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What Does Crypto-currency Look Like? Gaining Insight into Bitcoin Phenomenon

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  • Bouoiyour, Jamal
  • Selmi, Refk

Abstract

The present paper seeks to effectively address the following question: What Bitcoin looks like? To do so, we regress Bitcoin price on a number of variables (Bitcoin fundamentals recorded in the literature) by applying an ARDL Bounds Testing approach for daily data covering the period from December 2010 to June 2014. Our findings highlight the speculative nature of Bitcoin. We also provide insightful evidence that Bitcoin may be used for economic reasons but there is any sign of being a safe haven. By considering the Chinese trading bankruptcy and the closing of Road Silk by FBI, the contribution of users’ interest stills sharply dominant, indicating the robustness of our results.

Suggested Citation

  • Bouoiyour, Jamal & Selmi, Refk, 2014. "What Does Crypto-currency Look Like? Gaining Insight into Bitcoin Phenomenon," MPRA Paper 57907, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:57907
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    File URL: https://mpra.ub.uni-muenchen.de/57907/3/MPRA_paper_57907.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. David Yermack, 2013. "Is Bitcoin a Real Currency? An economic appraisal," NBER Working Papers 19747, National Bureau of Economic Research, Inc.
    3. Bouoiyour, Jamal & Selmi, Refk & Tiwari, Aviral, 2014. "Is Bitcoin business income or speculative bubble? Unconditional vs. conditional frequency domain analysis," MPRA Paper 59595, University Library of Munich, Germany.
    4. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    5. Ladislav Kristoufek, 2015. "What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-15, April.
    6. Gregory, Allan W. & Hansen, Bruce E., 1996. "Residual-based tests for cointegration in models with regime shifts," Journal of Econometrics, Elsevier, vol. 70(1), pages 99-126, January.
    7. Matija Piv{s}korec & Nino Antulov-Fantulin & Petra Kralj Novak & Igor Mozetiv{c} & Miha Grv{c}ar & Irena Vodenska & Tomislav v{S}muc, 2014. "News Cohesiveness: an Indicator of Systemic Risk in Financial Markets," Papers 1402.3483, arXiv.org.
    8. Breitung, Jorg & Candelon, Bertrand, 2006. "Testing for short- and long-run causality: A frequency-domain approach," Journal of Econometrics, Elsevier, vol. 132(2), pages 363-378, June.
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    Cited by:

    1. Panpan Zhu & Xing Zhang & You Wu & Hao Zheng & Yinpeng Zhang, 2021. "Investor attention and cryptocurrency: Evidence from the Bitcoin market," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-28, February.
    2. Clément Landormy, 2024. "An inquiry of Bitcoin price formation: Evidence from Linear and Nonlinear ARDL Frameworks, 2017-2018," Working Papers of BETA 2024-31, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    3. Taufeeq Ajaz & Anoop S. Kumar, 2018. "Herding In Crypto-Currency Markets," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-15, June.

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    More about this item

    Keywords

    Bitcoin; ARDL Bounds Testing method; innovative accounting approach; VEC Granger causality test.;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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