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Preference heterogeneity in Bitcoin and its forks' network

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  • Kim, Hyeonoh
  • Ha, Chang Yong
  • Ahn, Kwangwon

Abstract

This study investigates the transmission channel of information diffusion in the network of Bitcoin and its six forks using daily closing prices from the start of trading for each one to September 24, 2021. In particular, the price series are stationarized for further analysis by converting them to log returns. We find the following: (i) the Bitcoin market has the central authority of information flow because of its large market size and high liquidity, and (ii) the Bitcoin Gold and Bitcoin Diamond markets collaborate in information dissemination and intermediary role despite their small market size and low liquidity. Using the scaling and Hurst exponents, we explain the roles of Bitcoin, Bitcoin Gold, and Bitcoin Diamond in the network of forks. The potential externality emerges from a highly liquid market and spreads through efficient markets in terms of price fairness, resulting in considerable information share in the cryptocurrency market. Our findings suggest that the forks' network evolves for preference heterogeneity rather than for a single dominant entity with market leadership in the network.

Suggested Citation

  • Kim, Hyeonoh & Ha, Chang Yong & Ahn, Kwangwon, 2022. "Preference heterogeneity in Bitcoin and its forks' network," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    • Handle: RePEc:eee:chsofr:v:164:y:2022:i:c:s0960077922008980
    DOI: 10.1016/j.chaos.2022.112719
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    as
    1. Patrick L. Brockett & Yehuda Kahane, 1992. "Risk, Return, Skewness and Preference," Management Science, INFORMS, vol. 38(6), pages 851-866, June.
    2. Grossman, Sanford J & Miller, Merton H, 1988. " Liquidity and Market Structure," Journal of Finance, American Finance Association, vol. 43(3), pages 617-637, July.
    3. Shahzad, Syed Jawad Hussain & Bouri, Elie & Ahmad, Tanveer & Naeem, Muhammad Abubakr, 2022. "Extreme tail network analysis of cryptocurrencies and trading strategies," Finance Research Letters, Elsevier, vol. 44(C).
    4. John M. Griffin & Amin Shams, 2020. "Is Bitcoin Really Untethered?," Journal of Finance, American Finance Association, vol. 75(4), pages 1913-1964, August.
    5. Kwangwon Ahn & Yingyao Bi & Sungbin Sohn, 2019. "Price discovery among SSE 50 Index‐based spot, futures, and options markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(2), pages 238-259, February.
    6. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, May.
    7. Xavier Gabaix, 2016. "Power Laws in Economics: An Introduction," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 185-206, Winter.
    8. Qureshi, Saba & Aftab, Muhammad & Bouri, Elie & Saeed, Tareq, 2020. "Dynamic interdependence of cryptocurrency markets: An analysis across time and frequency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    9. Zięba, Damian & Kokoszczyński, Ryszard & Śledziewska, Katarzyna, 2019. "Shock transmission in the cryptocurrency market. Is Bitcoin the most influential?," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 102-125.
    10. Giudici, Paolo & Abu-Hashish, Iman, 2019. "What determines bitcoin exchange prices? A network VAR approach," Finance Research Letters, Elsevier, vol. 28(C), pages 309-318.
    11. Liu, Xia & Liu, Shancun & Qi, Zhen & Wen, Chunhui, 2020. "Discretionary liquidity trading, information production and market efficiency," Finance Research Letters, Elsevier, vol. 35(C).
    12. Bouri, Elie & Saeed, Tareq & Vo, Xuan Vinh & Roubaud, David, 2021. "Quantile connectedness in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    13. 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.
    14. Kumar, Ashish & Iqbal, Najaf & Mitra, Subrata Kumar & Kristoufek, Ladislav & Bouri, Elie, 2022. "Connectedness among major cryptocurrencies in standard times and during the COVID-19 outbreak," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    15. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    16. Song, Jung Yoon & Chang, Woojin & Song, Jae Wook, 2019. "Cluster analysis on the structure of the cryptocurrency market via Bitcoin–Ethereum filtering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    17. Chung, Dennis & Hrazdil, Karel, 2010. "Liquidity and market efficiency: A large sample study," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2346-2357, October.
    18. Syed Jawad Hussain Shahzad & Elie Bouri & Sang Hoon Kang & Tareq Saeed, 2021. "Regime specific spillover across cryptocurrencies and the role of COVID-19," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
    19. Bohl, Martin T. & Pütz, Alexander & Sulewski, Christoph, 2021. "Speculation and the informational efficiency of commodity futures markets," Journal of Commodity Markets, Elsevier, vol. 23(C).
    20. P. Gopikrishnan & M. Meyer & L.A.N. Amaral & H.E. Stanley, 1998. "Inverse cubic law for the distribution of stock price variations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 3(2), pages 139-140, July.
    21. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    22. Chansoo Kim & Daniel S Kim & Kwangwon Ahn & M Y Choi, 2017. "Dynamics of analyst forecasts and emergence of complexity: Role of information disparity," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-18, May.
    23. Dimpfl Thomas & Peter Franziska Julia, 2013. "Using transfer entropy to measure information flows between financial markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 85-102, February.
    24. Ji, Qiang & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2018. "Network causality structures among Bitcoin and other financial assets: A directed acyclic graph approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 203-213.
    25. David I. Okorie, 2021. "A network analysis of electricity demand and the cryptocurrency markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 3093-3108, April.
    26. Rabeh Khalfaoui & Sami Ben Jabeur & Buhari Dogan, 2022. "The spillover effects and connectedness among green commodities, Bitcoins, and US stock markets: Evidence from the quantile VAR network," Post-Print hal-03797573, HAL.
    27. Wenjin Kang & K. Geert Rouwenhorst & Ke Tang, 2020. "A Tale of Two Premiums: The Role of Hedgers and Speculators in Commodity Futures Markets," Journal of Finance, American Finance Association, vol. 75(1), pages 377-417, February.
    28. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    29. Joel L. Horowitz, 2003. "Bootstrap Methods for Markov Processes," Econometrica, Econometric Society, vol. 71(4), pages 1049-1082, July.
    30. Hasbrouck, Joel, 1995. "One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
    31. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    32. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    33. Guo, Xiaochun & Lu, Fengbin & Wei, Yunjie, 2021. "Capture the contagion network of bitcoin – Evidence from pre and mid COVID-19," Research in International Business and Finance, Elsevier, vol. 58(C).
    34. Choi, Darwin & Getmansky, Mila & Tookes, Heather, 2009. "Convertible bond arbitrage, liquidity externalities, and stock prices," Journal of Financial Economics, Elsevier, vol. 91(2), pages 227-251, February.
    35. Parameswaran Gopikrishnan & Martin Meyer & Luis A Nunes Amaral & H Eugene Stanley, 1998. "Inverse Cubic Law for the Probability Distribution of Stock Price Variations," Papers cond-mat/9803374, arXiv.org, revised May 1998.
    36. Bruno Biais & Christophe Bisière & Matthieu Bouvard & Catherine Casamatta, 2019. "Blockchains, Coordination, and Forks," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 88-92, May.
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