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The impact of trading volume on the stock market credibility: Bohmian quantum potential approach

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  • Nasiri, S.
  • Bektas, E.
  • Jafari, G.R.

Abstract

Price return is an interesting factor for many investors; however, it is expected that the price return to be affected by the trading volume of any given market as a complex system. The Bohmian quantum mechanics is used due to the time correlation of return and volume of the stock markets under consideration. Recent studies have shown that the quantum potential given by the Bohmian quantum mechanics confines price return variations into a definite interval. In this study, we extend the quantum potential concept to investigate the behavior of trading volume and its possible influences on the price return. The obtained results show that the quantum potential behaves in the same manner for trading volume as the price return, and confines the variations of the volume into a specific domain. Furthermore, a joint quantum potential as a function of return and volume is derived by the probability distribution function (PDF) constructed by the real data of a given market. It serves as a suitable instrument to investigate the relationship between these variables and to check the credibility of the market at higher volumes. The resultant PDF and the corresponding joint quantum potential illustrate that the variations of price return at higher volumes decrease as the trading volume increases, making the market more credible which is more pronounced in developed markets.

Suggested Citation

  • Nasiri, S. & Bektas, E. & Jafari, G.R., 2018. "The impact of trading volume on the stock market credibility: Bohmian quantum potential approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1104-1112.
    • Handle: RePEc:eee:phsmap:v:512:y:2018:i:c:p:1104-1112
    DOI: 10.1016/j.physa.2018.08.026
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    References listed on IDEAS

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    2. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    3. Ardalankia, Jamshid & Osoolian, Mohammad & Haven, Emmanuel & Jafari, G. Reza, 2020. "Scaling features of price–volume cross correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    4. Haoran Zheng & Jing Bai, 2024. "Quantum Leap: A Price Leap Mechanism in Financial Markets," Mathematics, MDPI, vol. 12(2), pages 1-27, January.
    5. Reza Hosseini & Samin Tajik & Zahra Koohi Lai & Tayeb Jamali & Emmanuel Haven & G. Reza Jafari, 2022. "Quantum Bohmian Inspired Potential to Model Non-Gaussian Events and the Application in Financial Markets," Papers 2204.11203, arXiv.org.
    6. Jamshid Ardalankia & Mohammad Osoolian & Emmanuel Haven & G. Reza Jafari, 2019. "Scaling Features of Price-Volume Cross-Correlation," Papers 1903.01744, arXiv.org, revised Aug 2020.
    7. Zhao, Jun, 2019. "Nonstationary response of a nonlinear economic cycle model under random disturbance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 409-421.

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