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Correlation and volatility in an Indian stock market: A random matrix approach

  • Varsha Kulkarni
  • Nivedita Deo

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    We examine the volatility of an Indian stock market in terms of correlation of stocks and quantify the volatility using the random matrix approach. First we discuss trends observed in the pattern of stock prices in the Bombay Stock Exchange for the three-year period 2000–2002. Random matrix analysis is then applied to study the relationship between the coupling of stocks and volatility. The study uses daily returns of 70 stocks for successive time windows of length 85 days for the year 2001. We compare the properties of matrix C of correlations between price fluctuations in time regimes characterized by different volatilities. Our analyses reveal that (i) the largest (deviating) eigenvalue of C correlates highly with the volatility of the index, (ii) there is a shift in the distribution of the components of the eigenvector corresponding to the largest eigenvalue across regimes of different volatilities, (iii) the inverse participation ratio for this eigenvector anti-correlates significantly with the market fluctuations and finally, (iv) this eigenvector of C can be used to set up a Correlation Index, CI whose temporal evolution is significantly correlated with the volatility of the overall market index. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007

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    File URL: http://hdl.handle.net/10.1140/epjb/e2007-00322-1
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    Article provided by Springer in its journal The European Physical Journal B.

    Volume (Year): 60 (2007)
    Issue (Month): 1 (November)
    Pages: 101-109

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    Handle: RePEc:spr:eurphb:v:60:y:2007:i:1:p:101-109
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    1. Simone Bianco & Roberto Reno, 2009. "Unexpected volatility and intraday serial correlation," Quantitative Finance, Taylor & Francis Journals, vol. 9(4), pages 465-475.
    2. Simone Bianco & Roberto Ren\'o, 2006. "Unexpected volatility and intraday serial correlation," Papers physics/0610023, arXiv.org.
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