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Dynamics of the market states in the space of correlation matrices with applications to financial markets

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  • Hirdesh K. Pharasi
  • Suchetana Sadhukhan
  • Parisa Majari
  • Anirban Chakraborti
  • Thomas H. Seligman

Abstract

The concept of states of financial markets based on correlations has gained increasing attention during the last 10 years. We propose to retrace some important steps up to 2018, and then give a more detailed view of recent developments that attempt to make the use of this more practical. Finally, we try to give a glimpse to the future proposing the analysis of trajectories in correlation matrix space directly or in terms of symbolic dynamics as well as attempts to analyze the clusters that make up the states in a random matrix context.

Suggested Citation

  • Hirdesh K. Pharasi & Suchetana Sadhukhan & Parisa Majari & Anirban Chakraborti & Thomas H. Seligman, 2021. "Dynamics of the market states in the space of correlation matrices with applications to financial markets," Papers 2107.05663, arXiv.org.
    • Handle: RePEc:arx:papers:2107.05663
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    References listed on IDEAS

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    3. Philip Rinn & Yuriy Stepanov & Joachim Peinke & Thomas Guhr & Rudi Schafer, 2015. "Dynamics of quasi-stationary systems: Finance as an example," Papers 1502.07522, arXiv.org.
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    6. Thomas Guhr & Andreas Schell, 2020. "Exact Multivariate Amplitude Distributions for Non-Stationary Gaussian or Algebraic Fluctuations of Covariances or Correlations," Papers 2011.07570, arXiv.org.
    7. Hirdesh K. Pharasi & Kiran Sharma & Rakesh Chatterjee & Anirban Chakraborti & Francois Leyvraz & Thomas H. Seligman, 2018. "Identifying long-term precursors of financial market crashes using correlation patterns," Papers 1809.00885, arXiv.org, revised Sep 2018.
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    Cited by:

    1. Heckens, Anton J. & Guhr, Thomas, 2022. "New collectivity measures for financial covariances and correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).

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