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Information-driven trade and price–volume relationship in artificial stock markets

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  • Liu, Xinghua
  • Liu, Xin
  • Liang, Xiaobei

Abstract

The positive relation between stock price changes and trading volume (price–volume relationship) as a stylized fact has attracted significant interest among finance researchers and investment practitioners. However, until now, consensus has not been reached regarding the causes of the relationship based on real market data because extracting valuable variables (such as information-driven trade volume) from real data is difficult. This lack of general consensus motivates us to develop a simple agent-based computational artificial stock market where extracting the necessary variables is easy. Based on this model and its artificial data, our tests have found that the aggressive trading style of informed agents can produce a price–volume relationship. Therefore, the information spreading process is not a necessary condition for producing price–volume relationship.

Suggested Citation

  • Liu, Xinghua & Liu, Xin & Liang, Xiaobei, 2015. "Information-driven trade and price–volume relationship in artificial stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 73-80.
    • Handle: RePEc:eee:phsmap:v:430:y:2015:i:c:p:73-80
    DOI: 10.1016/j.physa.2015.01.069
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    References listed on IDEAS

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    5. Xu, Chao & Zhao, Xiaojun & Wang, Yanwen, 2022. "Causal decomposition on multiple time scales: Evidence from stock price-volume time series," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).

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