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Emergence of statistically validated financial intraday lead-lag relationships

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  • 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.

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Bibliographic Info

Paper provided by arXiv.org in its series Papers with number 1401.0462.

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Date of creation: Jan 2014
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Handle: RePEc:arx:papers:1401.0462

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  1. Allez, Romain & Bouchaud, Jean-Philippe, 2011. "Individual and collective stock dynamics: intra-day seasonalities," Economics Papers from University Paris Dauphine, Paris Dauphine University 123456789/10898, Paris Dauphine University.
  2. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, American Finance Association, vol. 57(5), pages 2223-2261, October.
  3. 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, Elsevier, vol. 287(3), pages 362-373.
  4. Giovanni Bonanno & Fabrizio Lillo & Rosario N. Mantegna, 2000. "High-frequency Cross-correlation in a Set of Stocks," Papers cond-mat/0009350, arXiv.org, revised Nov 2000.
  5. Dror Y. Kenett & Matthias Raddant & Thomas Lux & Eshel Ben-Jacob, 2011. "Evolvement of uniformity and volatility in the stressed global financial village," Kiel Working Papers 1739, Kiel Institute for the World Economy.
  6. Robert E. Hall, 2010. "Why Does the Economy Fall to Pieces after a Financial Crisis?," Journal of Economic Perspectives, American Economic Association, American Economic Association, vol. 24(4), pages 3-20, Fall.
  7. Campbell, Rachel A.J. & Forbes, Catherine S. & Koedijk, Kees G. & Kofman, Paul, 2008. "Increasing correlations or just fat tails?," Journal of Empirical Finance, Elsevier, Elsevier, vol. 15(2), pages 287-309, March.
  8. Pollet, Joshua M. & Wilson, Mungo, 2010. "Average correlation and stock market returns," Journal of Financial Economics, Elsevier, Elsevier, vol. 96(3), pages 364-380, June.
  9. Stephen Cecchetti & Enisse Kharroubi, 2012. "Reassessing the impact of finance on growth," BIS Working Papers 381, Bank for International Settlements.
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