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The relationship between trend and volume on the bitcoin market

Author

Listed:
  • Beata Szetela

    (Rzeszów University of Technology)

  • Grzegorz Mentel

    (Rzeszów University of Technology)

  • Yuriy Bilan

    (Tomas Bata University in Zlín)

  • Urszula Mentel

    (Rzeszów University of Technology)

Abstract

The aim of the paper is to verify the existence of short- and long-term relationships between the strength of a trend and the volume in bullish and bearish cryptocurrency markets. We applied the vector error correction model to bitcoin daily data from 14.01.2015 to 22.12.2019. Based on the prices and following Wilder’s algorithm, the average directional movement index was calculated, and upward and downward trend periods were determined. No long-term relationship was found to exist between the strength of a trend and the volume in both bearish and bullish markets. Hence, trends do not react to volume changes. However, a long-term relationship exists between volume and trend—but only for the downward trend—with an adjustment speed of 88%. In the short-term, a statistically significant but very weak dependency is revealed; hence, the conclusion that trend strength is insensitive to volume changes can be reached.

Suggested Citation

  • Beata Szetela & Grzegorz Mentel & Yuriy Bilan & Urszula Mentel, 2021. "The relationship between trend and volume on the bitcoin market," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(1), pages 25-42, March.
    • Handle: RePEc:spr:eurase:v:11:y:2021:i:1:d:10.1007_s40822-021-00166-5
    DOI: 10.1007/s40822-021-00166-5
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    as
    1. Pengfei Wang & Wei Zhang & Xiao Li & Dehua Shen, 2019. "Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 377-418, June.
    2. Wood, Robert A & McInish, Thomas H & Ord, J Keith, 1985. "An Investigation of Transactions Data for NYSE Stocks," Journal of Finance, American Finance Association, vol. 40(3), pages 723-739, July.
    3. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    4. Cooper, Michael & Downs, David H & Patterson, Gary A, 2000. "Asymmetric Information and the Predictability of Real Estate Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 20(2), pages 225-244, March.
    5. Urquhart, Andrew, 2017. "Price clustering in Bitcoin," Economics Letters, Elsevier, vol. 159(C), pages 145-148.
    6. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    7. Glaser, Markus & Weber, Martin, 2009. "Which past returns affect trading volume?," Journal of Financial Markets, Elsevier, vol. 12(1), pages 1-31, February.
    8. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    9. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2002. "Dynamic Volume-Return Relation of Individual Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1005-1047.
    10. Bessembinder, Hendrik & Seguin, Paul J., 1993. "Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(1), pages 21-39, March.
    11. Yhlas Sovbetov, 2018. "Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 2(2), pages 1-27.
    12. Ciaian, Pavel & Rajcaniova, Miroslava & Kancs, d'Artis, 2018. "Virtual relationships: Short- and long-run evidence from BitCoin and altcoin markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 173-195.
    13. Corbet, Shaen & Lucey, Brian & Yarovaya, Larisa, 2018. "Datestamping the Bitcoin and Ethereum bubbles," Finance Research Letters, Elsevier, vol. 26(C), pages 81-88.
    14. John M. Griffin & Federico Nardari & René M. Stulz, 2007. "Do Investors Trade More When Stocks Have Performed Well? Evidence from 46 Countries," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 905-951.
    15. 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.
    16. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    17. Paul Lau, Sau-Him, 1999. "I(0) In, integration and cointegration out:: Time series properties of endogenous growth models," Journal of Econometrics, Elsevier, vol. 93(1), pages 1-24, November.
    18. Tianyi Wang & Zhuo Huang, 2012. "The Relationship between Volatility and Trading Volume in the Chinese Stock Market: A Volatility Decomposition Perspective," Annals of Economics and Finance, Society for AEF, vol. 13(1), pages 211-236, May.
    19. James, Christopher M & Edmister, Robert O, 1983. "The Relation between Common Stock Returns Trading Activity and Market Value," Journal of Finance, American Finance Association, vol. 38(4), pages 1075-1086, September.
    20. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    21. Harris, Lawrence E & Gurel, Eitan, 1986. "Price and Volume Effects Associated with Changes in the S&P 500 List: New Evidence for the Existence of Price Pressures," Journal of Finance, American Finance Association, vol. 41(4), pages 815-829, September.
    22. Jennings, Robert H & Starks, Laura T & Fellingham, John C, 1981. "An Equilibrium Model of Asset Trading with Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 36(1), pages 143-161, March.
    23. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    24. Giot, Pierre & Laurent, Sébastien & Petitjean, Mikael, 2010. "Trading activity, realized volatility and jumps," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 168-175, January.
    25. David McMillan & Alan Speight, 2002. "Return-volume dynamics in UK futures," Applied Financial Economics, Taylor & Francis Journals, vol. 12(10), pages 707-713.
    26. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    27. Fleming, Jeff & Kirby, Chris, 2011. "Long memory in volatility and trading volume," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1714-1726, July.
    28. Morgan, I G, 1976. "Stock Prices and Heteroscedasticity," The Journal of Business, University of Chicago Press, vol. 49(4), pages 496-508, October.
    29. Shih-Yung Wei & Li-Wei Lin & Surong Yan & Lu-jie Zhu, 2019. "Empirical Analysis on Price-Volume Relation in the Stock Market of China," International Journal of Economics and Financial Issues, Econjournals, vol. 9(5), pages 94-103.
    30. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    31. Bradford Cornell, 1981. "The relationship between volume and price variability in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 1(3), pages 303-316, September.
    32. Pradipta Kumar Sahoo & Dinabandhu Sethi & Debashis Acharya, 2019. "Is bitcoin a near stock? Linear and non-linear causal evidence from a price–volume relationship," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 15(4), pages 533-545, April.
    33. Jaka Sriyana, 2019. "What drives economic growth sustainability? Evidence from Indonesia," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(2), pages 906-918, December.
    34. Meir Statman & Steven Thorley & Keith Vorkink, 2006. "Investor Overconfidence and Trading Volume," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1531-1565.
    35. Harris, Milton & Raviv, Artur, 1993. "Differences of Opinion Make a Horse Race," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 473-506.
    36. Michael Smirlock & Laura Starks, 1985. "A Further Examination Of Stock Price Changes And Transaction Volume," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 8(3), pages 217-226, September.
    37. Crouch, R L, 1970. "A Nonlinear Test of the Random-Walk Hypothesis," American Economic Review, American Economic Association, vol. 60(1), pages 199-202, March.
    38. Beata Szetela & Grzegorz Mentel & Stanislaw Gedek, 2016. "Dependency analysis between Bitcoin and selected global currencies," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 16, pages 133-144.
    39. Ishmael Radikoko & Emmanuel Ndjadingwe, 2015. "Investigating the Effects of Dividends Pay-out on Stock Prices and Traded Equity Volumes of BSE Listed Firms," International Journal of Innovation and Economic Development, Inovatus Services Ltd., vol. 1(4), pages 24-37, October.
    40. Westerfield, Randolph, 1977. "The Distribution of Common Stock Price Changes: An Application of Transactions Time and Subordinated Stochastic Models," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(5), pages 743-765, December.
    41. Stock, James H, 1987. "Asymptotic Properties of Least Squares Estimators of Cointegrating Vectors," Econometrica, Econometric Society, vol. 55(5), pages 1035-1056, September.
    42. Ahmet E. Kocagil & Yochanan Shachmurove, 1998. "Return‐volume dynamics in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 18(4), pages 399-426, June.
    43. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    44. Ji, Qiang & Zhang, Dayong, 2019. "China’s crude oil futures: Introduction and some stylized facts," Finance Research Letters, Elsevier, vol. 28(C), pages 376-380.
    45. Imad A. Moosa & Param Silvapulle & Mervyn Silvapulle, 2003. "Testing for Temporal Asymmetry in the Price‐Volume Relationship," Bulletin of Economic Research, Wiley Blackwell, vol. 55(4), pages 373-389, October.
    46. Park, Beum-Jo, 2010. "Surprising information, the MDH, and the relationship between volatility and trading volume," Journal of Financial Markets, Elsevier, vol. 13(3), pages 344-366, August.
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    Cited by:

