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Emergence of universal scaling in financial markets from mean-field dynamics

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  • S. V. Vikram
  • Sitabhra Sinha

Abstract

Collective phenomena with universal properties have been observed in many complex systems with a large number of components. Here we present a microscopic model of the emergence of scaling behavior in such systems, where the interaction dynamics between individual components is mediated by a global variable making the mean-field description exact. Using the example of financial markets, we show that asset price can be such a global variable with the critical role of coordinating the actions of agents who are otherwise independent. The resulting model accurately reproduces empirical properties such as the universal scaling of the price fluctuation and volume distributions, long-range correlations in volatility and multiscaling.

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  • S. V. Vikram & Sitabhra Sinha, 2010. "Emergence of universal scaling in financial markets from mean-field dynamics," Papers 1006.0628, arXiv.org.
    • Handle: RePEc:arx:papers:1006.0628
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    Cited by:

    1. Takero Ibuki & Jun-ichi Inoue, 2011. "Response of double-auction markets to instantaneous Selling–Buying signals with stochastic Bid–Ask spread," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(2), pages 93-120, November.
    2. Tingqiang Chen & Binqing Xiao & Haifei Liu, 2018. "Credit Risk Contagion in an Evolving Network Model Integrating Spillover Effects and Behavioral Interventions," Complexity, Hindawi, vol. 2018, pages 1-16, March.
    3. Chakraborty, Abhijit & Easwaran, Soumya & Sinha, Sitabhra, 2018. "Deviations from universality in the fluctuation behavior of a heterogeneous complex system reveal intrinsic properties of components: The case of the international currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 599-610.
    4. Yuichi Ikeda, 2020. "An Interacting Agent Model of Economic Crisis," Papers 2001.11843, arXiv.org.
    5. Sitabhra Sinha & Uday Kovur, 2013. "Uncovering the network structure of the world currency market: Cross-correlations in the fluctuations of daily exchange rates," Papers 1305.0239, arXiv.org.
    6. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    7. Xiao-Qian Sun & Hua-Wei Shen & Xue-Qi Cheng & Zhao-Yang Wang, 2012. "Degree-Strength Correlation Reveals Anomalous Trading Behavior," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-9, October.
    8. Anindya S. Chakrabarti & Arnab Chatterjee & Tushar Nandi & Asim Ghosh & Anirban Chakraborti, 2018. "Quantifying invariant features of within-group inequality in consumption across groups," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 469-490, October.
    9. Takero Ibuki & Jun-ichi Inoue, 2010. "Response of double-auction markets to instantaneous Selling-Buying signals with stochastic Bid-Ask spread," Papers 1011.0748, arXiv.org, revised Mar 2011.
    10. IKEDA Yuichi & YOSHIKAWA Hiroshi, 2018. "Macroprudential Modeling Based on Spin Dynamics in a Supply Chain Network," Discussion papers 18045, Research Institute of Economy, Trade and Industry (RIETI).

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