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Asymmetric News Effects on Cryptocurrency Liquidity: an Event Study Perspective

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  • Yue, Wei
  • Zhang, Sijia
  • Zhang, Qiang

Abstract

We analyze the effects of positive and negative news on the liquidity of 100 largest cryptocurrencies in an event study context. We find that the liquidity of cryptocurrencies increases (decreases) after positive(negative) news announcement. The effects of positive news persist longer than that of negative news. We also reveal evidence that there is information leakage ahead of the news announcements, and the positive (negative) news produce an increase (decrease) in the cryptocurrency returns.

Suggested Citation

  • Yue, Wei & Zhang, Sijia & Zhang, Qiang, 2021. "Asymmetric News Effects on Cryptocurrency Liquidity: an Event Study Perspective," Finance Research Letters, Elsevier, vol. 41(C).
  • Handle: RePEc:eee:finlet:v:41:y:2021:i:c:s1544612320316135
    DOI: 10.1016/j.frl.2020.101799
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    References listed on IDEAS

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    1. Sijia Zhang & Andros Gregoriou, 2020. "The price and liquidity impact of China forbidding initial coin offerings on the cryptocurrency market," Applied Economics Letters, Taylor & Francis Journals, vol. 27(20), pages 1695-1698, November.
    2. Caporale, Guglielmo Maria & Plastun, Alex, 2019. "The day of the week effect in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 31(C).
    3. Sensoy, Ahmet, 2019. "The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies," Finance Research Letters, Elsevier, vol. 28(C), pages 68-73.
    4. Jiang, Yonghong & Nie, He & Ruan, Weihua, 2018. "Time-varying long-term memory in Bitcoin market," Finance Research Letters, Elsevier, vol. 25(C), pages 280-284.
    5. Brauneis, Alexander & Mestel, Roland, 2018. "Price discovery of cryptocurrencies: Bitcoin and beyond," Economics Letters, Elsevier, vol. 165(C), pages 58-61.
    6. Coën, Alain & de La Bruslerie, Hubert, 2019. "The informational dimensions of the Amihud (2002) illiquidity measure: Evidence from the M&A market," Finance Research Letters, Elsevier, vol. 29(C), pages 23-29.
    7. Geuder, Julian & Kinateder, Harald & Wagner, Niklas F., 2019. "Cryptocurrencies as financial bubbles: The case of Bitcoin," Finance Research Letters, Elsevier, vol. 31(C).
    8. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    9. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    10. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    11. Florackis, Chris & Gregoriou, Andros & Kostakis, Alexandros, 2011. "Trading frequency and asset pricing on the London Stock Exchange: Evidence from a new price impact ratio," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3335-3350.
    12. Dwyer, Gerald P., 2015. "The economics of Bitcoin and similar private digital currencies," Journal of Financial Stability, Elsevier, vol. 17(C), pages 81-91.
    13. C. Baek & M. Elbeck, 2015. "Bitcoins as an investment or speculative vehicle? A first look," Applied Economics Letters, Taylor & Francis Journals, vol. 22(1), pages 30-34, January.
    14. Riordan, Ryan & Storkenmaier, Andreas & Wagener, Martin & Sarah Zhang, S., 2013. "Public information arrival: Price discovery and liquidity in electronic limit order markets," Journal of Banking & Finance, Elsevier, vol. 37(4), pages 1148-1159.
    15. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
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    Cited by:

    1. Ante, Lennart, 2023. "How Elon Musk's Twitter activity moves cryptocurrency markets," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    2. Naeem, Muhammad Abubakr & Lucey, Brian M. & Karim, Sitara & Ghafoor, Abdul, 2022. "Do financial volatilities mitigate the risk of cryptocurrency indexes?," Finance Research Letters, Elsevier, vol. 50(C).
    3. Smales, L.A., 2022. "Investor attention in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 79(C).
    4. Arpaci, Ibrahim, 2023. "Predictors of financial sustainability for cryptocurrencies: An empirical study using a hybrid SEM-ANN approach," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    5. Prusak Błażej & Potrykus Marcin, 2022. "Stock price reaction to an arrangement approval in restructuring proceedings – the case of Poland," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 58(3), pages 279-298, September.
    6. Scharnowski, Stefan, 2022. "Central bank speeches and digital currency competition," Finance Research Letters, Elsevier, vol. 49(C).
    7. Kumar Kulbhaskar, Anamika & Subramaniam, Sowmya, 2023. "Breaking news headlines: Impact on trading activity in the cryptocurrency market," Economic Modelling, Elsevier, vol. 126(C).

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    More about this item

    Keywords

    Cryptocurrency; liquidity; bid-ask spread; Amihud ratio; event study;
    All these keywords.

    JEL classification:

    • 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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