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Related Experiment Videos

Quantifying and interpreting collective behavior in financial markets.

P Gopikrishnan1, B Rosenow, V Plerou

  • 1Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|October 3, 2001
PubMed
Summary

We found that stock price fluctuations reveal distinct, stable business sectors. These sectors exhibit power-law correlations, similar to strongly interacting systems in physics.

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Area of Science:

  • Quantitative Finance
  • Statistical Physics
  • Computational Economics

Background:

  • Firms with similar business activities exhibit correlated stock price movements.
  • Understanding these correlations is crucial for market analysis and risk management.

Purpose of the Study:

  • To identify and analyze distinct subsets of stocks based on their price fluctuation correlations.
  • To investigate the temporal stability and correlation characteristics of these identified subsets.

Main Methods:

  • Construction of cross-correlation matrices (C) from stock price fluctuations over different time scales and periods.
  • Analysis of the eigenvectors of C to partition stocks into distinct subsets.
  • Examination of time correlation functions within these subsets.

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Main Results:

  • Eigenvector analysis successfully partitioned stocks into subsets mirroring business sectors.
  • These identified sectors demonstrated remarkable stability over extended time periods.
  • Price fluctuations within these subsets exhibited power-law decaying time correlations.

Conclusions:

  • Stock market structure can be effectively revealed through correlation analysis of price fluctuations.
  • The identified business sectors possess inherent dynamics characterized by power-law correlations.
  • Findings suggest analogies between financial markets and strongly interacting physical systems.