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FoMO in the Bitcoin market: Revisiting and factors

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  • Wang, Jying-Nan
  • Liu, Hung-Chun
  • Lee, Yen-Hsien
  • Hsu, Yuan-Teng

Abstract

We revisit the “fear of missing out” (FoMO) effect of Bitcoin by observing asymmetric volatility dynamics and further investigate its driving factors. Using a longer sample period covering the COVID-19 pandemic, our results show evidence of positive asymmetric volatility behavior in the Bitcoin market, confirming the presence of the FoMO effect. This effect also exists in some other major cryptocurrencies. Further analysis indicates that the happiness index, the ratio of short-term to long-term Bitcoin trading volume, and the geopolitical risk index contribute positively to the FoMO, while the volatility index and the Twitter-based uncertainty index exert an opposite effect.

Suggested Citation

  • Wang, Jying-Nan & Liu, Hung-Chun & Lee, Yen-Hsien & Hsu, Yuan-Teng, 2023. "FoMO in the Bitcoin market: Revisiting and factors," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 244-253.
    • Handle: RePEc:eee:quaeco:v:89:y:2023:i:c:p:244-253
    DOI: 10.1016/j.qref.2023.04.007
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    Cited by:

    1. Alessio Brini & Jimmie Lenz, 2024. "A comparison of cryptocurrency volatility-benchmarking new and mature asset classes," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-38, December.
    2. Lin, Xudong & Meng, Yiqun & Zhu, Hao, 2023. "How connected is the crypto market risk to investor sentiment?," Finance Research Letters, Elsevier, vol. 56(C).
    3. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.

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    More about this item

    Keywords

    Bitcoin; FoMO; Cryptocurrency; GJR-GARCH; Rolling estimation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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