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Intraday volume-return nexus in cryptocurrency markets: Novel evidence from cryptocurrency classification

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  • Yarovaya, Larisa
  • Zięba, Damian

Abstract

This paper analyses the volume-return relationships across the top 30 most traded cryptocurrencies from February 2018 to July 2019 using high-frequency intraday data. We use a novel approach for the classification of cryptocurrencies with respect to multiple qualitative factors, such as geographical location of headquarters, founder and founder’s origin, platform on which the cryptocurrency is built, and consensus algorithm, among others. We identify significant bidirectional causalities between trading volume and returns at different high-frequency intervals; however, those linkages are weakening with decreasing data frequencies. The findings confirm the leading position of the Bitcoin trading volume in the cryptocurrency price formation. This evidence will help investors to design effective trading strategies in cryptocurrency markets providing useful insights from cryptocurrency categorisation.

Suggested Citation

  • Yarovaya, Larisa & Zięba, Damian, 2022. "Intraday volume-return nexus in cryptocurrency markets: Novel evidence from cryptocurrency classification," Research in International Business and Finance, Elsevier, vol. 60(C).
  • Handle: RePEc:eee:riibaf:v:60:y:2022:i:c:s0275531921002130
    DOI: 10.1016/j.ribaf.2021.101592
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    as
    1. Gervais, Simon & Odean, Terrance, 2001. "Learning to be Overconfident," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 1-27.
    2. Diks Cees & Panchenko Valentyn, 2005. "A Note on the Hiemstra-Jones Test for Granger Non-causality," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-9, June.
    3. Terrance Odean., 1996. "Volume, Volatility, Price and Profit When All Trader Are Above Average," Research Program in Finance Working Papers RPF-266, University of California at Berkeley.
    4. Lakonishok, Josef & Smidt, Seymour, 1986. "Volume for Winners and Losers: Taxation and Other Motives for Stock Trading," Journal of Finance, American Finance Association, vol. 41(4), pages 951-974, September.
    5. Makarov, Igor & Schoar, Antoinette, 2020. "Trading and arbitrage in cryptocurrency markets," Journal of Financial Economics, Elsevier, vol. 135(2), pages 293-319.
    6. Bouraoui, Taoufik, 2020. "The drivers of Bitcoin trading volume in selected emerging countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 218-229.
    7. Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Herding behaviour in cryptocurrencies," Finance Research Letters, Elsevier, vol. 29(C), pages 216-221.
    8. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    9. Khuntia, Sashikanta & Pattanayak, J.K., 2020. "Adaptive long memory in volatility of intra-day bitcoin returns and the impact of trading volume," Finance Research Letters, Elsevier, vol. 32(C).
    10. Urquhart, Andrew, 2018. "What causes the attention of Bitcoin?," Economics Letters, Elsevier, vol. 166(C), pages 40-44.
    11. Brad M. Barber & Terrance Odean, 2000. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors," Journal of Finance, American Finance Association, vol. 55(2), pages 773-806, April.
    12. Gianna Figà-Talamanca & Marco Patacca, 2020. "Disentangling the relationship between Bitcoin and market attention measures," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 71-91, March.
    13. repec:bla:jfinan:v:53:y:1998:i:5:p:1775-1798 is not listed on IDEAS
    14. Fassas, Athanasios P. & Papadamou, Stephanos & Koulis, Alexandros, 2020. "Price discovery in bitcoin futures," Research in International Business and Finance, Elsevier, vol. 52(C).
    15. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    16. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    17. Brad M. Barber & Terrance Odean, 2002. "Online Investors: Do the Slow Die First?," The Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 455-488, March.
    18. Zhang, Wei & Li, Yi, 2020. "Is idiosyncratic volatility priced in cryptocurrency markets?," Research in International Business and Finance, Elsevier, vol. 54(C).
