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Cryptocurrency liquidity during extreme price movements: is there a problem with virtual money?

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  • Viktor Manahov

Abstract

The enormous rise of the cryptocurrencies over the last few years has created one of the largest unregulated markets in the world. In this study, we obtain millisecond data for the five major cryptocurrencies—bitcoin, ethereum, ripple, litecoin and dash—and two cryptocurrency indices—Crypto Index (CRIX) and CCI30 Crypto Currencies Index—to investigate the relationship between cryptocurrency liquidity, herding behaviour and profitability during periods of extreme price movements (EPMs). We demonstrate that cryptocurrency traders (CTs) facilitate EPMs and demand liquidity even during the utmost EPMs. We observe the presence of herding behaviour during up markets across the entire dataset. Our robustness checks indicate that herding behaviour follows a dynamic pattern that varies over time with decreasing magnitude. We also provide novel evidence of CTs’ profitability after transaction costs, and demonstrate their strong profitability-generating record in the future.

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  • Viktor Manahov, 2021. "Cryptocurrency liquidity during extreme price movements: is there a problem with virtual money?," Quantitative Finance, Taylor & Francis Journals, vol. 21(2), pages 341-360, February.
    • Handle: RePEc:taf:quantf:v:21:y:2021:i:2:p:341-360
    DOI: 10.1080/14697688.2020.1788718
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    Cited by:

    1. Chu, Jeffrey & Chan, Stephen & Zhang, Yuanyuan, 2023. "An analysis of the return–volume relationship in decentralised finance (DeFi)," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 236-254.
    2. Youssef El-Khatib & Abdulnasser Hatemi-J, 2023. "On a regime switching illiquid high volatile prediction model for cryptocurrencies," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 51(2), pages 485-498, July.
    3. Emilio Barucci & Giancarlo Giuffra Moncayo & Daniele Marazzina, 2022. "Cryptocurrencies and stablecoins: a high-frequency analysis," Digital Finance, Springer, vol. 4(2), pages 217-239, September.
    4. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    5. Sharif, Arshian & Brahim, Mariem & Dogan, Eyup & Tzeremes, Panayiotis, 2023. "Analysis of the spillover effects between green economy, clean and dirty cryptocurrencies," Energy Economics, Elsevier, vol. 120(C).
    6. Chen, Rongxin & Lepori, Gabriele M. & Tai, Chung-Ching & Sung, Ming-Chien, 2022. "Explaining cryptocurrency returns: A prospect theory perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    7. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    8. Alexey Yu. Mikhaylov & Vikas Khare & Solomon Eghosa Uhunamure & Tsangyao Chang & Diana I. Stepanova, 2023. "Bitcoin Price Short-term Forecast Using Twitter Sentiment Analysis," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 4, pages 123-137, August.

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