IDEAS home Printed from https://ideas.repec.org/a/spr/infsem/v14y2016i4d10.1007_s10257-016-0304-0.html
   My bibliography  Save this article

The digital agenda of virtual currencies: Can BitCoin become a global currency?

Author

Listed:
  • Pavel Ciaian

    (DG Joint Research Centre)

  • Miroslava Rajcaniova

    (Slovak University of Agriculture (SUA))

  • d’Artis Kancs

    (DG Joint Research Centre)

Abstract

This paper identifies and analyzes BitCoin features which may facilitate BitCoin to become a global currency, as well as characteristics which may impede the use of BitCoin as a medium of exchange, a unit of account and a store of value, and compares BitCoin with standard currencies with respect to the main functions of money. Among all analyzed BitCoin features, the extreme price volatility stands out most clearly compared to standard currencies. In order to understand the reasons for such extreme price volatility, we attempt to identify drivers of BitCoin price formation and estimate their importance econometrically. We apply time-series analytical mechanisms to daily data for the 2009–2014 period. Our estimation results suggest that BitCoin attractiveness indicators are the strongest drivers of BitCoin price followed by market forces. In contrast, macro-financial developments do not determine BitCoin price in the long-run. Our findings suggest that as long as BitCoin price will be mainly driven by speculative investments, BitCoin will not be able to compete with standard currencies.

Suggested Citation

  • Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The digital agenda of virtual currencies: Can BitCoin become a global currency?," Information Systems and e-Business Management, Springer, vol. 14(4), pages 883-919, November.
    • Handle: RePEc:spr:infsem:v:14:y:2016:i:4:d:10.1007_s10257-016-0304-0
    DOI: 10.1007/s10257-016-0304-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10257-016-0304-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10257-016-0304-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    2. Dan Kovenock, 2002. "Fiat Exchange in Finite Economies," Economic Inquiry, Western Economic Association International, vol. 40(2), pages 147-157, April.
    3. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, September.
    4. Gautam Gowrisankaran & Joanna Stavins, 2004. "Network Externalities and Technology Adoption: Lessons from Electronic Payments," RAND Journal of Economics, The RAND Corporation, vol. 35(2), pages 260-276, Summer.
    5. 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.
    6. Simon Gervais & Ron Kaniel & Dan H. Mingelgrin, 2001. "The High‐Volume Return Premium," Journal of Finance, American Finance Association, vol. 56(3), pages 877-919, June.
    7. Nicolas Houy, 2014. "The economics of Bitcoin transaction fees," Working Papers halshs-00951358, HAL.
    8. Francois R. Velde, 2013. "Bitcoin: a primer," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue Dec.
    9. Jamal Bouoiyour & Refk Selmi, 2015. "What Does Bitcoin Look Like?," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 449-492, November.
    10. 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.
    11. Gustavo Grullon, 2004. "Advertising, Breadth of Ownership, and Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 439-461.
    12. Pantula, Sastry G., 1989. "Testing for Unit Roots in Time Series Data," Econometric Theory, Cambridge University Press, vol. 5(2), pages 256-271, August.
    13. Rainer Böhme & Nicolas Christin & Benjamin Edelman & Tyler Moore, 2015. "Bitcoin: Economics, Technology, and Governance," Journal of Economic Perspectives, American Economic Association, vol. 29(2), pages 213-238, Spring.
    14. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521839198, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. 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.
    3. Cedric Mbanga & Ali F. Darrat & Jung Chul Park, 2019. "Investor sentiment and aggregate stock returns: the role of investor attention," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 397-428, August.
    4. Wang, Chen & Shen, Dehua & Li, Youwei, 2022. "Aggregate Investor Attention and Bitcoin Return: The Long Short-term Memory Networks Perspective," Finance Research Letters, Elsevier, vol. 49(C).
    5. Robert Socha & Piotr Wdowiński, 2018. "Crude oil price and speculative activity: a cointegration analysis," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(3), pages 263-304, September.
    6. Algieri, Bernardina, 2013. "A Roller Coaster Ride: an empirical investigation of the main drivers of wheat price," Discussion Papers 145556, University of Bonn, Center for Development Research (ZEF).
    7. Avishek Khanal & Mohammad Mafizur Rahman & Rasheda Khanam & Eswaran Velayutham, 2021. "Are Tourism and Energy Consumption Linked? Evidence from Australia," Sustainability, MDPI, vol. 13(19), pages 1-20, September.
    8. Pedro M. G. Martins, 2010. "Fiscal Dynamics in Ethiopia: The Cointegrated VAR Model with Quarterly Data," Working Paper Series 0910, Department of Economics, University of Sussex Business School.
    9. Elżbieta Szaruga & Elżbieta Załoga, 2022. "Environmental Management from the Point of View of the Energy Intensity of Road Freight Transport and Shocks," IJERPH, MDPI, vol. 19(21), pages 1-22, November.
    10. Afsin Sahin, 2019. "Loom of Symmetric Pass-Through," Economies, MDPI, vol. 7(1), pages 1-25, February.
    11. Batool, Irem & Goldmann, Kathrin, 2021. "The role of public and private transport infrastructure capital in economic growth. Evidence from Pakistan," Research in Transportation Economics, Elsevier, vol. 88(C).
    12. Kaminski, Jermain & Hopp, Christian & Tykvová, Tereza, 2019. "New technology assessment in entrepreneurial financing – Does crowdfunding predict venture capital investments?," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 287-302.
    13. Mai, Nhat Chi, 2019. "Stock Market And Economic Growth In Vietnam," OSF Preprints de8zq, Center for Open Science.
    14. , Aisdl, 2019. "Stock Market And Economic Growth In Vietnam," OSF Preprints ucbhp, Center for Open Science.
    15. Cuiabano, Simone & Nicolini de Moraes, João Carlos & Pinha, Lucas, 2017. "Application of time series techniques in relevant market delimitation," TSE Working Papers 17-801, Toulouse School of Economics (TSE).
    16. Levent, Korap, 2007. "Modeling purchasing power parity using co-integration: evidence from Turkey," MPRA Paper 19584, University Library of Munich, Germany.
    17. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    18. Bernardina Algieri, 2014. "A roller coaster ride: an empirical investigation of the main drivers of the international wheat price," Agricultural Economics, International Association of Agricultural Economists, vol. 45(4), pages 459-475, July.
    19. Grau, Aaron Stephan Alexander & Hockmann, Heinrich, 2017. "Estimating oligopsony power on two vertically integrated markets," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 261277, European Association of Agricultural Economists.
    20. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164, Edward Elgar Publishing.

    More about this item

    Keywords

    BitCoin; