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Synchronization Model for Stock Market Asymmetry

Author

Listed:
  • Raul Donangelo
  • Mogens H. Jensen
  • Ingve Simonsen
  • Kim Sneppen

Abstract

The waiting time needed for a stock market index to undergo a given percentage change in its value is found to have an up-down asymmetry, which, surprisingly, is not observed for the individual stocks composing that index. To explain this, we introduce a market model consisting of randomly fluctuating stocks that occasionally synchronize their short term draw-downs. These synchronous events are parameterized by a ``fear factor'', that reflects the occurrence of dramatic external events which affect the financial market.

Suggested Citation

  • Raul Donangelo & Mogens H. Jensen & Ingve Simonsen & Kim Sneppen, 2006. "Synchronization Model for Stock Market Asymmetry," Papers physics/0604137, arXiv.org, revised Aug 2006.
    • Handle: RePEc:arx:papers:physics/0604137
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    Citations

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    Cited by:

    1. Stefan Bornholdt, 2021. "A q-spin Potts model of markets: Gain-loss asymmetry in stock indices as an emergent phenomenon," Papers 2112.06290, arXiv.org.
    2. Johannes Vitalis Siven & Jeffrey Todd Lins, 2009. "Temporal structure and gain/loss asymmetry for real and artificial stock indices," Papers 0907.0554, arXiv.org.
    3. Katahira, Kei & Chen, Yu & Akiyama, Eizo, 2021. "Self-organized Speculation Game for the spontaneous emergence of financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    4. Andrea Di Iura & Giulia Terenzi, 2022. "A Bayesian analysis of gain-loss asymmetry," SN Business & Economics, Springer, vol. 2(5), pages 1-23, May.
    5. Kei Katahira & Yu Chen & Gaku Hashimoto & Hiroshi Okuda, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Papers 1902.02040, arXiv.org.
    6. Katahira, Kei & Chen, Yu & Hashimoto, Gaku & Okuda, Hiroshi, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 503-518.
    7. Andrea Giuseppe Di Iura & Giulia Terenzi, 2021. "A Bayesian analysis of gain-loss asymmetry," Papers 2104.06044, arXiv.org.
    8. Bornholdt, Stefan, 2022. "A q-spin Potts model of markets: Gain–loss asymmetry in stock indices as an emergent phenomenon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    9. Johannes Vitalis Siven & Jeffrey Todd Lins & Jonas Lundbek Hansen, 2008. "A multiscale view on inverse statistics and gain/loss asymmetry in financial time series," Papers 0811.3122, arXiv.org.
    10. Luis Goncalves de Faria, 2022. "An Agent-Based Model With Realistic Financial Time Series: A Method for Agent-Based Models Validation," Papers 2206.09772, arXiv.org.
    11. I. Simonsen & P. T.H. Ahlgren & M. H. Jensen & R. Donangelo & K. Sneppen, 2007. "Fear and its implications for stock markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(2), pages 153-158, May.
    12. Lisa Borland & Yoan Hassid, 2010. "Market panic on different time-scales," Papers 1010.4917, arXiv.org.

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