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Cryptocurrency Market: Overreaction to News and Herd Instincts
[Рынок Криптовалют: Сверхреакция На Новости И Стадные Инстинкты]

Author

Listed:
  • Malkina, Marina (Малкина, Марина)

    (Lobachevsky State University of Nizhni Novgorod)

  • Ovchinnikov, Vyacheslav (Овчинников, Вячеслав)

    (Financial Research Institute of the Ministry of Finance of the Russian Federation; Lobachevsky State University of Nizhni Novgorod)

Abstract

We studied the specific properties of the cryptocurrency market. Guided by the concept of implied volatility, we investigated the asymmetric reaction of the market to news. Based on the concept of realized volatility, we verified the hypothesis of herding behavior in the market. To test the properties of the market, we used a combination of methods, starting from the analysis of statistics of search queries, interpreted as proxies of information demand from professional market participants and the “wide crowd”, and ending with advanced Markov-Switching GARCH models and heterogeneous autoregressive models of realized volatility (HAR-RV-J-models). As a result, we found various types of asymmetric reactions of the cryptocurrency market to news related to both the general direction of its dynamics (growth or decrease) and the amplitude of return fluctuations (high or low volatility). During the upward price rally and overheating of the market, investors deliberately avoided the bad news; thereby the asymmetry in the cryptocurrency market was inverse (to the adopted leverage effect). On the contrary, during the downward price rally, market participants exhibited an overreaction to bad news. In addition, the asymmetric reaction to the news observed during the period of low market volatility actually disappeared when the amplitude of cryptocurrency return volatility increased. The behavior of short-term investors was also varied in the study period. While during the growth of the market, small speculators were more likely to follow their own trading strategies, during the hype they borrowed the trading practices of the largest players. We also revealed the effect of training among small investors: over time, they became less prone to provocations from large players, which did not allow the 2019 rally to surpass its counterpart in 2017 in terms of both return oscillations and duration.

Suggested Citation

  • Malkina, Marina (Малкина, Марина) & Ovchinnikov, Vyacheslav (Овчинников, Вячеслав), 2020. "Cryptocurrency Market: Overreaction to News and Herd Instincts [Рынок Криптовалют: Сверхреакция На Новости И Стадные Инстинкты]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 3, pages 74-105, June.
    • Handle: RePEc:rnp:ecopol:ep2017
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    References listed on IDEAS

    as
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    2. Corbet, Shaen & Lucey, Brian & Yarovaya, Larisa, 2018. "Datestamping the Bitcoin and Ethereum bubbles," Finance Research Letters, Elsevier, vol. 26(C), pages 81-88.
    3. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Yoon, Seong-Min, 2018. "Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets," Finance Research Letters, Elsevier, vol. 27(C), pages 228-234.
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    More about this item

    Keywords

    cryptocurrencies; market (in)efficiency; overreaction to news; asymmetry effect; herding behavior; learning effect.;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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