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Emergence of statistically validated financial intraday lead-lag relationships

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Listed:
  • Chester Curme
  • Michele Tumminello
  • Rosario N. Mantegna
  • H. Eugene Stanley
  • Dror Y. Kenett

Abstract

According to the leading models in modern finance, the presence of intraday lead-lag relationships between financial assets is negligible in efficient markets. With the advance of technology, however, markets have become more sophisticated. To determine whether this has resulted in an improved market efficiency, we investigate whether statistically significant lagged correlation relationships exist in financial markets. We introduce a numerical method to statistically validate links in correlation-based networks, and employ our method to study lagged correlation networks of equity returns in financial markets. Crucially, our statistical validation of lead-lag relationships accounts for multiple hypothesis testing over all stock pairs. In an analysis of intraday transaction data from the periods 2002--2003 and 2011--2012, we find a striking growth in the networks as we increase the frequency with which we sample returns. We compute how the number of validated links and the magnitude of correlations change with increasing sampling frequency, and compare the results between the two data sets. Finally, we compare topological properties of the directed correlation-based networks from the two periods using the in-degree and out-degree distributions and an analysis of three-node motifs. Our analysis suggests a growth in both the efficiency and instability of financial markets over the past decade.

Suggested Citation

  • Chester Curme & Michele Tumminello & Rosario N. Mantegna & H. Eugene Stanley & Dror Y. Kenett, 2014. "Emergence of statistically validated financial intraday lead-lag relationships," Papers 1401.0462, arXiv.org.
  • Handle: RePEc:arx:papers:1401.0462
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    References listed on IDEAS

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    1. Stephen Cecchetti & Enisse Kharroubi, 2012. "Reassessing the impact of finance on growth," BIS Working Papers 381, Bank for International Settlements.
    2. 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.
    3. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    4. Campbell, Rachel A.J. & Forbes, Catherine S. & Koedijk, Kees G. & Kofman, Paul, 2008. "Increasing correlations or just fat tails?," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 287-309, March.
    5. Kenett, Dror Y. & Raddant, Matthias & Lux, Thomas & Ben-Jacob, Eshel, 2011. "Evolvement of uniformity and volatility in the stressed global financial village," Kiel Working Papers 1739, Kiel Institute for the World Economy (IfW).
    6. Pollet, Joshua M. & Wilson, Mungo, 2010. "Average correlation and stock market returns," Journal of Financial Economics, Elsevier, vol. 96(3), pages 364-380, June.
    7. Gopikrishnan, P & Plerou, V & Liu, Y & Amaral, L.A.N & Gabaix, X & Stanley, H.E, 2000. "Scaling and correlation in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 362-373.
    8. Robert E. Hall, 2010. "Why Does the Economy Fall to Pieces after a Financial Crisis?," Journal of Economic Perspectives, American Economic Association, vol. 24(4), pages 3-20, Fall.
    9. repec:dau:papers:123456789/10898 is not listed on IDEAS
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    Citations

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    Cited by:

    1. Rodriguez, E. & Aguilar-Cornejo, M. & Femat, R. & Alvarez-Ramirez, J., 2014. "US stock market efficiency over weekly, monthly, quarterly and yearly time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 554-564.
    2. Jacopo Rocchi & Enoch Yan Lok Tsui & David Saad, 2016. "Emerging interdependence between stock values during financial crashes," Papers 1611.02549, arXiv.org.
    3. Puccio, Elena & Pajala, Antti & Piilo, Jyrki & Tumminello, Michele, 2016. "Structure and evolution of a European Parliament via a network and correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 167-185.
    4. Chester Curme & H. Eugene Stanley & Irena Vodenska, 2015. "Coupled Network Approach To Predictability Of Financial Market Returns And News Sentiments," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 18(07), pages 1-26, November.
    5. 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 Sep 2017.
    6. Stefan Lyocsa & Tomas Vyrost & Eduard Baumohl, 2015. "Return spillovers around the globe: A network approach," Papers 1507.06242, arXiv.org, revised Nov 2015.
    7. Irena Vodenska & Alexander P. Becker & Di Zhou & Dror Y. Kenett & H. Eugene Stanley & Shlomo Havlin, 2016. "Community Analysis of Global Financial Markets," Risks, MDPI, Open Access Journal, vol. 4(2), pages 1-15, May.
    8. Chuang, Hongwei, 2016. "Brokers’ financial network and stock return," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 172-183.
    9. repec:gam:jrisks:v:4:y:2016:i:2:p:13:d:70032 is not listed on IDEAS
    10. Damien Challet & R'emy Chicheportiche & Mehdi Lallouache & Serge Kassibrakis, 2016. "Trader lead-lag networks and order flow prediction," Papers 1609.04640, arXiv.org, revised Feb 2017.

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