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Directional predictability between returns and volume in cryptocurrencies markets

Author

Listed:
  • Panos Fousekis
  • Vasilis Grigoriadis

Abstract

Purpose - This paper aims to identify and quantify directional predictability between returns and volume in major cryptocurrencies markets. Design/methodology/approach - The empirical analysis relies on the cross-quantilogram approach that allows one to assess the temporal (lag-lead) association between two stationary time series at different parts of their joint distribution. The data are daily prices and trading volumes from four markets (Bitcoin, Ethereum, Ripple and Litecoin). Findings - Extreme returns either positive or negative tend to lead high volume levels. Low levels of trading activity have in general no information content about future returns; high levels, however, tend to precede extreme positive returns. Originality/value - This is the first work that uses the cross-quantilogram approach to assess the temporal association between returns and volume in cryptocurrencies markets. The findings provide new insights about the informational efficiency of these markets and the traders’ strategies.

Suggested Citation

  • Panos Fousekis & Vasilis Grigoriadis, 2021. "Directional predictability between returns and volume in cryptocurrencies markets," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 38(4), pages 693-711, February.
    • Handle: RePEc:eme:sefpps:sef-08-2020-0318
    DOI: 10.1108/SEF-08-2020-0318
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    Citations

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    Cited by:

    1. 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).
    2. Nuray Tosunoğlu & Hilal Abacı & Gizem Ateş & Neslihan Saygılı Akkaya, 2023. "Artificial neural network analysis of the day of the week anomaly in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-24, December.

    More about this item

    Keywords

    Returns; Volume; Predictability; Cryptocurrencies; Quantile dependence; G14; C12;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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