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The Impact of Market Mood on a Dynamic Model of Insider Trading

Author

Listed:
  • Ruohan Wang

    (College of Mathematics and Statistics, Yili Normal University, Yining 835000, China)

  • Jing Wang

    (College of Mathematics and Statistics, Yili Normal University, Yining 835000, China
    Institute of Applied Mathematics, Yili Normal University, Yining 835000, China)

  • Zhi Yang

    (College of Mathematics and Statistics, Yili Normal University, Yining 835000, China
    Institute of Applied Mathematics, Yili Normal University, Yining 835000, China)

Abstract

According to the research, the proportions of various types of investors may or may not change in response to different trading strategies or complex trading environments. This paper investigates a single-period trading model for multiple risk-averse and risk-neutral insider traders. The distinction is that we consider the impact of the number of risk-averse traders and different types of insider traders on market liquidity. The model contains four types of trading entities: risk-neutral and risk-adverse insider traders, risk-neutral market makers, and noise traders. Firstly, we prove the existence and uniqueness of the model’s linear Nash equilibrium; secondly, we compare the model with multiple risk-neutral and risk-adverse insider traders in the market to the model with only risk-neutral insider traders and risk-adverse insider traders. It is shown that the market liquidity parameter λ decreases with the increase in the number of risk-averse persons N 2 in a particular range and increases with the increase in the number of risk-averse persons N 2 in another range. Markets with risk-neutral and risk-averse insider traders have consistently lower liquidity than markets with only risk-neutral insider traders. Comparing this to markets with only risk-adverse insider traders reveals that the number of risk-adverse traders heavily influences market liquidity.

Suggested Citation

  • Ruohan Wang & Jing Wang & Zhi Yang, 2025. "The Impact of Market Mood on a Dynamic Model of Insider Trading," Games, MDPI, vol. 16(4), pages 1-16, June.
    • Handle: RePEc:gam:jgames:v:16:y:2025:i:4:p:32-:d:1683770
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    References listed on IDEAS

    as
    1. Holden, Craig W & Subrahmanyam, Avanidhar, 1992. "Long-Lived Private Information and Imperfect Competition," Journal of Finance, American Finance Association, vol. 47(1), pages 247-270, March.
    2. Daher, Wassim & Saleeby, Elias G., 2023. "Existence of Linear Equilibria in The Kyle Model with Partial Correlation and Two Risk Neutral Traders," MPRA Paper 117813, University Library of Munich, Germany.
    3. Dieci, Roberto & Foroni, Ilaria & Gardini, Laura & He, Xue-Zhong, 2006. "Market mood, adaptive beliefs and asset price dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 29(3), pages 520-534.
    4. Kerry Back & C. Henry Cao & Gregory A. Willard, 2000. "Imperfect Competition among Informed Traders," Journal of Finance, American Finance Association, vol. 55(5), pages 2117-2155, October.
    5. Carré, Sylvain & Collin-Dufresne, Pierre & Gabriel, Franck, 2022. "Insider trading with penalties," Journal of Economic Theory, Elsevier, vol. 203(C).
    6. Naeimah Alkharafi & Mariam Alsabah, 2025. "Globalization: An Overview of Its Main Characteristics and Types, and an Exploration of Its Impacts on Individuals, Firms, and Nations," Economies, MDPI, vol. 13(4), pages 1-33, March.
    7. Jiang, Ying & Liu, Hong, 2022. "Insider trading, overconfidence, and private information flow," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    8. Baruch, Shmuel, 2002. "Insider trading and risk aversion," Journal of Financial Markets, Elsevier, vol. 5(4), pages 451-464, October.
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