Correlations, Delays and Financial Time Series

  • K. B. K. Mayya
  • M. S. Santhanam
Part of the New Economic Windows book series (NEW)


We study the returns of stock prices and show that in the context of data from Bombay stock exchange there are groups of stocks that remain moderately correlated for up to 3 days. We use the delay correlations to identify these groups of stocks. In contrast to the results of same-time correlation matrix analysis, the groups in this case do not appear to come from any industry segments. We present our results using the closing prices of 326 significant stocks of Bombay stock exchange for the period 1995 to 2005.


Stock Market Stock Prex Financial Time Series Market Mode Eigenvalue Density 
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  1. 1.
    Gabaix X et. al. (2003) A Theory of Power-Law Distributions in Financial Market Fluctuations, Nature 423:267–270.CrossRefADSGoogle Scholar
  2. 2.
    Plerou V et. al. (2002) Random Matrix approach to Cross-Correlations in Financial Data, Phys. Rev. E, 65:066126CrossRefADSGoogle Scholar
  3. 3.
    Liu Y et. al. (1999) Statistical properties of the volatility of price fluctuations, Phys. Rev. E, 60:1390.CrossRefADSGoogle Scholar
  4. 4.
    Sinha S, Pan RK (in this volume).Google Scholar
  5. 5.
    Lo AW, MacKinlay AC (1990) Review of Financial Studies 3:175–276.CrossRefGoogle Scholar
  6. 6.
    Mayya KBK, Amritkar RE (2006) cond-mat/0601279.Google Scholar
  7. 7.
    Biely C, Thurner S (2006) physics/0609053.Google Scholar

Copyright information

© Springer-Verlag Italia 2007

Authors and Affiliations

  • K. B. K. Mayya
    • 1
  • M. S. Santhanam
    • 1
  1. 1.Physical Research LaboratoryNavrangpura, AhmedabadIndia

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