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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.

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  • 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

    as
    1. Haven, Emmanuel, 2004. "An `ℏ-Brownian motion' and the existence of stochastic option prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 152-155.
    2. Simon Gervais & Ron Kaniel & Dan H. Mingelgrin, 2001. "The High‐Volume Return Premium," Journal of Finance, American Finance Association, vol. 56(3), pages 877-919, June.
    3. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    4. Conrad, Jennifer S & Hameed, Allaudeen & Niden, Cathy, 1994. "Volume and Autocovariances in Short-Horizon Individual Security Returns," Journal of Finance, American Finance Association, vol. 49(4), pages 1305-1329, September.
    5. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: II. Agent-based models," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1013-1041.
    6. Lo, Andrew W & Wang, Jiang, 2000. "Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory," The Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 257-300.
    7. M. F. M. Osborne, 1959. "Brownian Motion in the Stock Market," Operations Research, INFORMS, vol. 7(2), pages 145-173, April.
    8. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2002. "Dynamic Volume-Return Relation of Individual Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1005-1047.
    9. Baaquie, Belal E. & Du, Xin & Bhanap, Jitendra, 2014. "Option pricing: Stock price, stock velocity and the acceleration Lagrangian," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 564-581.
    10. Hsin-Yi Lin, 2013. "Dynamic Stock Return–Volume Relation: Evidence From Emerging Asian Markets," Bulletin of Economic Research, Wiley Blackwell, vol. 65(2), pages 178-193, April.
    11. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    12. Sina Nasiri & Eralp Bektas & Gholamreza Jafari, 2018. "Risk Information of Stock Market Using Quantum Potential Constraints," Springer Proceedings in Business and Economics, in: Nesrin Ozatac & Korhan K. Gökmenoglu (ed.), Emerging Trends in Banking and Finance, pages 132-138, Springer.
    13. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    14. Saatcioglu, Kemal & Starks, Laura T., 1998. "The stock price-volume relationship in emerging stock markets: the case of Latin America," International Journal of Forecasting, Elsevier, vol. 14(2), pages 215-225, June.
    15. Baaquie, Belal E., 2013. "Statistical microeconomics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4400-4416.
    16. Todorova, Neda & Souček, Michael, 2014. "The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range," Economic Modelling, Elsevier, vol. 36(C), pages 332-340.
    17. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-168, February.
    18. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frédéric Abergel, 2011. "Econophysics review: II. Agent-based models," Post-Print hal-00621059, HAL.
    19. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    20. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    21. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    22. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
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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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