IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v5y2005i6p519-521.html
   My bibliography  Save this article

Two phase behaviour and the distribution of volume

Author

Listed:
  • Vasiliki Plerou
  • Parameswaran Gopikrishnan
  • H. Eugene Stanley

Abstract

No abstract is available for this item.

Suggested Citation

  • Vasiliki Plerou & Parameswaran Gopikrishnan & H. Eugene Stanley, 2005. "Two phase behaviour and the distribution of volume," Quantitative Finance, Taylor & Francis Journals, vol. 5(6), pages 519-521.
    • Handle: RePEc:taf:quantf:v:5:y:2005:i:6:p:519-521
    DOI: 10.1080/14697680500406093
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/14697680500406093
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/14697680500406093?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. Vasiliki Plerou & Parameswaran Gopikrishnan & H. Eugene Stanley, 2003. "Two-phase behaviour of financial markets," Nature, Nature, vol. 421(6919), pages 130-130, January.
    2. Parameswaran Gopikrishnan & Vasiliki Plerou & Xavier Gabaix & H. Eugene Stanley, 2000. "Statistical Properties of Share Volume Traded in Financial Markets," Papers cond-mat/0008113, arXiv.org.
    3. Kaushik Matia & Kazuko Yamasaki, 2005. "Statistical Properties of Demand Fluctuation in the Financial Market," Papers physics/0502084, arXiv.org.
    4. Kaushik Matia & Kazuko Yamasaki, 2005. "Statistical properties of demand fluctuation in the financial market," Quantitative Finance, Taylor & Francis Journals, vol. 5(6), pages 513-517.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhaoyuan Li & Maozai Tian, 2017. "A New Method For Dynamic Stock Clustering Based On Spectral Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 373-392, October.
    2. Kang, Bo Soo & Park, Chanhi & Ryu, Doojin & Song, Wonho, 2015. "Phase transition phenomenon: A compound measure analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 383-395.
    3. Kozłowska, M. & Denys, M. & Wiliński, M. & Link, G. & Gubiec, T. & Werner, T.R. & Kutner, R. & Struzik, Z.R., 2016. "Dynamic bifurcations on financial markets," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 126-142.
    4. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "Why the long-term auto-correlation has not been eliminated by arbitragers: Evidences from NYMEX," Energy Economics, Elsevier, vol. 59(C), pages 167-178.
    5. Hwang, Keunho & Kang, Jangkoo & Ryu, Doojin, 2010. "Phase-transition behavior in the emerging market: Evidence from the KOSPI200 futures market," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 35-46, January.
    6. Kostanjcar, Zvonko & Jeren, Branko & Juretic, Zeljan, 2012. "Impact of uncertainty in expected return estimation on stock price volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5563-5571.
    7. Shanshan Wang & Thomas Guhr, 2017. "Local fluctuations of the signed traded volumes and the dependencies of demands: a copula analysis," Papers 1706.09240, arXiv.org, revised Apr 2018.

    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. Kozłowska, M. & Denys, M. & Wiliński, M. & Link, G. & Gubiec, T. & Werner, T.R. & Kutner, R. & Struzik, Z.R., 2016. "Dynamic bifurcations on financial markets," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 126-142.
    2. Kang, Bo Soo & Park, Chanhi & Ryu, Doojin & Song, Wonho, 2015. "Phase transition phenomenon: A compound measure analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 383-395.
    3. Nobi, Ashadun & Maeng, Seong Eun & Ha, Gyeong Gyun & Lee, Jae Woo, 2014. "Effects of global financial crisis on network structure in a local stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 135-143.
    4. Hwang, Keunho & Kang, Jangkoo & Ryu, Doojin, 2010. "Phase-transition behavior in the emerging market: Evidence from the KOSPI200 futures market," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 35-46, January.
    5. Stanley, H.Eugene, 2003. "Statistical physics and economic fluctuations: do outliers exist?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(1), pages 279-292.
    6. Shanshan Wang & Thomas Guhr, 2017. "Local fluctuations of the signed traded volumes and the dependencies of demands: a copula analysis," Papers 1706.09240, arXiv.org, revised Apr 2018.
    7. Thomas Lux, 2009. "Applications of Statistical Physics in Finance and Economics," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 9, Edward Elgar Publishing.
    8. Chen, Zhimin & Ibragimov, Rustam, 2019. "One country, two systems? The heavy-tailedness of Chinese A- and H- share markets," Emerging Markets Review, Elsevier, vol. 38(C), pages 115-141.
    9. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "The effect of fragmentation in trading on market quality in the UK equity market," CeMMAP working papers 42/13, Institute for Fiscal Studies.
    10. Nagarajan, Radhakrishnan & Kavasseri, Rajesh G., 2005. "Minimizing the effect of periodic and quasi-periodic trends in detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 26(3), pages 777-784.
    11. Stanley, H.Eugene & Nunes Amaral, Luis A. & Gabaix, Xavier & Gopikrishnan, Parameswaran & Plerou, Vasiliki, 2001. "Quantifying economic fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 302(1), pages 126-137.
    12. Neeraj, & Panigrahi, Prasanta K., 2017. "Causality and correlations between BSE and NYSE indexes: A Janus faced relationship," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 284-313.
    13. Jean-Philippe Bouchaud & Marc Mezard & Marc Potters, 2002. "Statistical properties of stock order books: empirical results and models," Science & Finance (CFM) working paper archive 0203511, Science & Finance, Capital Fund Management.
    14. J. Doyne Farmer & Austin Gerig & Fabrizio Lillo & Henri Waelbroeck, 2013. "How efficiency shapes market impact," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1743-1758, November.
    15. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical shape function of limit-order books in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5182-5188.
    16. J. Doyne Farmer & Laszlo Gillemot & Fabrizio Lillo & Szabolcs Mike & Anindya Sen, 2004. "What really causes large price changes?," Quantitative Finance, Taylor & Francis Journals, vol. 4(4), pages 383-397.
    17. Andrew Balthrop, 2016. "Power laws in oil and natural gas production," Empirical Economics, Springer, vol. 51(4), pages 1521-1539, December.
    18. Einmahl, John & He, Y., 2020. "Unified Extreme Value Estimation for Heterogeneous Data," Other publications TiSEM dfe6c38c-823b-4394-b4fd-a, Tilburg University, School of Economics and Management.
    19. 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.
    20. Nagarajan, Radhakrishnan & Kavasseri, Rajesh G., 2005. "Minimizing the effect of trends on detrended fluctuation analysis of long-range correlated noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 182-198.

    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:taf:quantf:v:5:y:2005:i:6:p:519-521. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RQUF20 .

    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.