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Time-dependent complexity measurement of causality in international equity markets: A spatial approach

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  • Lahmiri, Salim
  • Bekiros, Stelios
  • Avdoulas, Christos

Abstract

A nonlinear temporal complexity approach is proposed in order to properly model the evolution of randomness, self-similarity and information transmission for thirty-four international stock markets, grouped into four major geographical segments: America, Europe, Asia and Oceania. The causality between each type of time-dependent measures is investigated to assess the state system flows across all geographic segments. The empirical results show that self-similarity is vastly transmitted between financial markets. Moreover, significant emissions of entropy and self-similarity are found between America and Europe. Informational flows are observed only between Europe and Asia, and Europe and Oceania. Our findings may have important implications for portfolio management based on the spatial dimension of spillovers of stochasticity, self-similarity and system state informational content for world stock markets. These results would not have emerged by means of standard econometric approaches of causality investigation in financial returns.

Suggested Citation

  • Lahmiri, Salim & Bekiros, Stelios & Avdoulas, Christos, 2018. "Time-dependent complexity measurement of causality in international equity markets: A spatial approach," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 215-219.
    • Handle: RePEc:eee:chsofr:v:116:y:2018:i:c:p:215-219
    DOI: 10.1016/j.chaos.2018.09.030
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    References listed on IDEAS

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    2. Lahmiri, Salim & Bekiros, Stelios, 2020. "Renyi entropy and mutual information measurement of market expectations and investor fear during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Mohammad Arashi & Mohammad Mahdi Rounaghi, 2022. "Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model," Future Business Journal, Springer, vol. 8(1), pages 1-12, December.
    4. Xavier Brouty & Matthieu Garcin, 2022. "A statistical test of market efficiency based on information theory," Papers 2208.11976, arXiv.org.
    5. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Papers 2305.13123, arXiv.org.
    6. Zhang, Bo & Wang, Guochao & Wang, Yiduan & Zhang, Wei & Wang, Jun, 2019. "Multiscale statistical behaviors for Ising financial dynamics with continuum percolation jump," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1012-1025.
    7. Shao, Wei & Wang, Jian, 2020. "Does the “ice-breaking” of South and North Korea affect the South Korean financial market?," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    8. Xavier Brouty & Matthieu Garcin, 2022. "A statistical test of market efficiency based on information theory," Working Papers hal-03760478, HAL.

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