    19. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    20. Aalborg, Halvor Aarhus & Molnár, Peter & de Vries, Jon Erik, 2019. "What can explain the price, volatility and trading volume of Bitcoin?," Finance Research Letters, Elsevier, vol. 29(C), pages 255-265.
    21. Baur, Dirk G. & Cahill, Daniel & Godfrey, Keith & (Frank) Liu, Zhangxin, 2019. "Bitcoin time-of-day, day-of-week and month-of-year effects in returns and trading volume," Finance Research Letters, Elsevier, vol. 31(C), pages 78-92.
    22. Makarov, Igor & Schoar, Antoinette, 2020. "Trading and arbitrage in cryptocurrency markets," LSE Research Online Documents on Economics 100409, London School of Economics and Political Science, LSE Library.
    23. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    24. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    25. Platanakis, Emmanouil & Urquhart, Andrew, 2020. "Should investors include Bitcoin in their portfolios? A portfolio theory approach," The British Accounting Review, Elsevier, vol. 52(4).
    26. Shefrin, Hersh & Statman, Meir, 1985. "The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence," Journal of Finance, American Finance Association, vol. 40(3), pages 777-790, July.
    27. Akyildirim, Erdinc & Corbet, Shaen & Sensoy, Ahmet & Yarovaya, Larisa, 2020. "The impact of blockchain related name changes on corporate performance," Journal of Corporate Finance, Elsevier, vol. 65(C).
    28. Terrance Odean, 1999. "Do Investors Trade Too Much?," American Economic Review, American Economic Association, vol. 89(5), pages 1279-1298, December.
    29. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    30. Corbet, Shaen & Lucey, Brian & Peat, Maurice & Vigne, Samuel, 2018. "Bitcoin Futures—What use are they?," Economics Letters, Elsevier, vol. 172(C), pages 23-27.
    31. Damianov, Damian S. & Elsayed, Ahmed H., 2020. "Does Bitcoin add value to global industry portfolios?," Economics Letters, Elsevier, vol. 191(C).
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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. Katsiampa, Paraskevi & Yarovaya, Larisa & Zięba, Damian, 2022. "High-frequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    3. Şoiman, Florentina & Dumas, Jean-Guillaume & Jimenez-Garces, Sonia, 2023. "What drives DeFi market returns?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    4. Naeem, Muhammad Abubakr & Yousaf, Imran & Karim, Sitara & Yarovaya, Larisa & Ali, Shoaib, 2023. "Tail-event driven NETwork dependence in emerging markets," Emerging Markets Review, Elsevier, vol. 55(C).
    5. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).
    6. Zhao, Yuan & Liu, Nan & Li, Wanpeng, 2022. "Industry herding in crypto assets," International Review of Financial Analysis, Elsevier, vol. 84(C).
    7. Ghosh, Indranil & Alfaro-Cortés, Esteban & Gámez, Matías & García-Rubio, Noelia, 2023. "Prediction and interpretation of daily NFT and DeFi prices dynamics: Inspection through ensemble machine learning & XAI," International Review of Financial Analysis, Elsevier, vol. 87(C).
    8. José Antonio Núñez-Mora & Mario Iván Contreras-Valdez & Roberto Joaquín Santillán-Salgado, 2023. "Risk Premium of Bitcoin and Ethereum during the COVID-19 and Non-COVID-19 Periods: A High-Frequency Approach," Mathematics, MDPI, vol. 11(20), pages 1-20, October.
    9. Jalan, Akanksha & Matkovskyy, Roman & Urquhart, Andrew, 2022. "Demand elasticities of Bitcoin and Ethereum," Economics Letters, Elsevier, vol. 220(C).
    10. Zięba, Damian, 2024. "If GPU(time) == money: Sustainable crypto-asset market? Analysis of similarity among crypto-asset financial time series," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 863-912.
    11. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).

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    More about this item

    Keywords

    Cryptocurrency classification; Bitcoin; Volume-return relationships; Granger causality;
    All these keywords.

    JEL classification:

    • 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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