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Stability and Hierarchy of Quasi-Stationary States: Financial Markets as an Example

Author

Listed:
  • Yuriy Stepanov
  • Philip Rinn
  • Thomas Guhr
  • Joachim Peinke
  • Rudi Schafer

Abstract

We combine geometric data analysis and stochastic modeling to describe the collective dynamics of complex systems. As an example we apply this approach to financial data and focus on the non-stationarity of the market correlation structure. We identify the dominating variable and extract its explicit stochastic model. This allows us to establish a connection between its time evolution and known historical events on the market. We discuss the dynamics, the stability and the hierarchy of the recently proposed quasi-stationary market states.

Suggested Citation

  • Yuriy Stepanov & Philip Rinn & Thomas Guhr & Joachim Peinke & Rudi Schafer, 2015. "Stability and Hierarchy of Quasi-Stationary States: Financial Markets as an Example," Papers 1503.00556, arXiv.org.
    • Handle: RePEc:arx:papers:1503.00556
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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).
    2. 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.
    3. Martin He{ss}ler & Tobias Wand & Oliver Kamps, 2023. "Efficient Multi-Change Point Analysis to decode Economic Crisis Information from the S&P500 Mean Market Correlation," Papers 2308.00087, arXiv.org.
    4. Gartzke, Sebastian & Wang, Shanshan & Guhr, Thomas & Schreckenberg, Michael, 2022. "Spatial correlation analysis of traffic flow on parallel motorways in Germany," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).

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