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Matrix H-theory approach to stock market fluctuations

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  • Luan M. T. de Moraes
  • Ant^onio M. S. Macedo
  • Raydonal Ospina
  • Giovani L. Vasconcelos

Abstract

We introduce matrix H theory, a framework for analyzing collective behavior arising from multivariate stochastic processes with hierarchical structure. The theory models the joint distribution of the multiple variables (the measured signal) as a compound of a large-scale multivariate distribution with the distribution of a slowly fluctuating background. The background is characterized by a hierarchical stochastic evolution of internal degrees of freedom, representing the correlations between stocks at different time scales. As in its univariate version, the matrix H-theory formalism also has two universality classes: Wishart and inverse Wishart, enabling a concise description of both the background and the signal probability distributions in terms of Meijer G-functions with matrix argument. Empirical analysis of daily returns of stocks within the S&P500 demonstrates the effectiveness of matrix H theory in describing fluctuations in stock markets. These findings contribute to a deeper understanding of multivariate hierarchical processes and offer potential for developing more informed portfolio strategies in financial markets.

Suggested Citation

  • Luan M. T. de Moraes & Ant^onio M. S. Macedo & Raydonal Ospina & Giovani L. Vasconcelos, 2025. "Matrix H-theory approach to stock market fluctuations," Papers 2503.08697, arXiv.org.
    • Handle: RePEc:arx:papers:2503.08697
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