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Understanding the pattern of the BSE Sensex

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  • Mukherjee, I.
  • Chatterjee, Soumya
  • Giri, A.
  • Barat, P.

Abstract

An attempt is made to understand the pattern of behaviour of the BSE Sensex by analysing the tick-by-tick Sensex data for the years 2006 to 2012 on yearly as well as cumulative basis using Principal Component Analysis (PCA) and its nonlinear variant Kernel Principal Component Analysis (KPCA). The latter technique ensures that the nonlinear character of the interactions present in the system gets captured in the analysis. The analysis is carried out by constructing vector spaces of varying dimensions. The size of the data set ranges from a minimum of 360,000 for one year to a maximum of 2,520,000 for seven years. In all cases the prices appear to be highly correlated and restricted to a very low dimensional subspace of the original vector space. An external perturbation is added to the system in the form of noise. It is observed that while standard PCA is unable to distinguish the behaviour of the noise-mixed data from that of the original, KPCA clearly identifies the effect of the noise. The exercise is extended in case of daily data of other stock markets and similar results are obtained.

Suggested Citation

  • Mukherjee, I. & Chatterjee, Soumya & Giri, A. & Barat, P., 2017. "Understanding the pattern of the BSE Sensex," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 262-275.
    • Handle: RePEc:eee:phsmap:v:482:y:2017:i:c:p:262-275
    DOI: 10.1016/j.physa.2017.04.026
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    References listed on IDEAS

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    1. Challet, Damien & Marsili, Matteo & Zhang, Yi-Cheng, 2013. "Minority Games: Interacting agents in financial markets," OUP Catalogue, Oxford University Press, number 9780199686698, Decembrie.
    2. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    3. Chakrabarti,Bikas K. & Chakraborti,Anirban & Chakravarty,Satya R. & Chatterjee,Arnab, 2013. "Econophysics of Income and Wealth Distributions," Cambridge Books, Cambridge University Press, number 9781107013445.
    4. Johnson, Neil F. & Jefferies, Paul & Hui, Pak Ming, 2003. "Financial Market Complexity," OUP Catalogue, Oxford University Press, number 9780198526650, Decembrie.
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    Cited by:

    1. Lei Wang & Yan Yan & Xiaoteng Li & Xiaosong Chen, 2018. "General Component Analysis (GCA): A new approach to identify Chinese corporate bond market structures," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-18, July.
    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. Upadhyay, Shashankaditya & Mukherjee, Indranil & Panigrahi, Prasanta K., 2023. "Inner composition alignment networks reveal financial impacts of COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).

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