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A study of correlations in the stock market

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  • Sharma, Chandradew
  • Banerjee, Kinjal

Abstract

We study the various sectors of the Bombay Stock Exchange (BSE) for a period of 8 years from April 2006 to March 2014. Using the data of daily returns of a period of eight years we make a direct model free analysis of the pattern of the sectorial indices movement and the correlations among them. Our analysis shows significant auto correlation among the individual sectors and also strong cross-correlation among sectors. We also find that auto correlations in some of the sectors persist in time. This is a very significant result and has not been reported so far in Indian context. These findings will be very useful in model building for prediction of price movement of equities, derivatives and portfolio management. We show that the Random Walk Hypothesis is not applicable in modeling the Indian market and mean–variance–skewness–kurtosis based portfolio optimization might be required. We also find that almost all sectors are highly correlated during large fluctuation periods and have only moderate correlation during normal periods.

Suggested Citation

  • Sharma, Chandradew & Banerjee, Kinjal, 2015. "A study of correlations in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 321-330.
    • Handle: RePEc:eee:phsmap:v:432:y:2015:i:c:p:321-330
    DOI: 10.1016/j.physa.2015.03.061
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    Citations

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    Cited by:

    1. Shilpa Srivastava & Millie Pant & Varuna Gupta, 2023. "Analysis and prediction of Indian stock market: a machine-learning approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(4), pages 1567-1585, August.
    2. Chatterjee, Soumya & Mukherjee, Indranil & Barat, P., 2018. "Analysis of the behaviour of the detrended BSE sensex data," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 186-196.
    3. Ming-Yuan Yang & Sai-Ping Li & Li-Xin Zhong & Fei Ren, 2018. "Modelling stock correlations with expected returns from investors," Papers 1803.02019, arXiv.org, revised Mar 2018.
    4. Anwesha Sengupta & Shashankaditya Upadhyay & Indranil Mukherjee & Prasanta K. Panigrahi, 2022. "Describing the effect of influential spreaders on the different sectors of Indian market: a complex networks perspective," Papers 2303.05432, arXiv.org.

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