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Analysing the behavioural finance impact of 'fake news' phenomena on financial markets: a representative agent model and empirical validation

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  • Bryan Fong

    (University of Cambridge)

Abstract

This paper proposes an original behavioural finance representative agent model, to explain how fake news’ empirical price impacts can persist in finance despite contradicting the efficient-market hypothesis. The model reconciles empirically-observed price overreactions to fake news with empirically-observed price underreactions to real news, and predicts a novel secondary impact of fake news: that fake news in a security amplifies underreactions to subsequent real news for the security. Evaluating the model against a large-sample event study of the 2019 Chinese ADR Delisting Threat fake news and debunking event, this paper finds strong qualitative validation for its model’s dynamics and predictions.

Suggested Citation

  • Bryan Fong, 2021. "Analysing the behavioural finance impact of 'fake news' phenomena on financial markets: a representative agent model and empirical validation," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.
    • Handle: RePEc:spr:fininn:v:7:y:2021:i:1:d:10.1186_s40854-021-00271-z
    DOI: 10.1186/s40854-021-00271-z
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    References listed on IDEAS

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    Cited by:

    1. Arcuri, Maria Cristina & Gandolfi, Gino & Russo, Ivan, 2023. "Does fake news impact stock returns? Evidence from US and EU stock markets," Journal of Economics and Business, Elsevier, vol. 125.
    2. Jonathan Paul Marshall, 2022. "A Social Exploration of the West Australian Gorgon Gas, Carbon Capture and Storage Project," Clean Technol., MDPI, vol. 4(1), pages 1-24, February.
    3. Qingchong Chen & Xiong Xiong & Ya Gao, 2021. "Is information really efficient for the market? Evidence of confirmatory bias in China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(5), pages 5965-5997, December.
    4. Li-Chen Cheng & Wei-Ting Lu & Benjamin Yeo, 2023. "Predicting abnormal trading behavior from internet rumor propagation: a machine learning approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.

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