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Dynamic topology and allometric scaling behavior on the Vietnamese stock market

Author

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  • Nguyen, Q.
  • Nguyen, N.K. K.
  • Nguyen, L.H. N.

Abstract

The impact of the Vietnamese financial crisis during 2011–2012 into the stock market was revealed by a structural change of the minimum spanning tree (MST) constructed from the daily stock price. We found that the MST has a star-like structure during this period, similar to that of the German market during the worldwide financial crisis of 2007–2008 (M. Wiliski et al., 2013), and a hierarchical scale-free structure for the rest of time. In addition, we investigate the market from a complex network perspective by analyzing the allometric scaling behavior. We found that all networks have the allometric scaling property, with exponent η ranging from 1.213±0.013 during the financial instability period to about 1.357±0.011 in normal time. These values correspond to a complex “dimension” of the financial market of between 3 and 5, which need to be further investigated in the future.

Suggested Citation

  • Nguyen, Q. & Nguyen, N.K. K. & Nguyen, L.H. N., 2019. "Dynamic topology and allometric scaling behavior on the Vietnamese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 235-243.
  • Handle: RePEc:eee:phsmap:v:514:y:2019:i:c:p:235-243
    DOI: 10.1016/j.physa.2018.09.061
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    as
    1. G. Bonanno & F. Lillo & R. N. Mantegna, 2001. "High-frequency cross-correlation in a set of stocks," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 96-104.
    2. Wiliński, M. & Sienkiewicz, A. & Gubiec, T. & Kutner, R. & Struzik, Z.R., 2013. "Structural and topological phase transitions on the German Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5963-5973.
    3. Stefan Thurner & J. Doyne Farmer & John Geanakoplos, 2012. "Leverage causes fat tails and clustered volatility," Quantitative Finance, Taylor & Francis Journals, vol. 12(5), pages 695-707, February.
    4. 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.
    5. Grigory Bautin & Valery Kalyagin & Alexander Koldanov & Petr Koldanov & Panos Pardalos, 2013. "Simple measure of similarity for the market graph construction," Computational Management Science, Springer, vol. 10(2), pages 105-124, June.
    6. Garas, Antonios & Argyrakis, Panos, 2007. "Correlation study of the Athens Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 399-410.
    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.
    8. Li, Shouwei & He, Jianmin & Zhuang, Yaming, 2010. "A network model of the interbank market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5587-5593.
    9. C. Coronnello & M. Tumminello & F. Lillo & S. Miccich`e & R. N. Mantegna, 2005. "Sector identification in a set of stock return time series traded at the London Stock Exchange," Papers cond-mat/0508122, arXiv.org.
    10. A. Sienkiewicz & T. Gubiec & R. Kutner & Z. R. Struzik, 2013. "Dynamic structural and topological phase transitions on the Warsaw Stock Exchange: A phenomenological approach," Papers 1301.6506, arXiv.org.
    11. Djauhari, Maman A., 2012. "A robust filter in stock networks analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 5049-5057.
    12. Jean-Philippe Bouchaud, 2008. "Economics need a scientific revolution," Papers 0810.5306, arXiv.org.
    13. Djauhari, Maman Abdurachman & Gan, Siew Lee, 2013. "Minimal spanning tree problem in stock networks analysis: An efficient algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2226-2234.
    14. M. Wili'nski & A. Sienkiewicz & T. Gubiec & R. Kutner & Z. R. Struzik, 2013. "Structural and topological phase transitions on the German Stock Exchange," Papers 1301.2530, arXiv.org, revised Jul 2013.
    15. repec:dau:papers:123456789/10757 is not listed on IDEAS
    16. 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.
    17. Mark Buchanan, 2009. "Economics: Meltdown modelling," Nature, Nature, vol. 460(7256), pages 680-682, August.
    18. Delphine Lautier and Franck Raynaud, 2012. "Systemic Risk in Energy Derivative Markets: A Graph-Theory Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    19. Delphine Lautier & Franck Raynaud, 2012. "Systemic risk in energy derivative markets: a graph theory analysis," Post-Print halshs-00738201, HAL.
    20. J. Doyne Farmer & Duncan Foley, 2009. "The economy needs agent-based modelling," Nature, Nature, vol. 460(7256), pages 685-686, August.
    21. A. Z. Górski & S. Drożdż & J. Kwapień, 2008. "Scale free effects in world currency exchange network," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 66(1), pages 91-96, November.
    22. Jayanth R. Banavar & Amos Maritan & Andrea Rinaldo, 1999. "Size and form in efficient transportation networks," Nature, Nature, vol. 399(6732), pages 130-132, May.
    23. Wang, Gang-Jin & Xie, Chi & Han, Feng & Sun, Bo, 2012. "Similarity measure and topology evolution of foreign exchange markets using dynamic time warping method: Evidence from minimal spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(16), pages 4136-4146.
    24. 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.
    25. A. Z. Gorski & S. Drozdz & J. Kwapien, 2008. "Scale free effects in world currency exchange network," Papers 0810.1215, arXiv.org.
    26. Jean-Philippe Bouchaud, 2008. "Economics needs a scientific revolution," Nature, Nature, vol. 455(7217), pages 1181-1181, October.
    27. Boginski, Vladimir & Butenko, Sergiy & Pardalos, Panos M., 2005. "Statistical analysis of financial networks," Computational Statistics & Data Analysis, Elsevier, vol. 48(2), pages 431-443, February.
    28. Diego Garlaschelli & Guido Caldarelli & Luciano Pietronero, 2003. "Universal scaling relations in food webs," Nature, Nature, vol. 423(6936), pages 165-168, May.
    29. repec:dau:papers:123456789/9709 is not listed on IDEAS
    30. N. Vandewalle & F. Brisbois & X. Tordoir, 2001. "Non-random topology of stock markets," Quantitative Finance, Taylor & Francis Journals, vol. 1(3), pages 372-374, March.
    Full references (including those not matched with items on IDEAS)

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