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Liquidity and market efficiency in cryptocurrencies

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  • Wei, Wang Chun

Abstract

We examine the liquidity of 456 different cryptocurrencies, and show that return predictability diminishes in cryptocurrencies with high market liquidity. We show that whilst Bitcoin returns are showing signs of efficiency, numerous cryptocurrencies still exhibit signs of autocorrelation and non-independence. Our findings also show a strong relationship between the Hurst exponent and liquidity on a cross-sectional basis. Therefore, we conclude that liquidity plays a significant role in market efficiency and return predictability of new cryptocurrencies.

Suggested Citation

  • Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    • Handle: RePEc:eee:ecolet:v:168:y:2018:i:c:p:21-24
    DOI: 10.1016/j.econlet.2018.04.003
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    1. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    2. Selgin, George, 2015. "Synthetic commodity money," Journal of Financial Stability, Elsevier, vol. 17(C), pages 92-99.
    3. Nadarajah, Saralees & Chu, Jeffrey, 2017. "On the inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 150(C), pages 6-9.
    4. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    5. 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.
    6. 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.
    7. Kim, Jae H., 2009. "Automatic variance ratio test under conditional heteroskedasticity," Finance Research Letters, Elsevier, vol. 6(3), pages 179-185, September.
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    More about this item

    Keywords

    Bitcoin; Cryptocurrency; Market efficiency; Market liquidity;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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