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Dynamics of the number of trades of financial securities

Author

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  • Bonanno, Giovanni
  • Lillo, Fabrizio
  • Mantegna, Rosario N

Abstract

We perform a parallel analysis of the spectral density of (i) the logarithm of price and (ii) the daily number of trades of a set of stocks traded in the New York Stock Exchange. The stocks are selected to be representative of a wide range of stock capitalization. The observed spectral densities show a different power-law behavior. We confirm the 1/f2 behavior for the spectral density of the logarithm of stock price, whereas we detect a 1/f-like behavior for the spectral density of the daily number of trades.

Suggested Citation

  • Bonanno, Giovanni & Lillo, Fabrizio & Mantegna, Rosario N, 2000. "Dynamics of the number of trades of financial securities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 280(1), pages 136-141.
    • Handle: RePEc:eee:phsmap:v:280:y:2000:i:1:p:136-141
    DOI: 10.1016/S0378-4371(99)00629-9
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    Cited by:

    1. Plamen Ch Ivanov & Ainslie Yuen & Pandelis Perakakis, 2014. "Impact of Stock Market Structure on Intertrade Time and Price Dynamics," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-14, April.
    2. Staccioli, Jacopo & Napoletano, Mauro, 2021. "An agent-based model of intra-day financial markets dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 331-348.
    3. Aki-Hiro Sato & Takaki Hayashi & Janusz Hołyst, 2012. "Comprehensive analysis of market conditions in the foreign exchange market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 167-179, October.
    4. Ponta, Linda & Trinh, Mailan & Raberto, Marco & Scalas, Enrico & Cincotti, Silvano, 2019. "Modeling non-stationarities in high-frequency financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 173-196.
    5. Eisler, Z. & Kertész, J., 2004. "Multifractal model of asset returns with leverage effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 603-622.
    6. Taisei Kaizoji, 2013. "Modelling of Stock Returns and Trading Volume," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 147-155, July.
    7. Dremin, I.M. & Leonidov, A.V., 2005. "On distribution of number of trades in different time windows in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 388-402.
    8. Pasquale, Maria & Renò, Roberto, 2005. "Statistical properties of trading volume depending on size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 518-528.
    9. Alvarez-Ramirez, Jose & Ibarra-Valdez, Carlos, 2001. "Modeling stock market dynamics based on conservation principles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 301(1), pages 493-511.
    10. Zoltan Eisler & Janos Kertesz, 2004. "Multifractal model of asset returns with leverage effect," Papers cond-mat/0403767, arXiv.org, revised May 2004.
    11. Sanjiv Das & Paul Hanouna, 2010. "Run lengths and liquidity," Annals of Operations Research, Springer, vol. 176(1), pages 127-152, April.

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