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Uncovering the Internal Structure of the Indian Financial Market: Cross-correlation behavior in the NSE

Listed author(s):
  • Sitabhra Sinha
  • Raj Kumar Pan

The cross-correlations between price fluctuations of 201 frequently traded stocks in the National Stock Exchange (NSE) of India are analyzed in this paper. We use daily closing prices for the period 1996-2006, which coincides with the period of rapid transformation of the market following liberalization. The eigenvalue distribution of the cross-correlation matrix, $\mathbf{C}$, of NSE is found to be similar to that of developed markets, such as the New York Stock Exchange (NYSE): the majority of eigenvalues fall within the bounds expected for a random matrix constructed from mutually uncorrelated time series. Of the few largest eigenvalues that deviate from the bulk, the largest is identified with market-wide movements. The intermediate eigenvalues that occur between the largest and the bulk have been associated in NYSE with specific business sectors with strong intra-group interactions. However, in the Indian market, these deviating eigenvalues are comparatively very few and lie much closer to the bulk. We propose that this is because of the relative lack of distinct sector identity in the market, with the movement of stocks dominantly influenced by the overall market trend. This is shown by explicit construction of the interaction network in the market, first by generating the minimum spanning tree from the unfiltered correlation matrix, and later, using an improved method of generating the graph after filtering out the market mode and random effects from the data. Both methods show, compared to developed markets, the relative absence of clusters of co-moving stocks that belong to the same business sector. This is consistent with the general belief that emerging markets tend to be more correlated than developed markets.

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Paper provided by in its series Papers with number 0704.2115.

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Date of creation: Apr 2007
Publication status: Published in Econophysics of Markets and Business Networks, (Springer, Milan, 2007) p. 3-19
Handle: RePEc:arx:papers:0704.2115
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  1. Dong-Hee Kim & Hawoong Jeong, 2005. "Systematic analysis of group identification in stock markets," Papers physics/0503076,, revised Oct 2005.
  2. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
  3. Goetzmann, William N. & Rouwenhorst, K. Geert (ed.), 2005. "The Origins of Value: The Financial Innovations that Created Modern Capital Markets," OUP Catalogue, Oxford University Press, number 9780195175714.
  4. Laurent Laloux & Pierre Cizeau & Jean-Philippe Bouchaud & Marc Potters, 1998. "Noise dressing of financial correlation matrices," Science & Finance (CFM) working paper archive 500051, Science & Finance, Capital Fund Management.
  5. V. Kulkarni & N. Deo, 2005. "Volatility of an Indian stock market : A random matrix approach," Papers physics/0512169,
  6. Çukur, Sadik & Eryiğit, Mehmet & Eryiğit, Resul, 2007. "Cross correlations in an emerging market financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 555-564.
  7. Sitabhra Sinha & Raj Kumar Pan, 2006. "The Power (Law) of Indian Markets: Analysing NSE and BSE trading statistics," Papers physics/0605247,
  8. Wilcox, Diane & Gebbie, Tim, 2004. "On the analysis of cross-correlations in South African market data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 294-298.
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