian Stock Price and Volume," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 14(3), pages 239-257, December.
    15. Saswat Patra & Malay Bhattacharyya, 2021. "Does volume really matter? A risk management perspective using cross‐country evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 118-135, January.
    16. Marcus Alexander Ong, 2015. "An information theoretic analysis of stock returns, volatility and trading volumes," Applied Economics, Taylor & Francis Journals, vol. 47(36), pages 3891-3906, August.
    17. Cathy W. S. Chen & Mike K. P. So & Thomas C. Chiang, 2016. "Evidence of Stock Returns and Abnormal Trading Volume: A Threshold Quantile Regression Approach," The Japanese Economic Review, Springer, vol. 67(1), pages 96-124, March.
    18. Sensoy, Ahmet & Tabak, Benjamin M., 2014. "Dynamic spanning trees in stock market networks: The case of Asia-Pacific," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 387-402.
    19. Elena Kalotychou & Sotiris Staikouras, 2006. "Volatility and trading activity in Short Sterling futures," Applied Economics, Taylor & Francis Journals, vol. 38(9), pages 997-1005.
    20. Ming-Hsien Chen & Vivian Tai, 2014. "The price discovery of day trading activities in futures market," Review of Derivatives Research, Springer, vol. 17(2), pages 217-239, July.

    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:phsmap:v:387:y:2008:i:21:p:5205-5210. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.