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Phase Transition in the S&P Stock Market

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  • Matthias Raddant
  • Friedrich Wagner

Abstract

We analyze the stock prices of the S&P market from 1987 until 2012 with the covariance matrix of the firm returns determined in time windows of several years. The eigenvector belonging to the leading eigenvalue (market) exhibits in its long term time dependence a phase transition with an order parameter which can be interpreted within an agent-based model. From 1995 to 2005 the market is in an ordered state and after 2005 in a disordered state.

Suggested Citation

  • Matthias Raddant & Friedrich Wagner, 2013. "Phase Transition in the S&P Stock Market," Papers 1306.2508, arXiv.org, revised Jun 2015.
    • Handle: RePEc:arx:papers:1306.2508
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    1. Giacomo Livan & Jun-ichi Inoue & Enrico Scalas, 2012. "On the non-stationarity of financial time series: impact on optimal portfolio selection," Papers 1205.0877, arXiv.org, revised Jul 2012.
    2. Michael C. Munnix & Takashi Shimada & Rudi Schafer & Francois Leyvraz Thomas H. Seligman & Thomas Guhr & H. E. Stanley, 2012. "Identifying States of a Financial Market," Papers 1202.1623, arXiv.org.
    3. Stauffer, Dietrich & Sornette, Didier, 1999. "Self-organized percolation model for stock market fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 271(3), pages 496-506.
    4. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    5. Michel Beine & Bertrand Candelon, 2011. "Liberalisation and stock market co-movement between emerging economies," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 299-312.
    6. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(1), pages 137-156.
    7. Bodurtha, James N, Jr & Mark, Nelson C, 1991. "Testing the CAPM with Time-Varying Risks and Returns," Journal of Finance, American Finance Association, vol. 46(4), pages 1485-1505, September.
    8. Dror Y Kenett & Matthias Raddant & Thomas Lux & Eshel Ben-Jacob, 2012. "Evolvement of Uniformity and Volatility in the Stressed Global Financial Village," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-8, February.
    9. Wagner, Friedrich, 2006. "Application of Zhangs square root law and herding to financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 369-384.
    10. Gian Italo Bischi & Carl Chiarella & Laura Gardini (ed.), 2010. "Nonlinear Dynamics in Economics, Finance and Social Sciences," Springer Books, Springer, number 978-3-642-04023-8, December.
    11. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    12. Bos, T & Newbold, P, 1984. "An Empirical Investigation of the Possibility of Stochastic Systematic Risk in the Market Model," The Journal of Business, University of Chicago Press, vol. 57(1), pages 35-41, January.
    13. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    14. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    15. Burda, Z. & Görlich, A. & Jarosz, A. & Jurkiewicz, J., 2004. "Signal and noise in correlation matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 295-310.
    16. Galluccio, Stefano & Bouchaud, Jean-Philippe & Potters, Marc, 1998. "Rational decisions, random matrices and spin glasses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 259(3), pages 449-456.
    17. Cont, Rama & Bouchaud, Jean-Philipe, 2000. "Herd Behavior And Aggregate Fluctuations In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(2), pages 170-196, June.
    18. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2009. "A Framework for CAPM with Heterogenous Beliefs," Research Paper Series 254, Quantitative Finance Research Centre, University of Technology, Sydney.
    19. Pierre Cizeau & Marc Potters & Jean-Philippe Bouchaud, 2000. "Correlation structure of extreme stock returns," Papers cond-mat/0006034, arXiv.org, revised Jan 2001.
    20. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 19-49, August.
    21. G. Livan & S. Alfarano & E. Scalas, 2011. "The fine structure of spectral properties for random correlation matrices: an application to financial markets," Papers 1102.4076, arXiv.org.
    22. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    23. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    24. C. J. Adcock & M. Ceu Cortez & M. J. Rocha Armada & F. Silva, 2012. "Time varying betas and the unconditional distribution of asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 12(6), pages 951-967, November.
    25. Dror Y Kenett & Yoash Shapira & Asaf Madi & Sharron Bransburg-Zabary & Gitit Gur-Gershgoren & Eshel Ben-Jacob, 2011. "Index Cohesive Force Analysis Reveals That the US Market Became Prone to Systemic Collapses Since 2002," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-8, April.
    26. Lisa Borland & Yoan Hassid, 2010. "Market panic on different time-scales," Papers 1010.4917, arXiv.org.
    27. P. Cizeau & M. Potters & J-P. Bouchaud, 2001. "Correlation structure of extreme stock returns," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 217-222.
    28. Ahlgren, Niklas & Antell, Jan, 2010. "Stock market linkages and financial contagion: A cobreaking analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(2), pages 157-166, May.
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    Cited by:

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    2. Kyrtsou, Catherine & Mikropoulou, Christina & Papana, Angeliki, 2016. "Does the S&P500 index lead the crude oil dynamics? A complexity-based approach," Energy Economics, Elsevier, vol. 56(C), pages 239-246.

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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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