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Understanding the cubic and half-cubic laws of financial fluctuations

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  • Gabaix, Xavier
  • Gopikrishnan, Parameswaran
  • Plerou, Vasiliki
  • Stanley, H.Eugene

Abstract

Recent empirical research has uncovered regularities in financial fluctuations. Those are: (i) the cubic law of returns: returns follow a power law distribution with exponent 3; (ii) the half cubic law of volumes: volumes follow a power law distribution with exponent 32; (iii) Approximate cubic law of number of trades: the number of trades in a given time intervals follows a power law distribution with exponent around 3. We discuss a new theory that explains them, as well as some related facts.

Suggested Citation

  • Gabaix, Xavier & Gopikrishnan, Parameswaran & Plerou, Vasiliki & Stanley, H.Eugene, 2003. "Understanding the cubic and half-cubic laws of financial fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 1-5.
    • Handle: RePEc:eee:phsmap:v:324:y:2003:i:1:p:1-5
    DOI: 10.1016/S0378-4371(03)00174-2
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    References listed on IDEAS

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    1. V. Plerou & P. Gopikrishnan & L. A. N. Amaral & M. Meyer & H. E. Stanley, 1999. "Scaling of the distribution of price fluctuations of individual companies," Papers cond-mat/9907161, arXiv.org.
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    Cited by:

    1. Wei-Xing Zhou, 2012. "Universal price impact functions of individual trades in an order-driven market," Quantitative Finance, Taylor & Francis Journals, vol. 12(8), pages 1253-1263, June.
    2. Carlos León, 2014. "Scale-free tails in Colombian financial indexes: A primer," Borradores de Economia 812, Banco de la Republica de Colombia.
    3. Zhao, Xiaojun & Zhang, Pengyuan, 2020. "Multiscale horizontal visibility entropy: Measuring the temporal complexity of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    4. Gu, Gao-Feng & Zhou, Wei-Xing, 2007. "Statistical properties of daily ensemble variables in the Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(2), pages 497-506.
    5. Eisenberg, Larry, 2011. "Destabilizing properties of a VaR or probability-of-ruin constraint when variances may be infinite," Journal of Financial Stability, Elsevier, vol. 7(1), pages 10-18, January.
    6. Vladik Kreinovich & Monchaya Chiangpradit & Wararit Panichkitkosolkul, 2012. "Efficient algorithms for heavy-tail analysis under interval uncertainty," Annals of Operations Research, Springer, vol. 195(1), pages 73-96, May.
    7. Huang, Jingjing & Shang, Pengjian & Zhao, Xiaojun, 2012. "Multifractal diffusion entropy analysis on stock volatility in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5739-5745.
    8. Gu, Gao-Feng & Xiong, Xiong & Zhang, Yong-Jie & Chen, Wei & Zhang, Wei & Zhou, Wei-Xing, 2016. "Stylized facts of price gaps in limit order books," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 48-58.
    9. Gao-Feng Gu & Xiong Xiong & Yong-Jie Zhang & Wei Chen & Wei Zhang & Wei-Xing Zhou, 2014. "Stylized facts of price gaps in limit order books: Evidence from Chinese stocks," Papers 1405.1247, arXiv.org.
    10. Andrzej Krawiecki, 2009. "Microscopic spin model for the stock market with attractor bubbling on scale-free networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 4(2), pages 213-220, November.

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