    1. Luis Lorenzo & Javier Arroyo, 2022. "Analysis of the cryptocurrency market using different prototype-based clustering techniques," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-46, December.
    2. 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).
    3. Adeyinka Adediran & Bola Babajide & Nataliia Osina, 2023. "Exploring the nexus between price and volume changes in the cryptocurrency market," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 498-512, October.
    4. Clement Moyo & Andrew Phiri, 2023. "Re-Examining Bitcoin’s Price–Volume Relationship: A Time-Varying Spectral Analysis," JRFM, MDPI, vol. 16(7), pages 1-16, July.
    5. Jong-Min Kim & Chanho Cho & Chulhee Jun, 2022. "Forecasting the Price of the Cryptocurrency Using Linear and Nonlinear Error Correction Model," JRFM, MDPI, vol. 15(2), pages 1-10, February.
    6. Achraf Ghorbel & Wajdi Frikha & Yasmine Snene Manzli, 2022. "Testing for asymmetric non-linear short- and long-run relationships between crypto-currencies and stock markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 387-425, September.
    7. Corina-Narcisa (Bodescu) Cotoc & Maria Nițu & Mircea Constantin Șcheau & Adeline-Cristina Cozma, 2021. "Efficiency of Money Laundering Countermeasures: Case Studies from European Union Member States," Risks, MDPI, vol. 9(6), pages 1-19, June.

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    More about this item

    Keywords

    VECM; VAR; ADX; Volume; Long-run; Bitcoin; Cryptocurrency;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets

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