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Extrapolative Bubbles and Trading Volume

Author

Listed:
  • Jingchi Liao
  • Cameron Peng
  • Ning Zhu

Abstract

We propose an extrapolative model of bubbles to explain the sharp rise in prices and volume observed in historical financial bubbles. The model generates a novel mechanism for volume: because of the interaction between extrapolative beliefs and disposition effects, investors are quick to not only buy assets with positive past returns but also sell them if good returns continue. Using account-level transaction data on the 2014–2015 Chinese stock market bubble, we test and confirm the model’s predictions about trading volume. We quantify the magnitude of the proposed mechanism and show that it can increase trading volume by another 30.

Suggested Citation

  • Jingchi Liao & Cameron Peng & Ning Zhu, 2022. "Extrapolative Bubbles and Trading Volume," The Review of Financial Studies, Society for Financial Studies, vol. 35(4), pages 1682-1722.
    • Handle: RePEc:oup:rfinst:v:35:y:2022:i:4:p:1682-1722.
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    File URL: http://hdl.handle.net/10.1093/rfs/hhab070
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    Citations

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    Cited by:

    1. Cong Chen & Changsheng Hu & Hongxing Yao, 2022. "Noise Trader Risk and Wealth Effect: A Theoretical Framework," Mathematics, MDPI, vol. 10(20), pages 1-18, October.
    2. Xingguo Luo & Doojin Ryu & Libin Tao & Chuxin Ye, 2024. "Price monotonicity violations during stock market crashes: Evidence from the SSE 50 ETF options market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(3), pages 533-554, March.
    3. Huihui WU & Chunpeng YANG, 2022. "Investor Sentiment, Extrapolation and Asset Pricing," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 182-205, December.
    4. Liu, Xin & Qiu, Zhigang & Shen, Luyao & Zheng, Weinan, 2023. "Coreversal: The booms and busts of arbitrage activities in China," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 51-65.
    5. Qi Xu & Yang Ye, 2023. "Commodity network and predictable returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(10), pages 1423-1449, October.
    6. Cong Chen & Changsheng Hu & Liang Wu, 2023. "Feedback Trading, Investor Sentiment and the Volatility Puzzle: An Infinite Theoretical Framework," Mathematics, MDPI, vol. 11(14), pages 1-15, July.
    7. Ricardo Barahona & Stefano Cassella & Kristy A. E. Jansen, 2023. "Do Teams Alleviate or Exacerbate the Extrapolation Bias in the Stock Market?," Working Papers 2335, Banco de España.
    8. Kanis Saengchote, 2022. "Cryptocurrency bubbles, the wealth effect, and non-fungible token prices: Evidence from metaverse LAND," Papers 2209.04385, arXiv.org.

    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • G50 - Financial Economics - - Household Finance - - - General

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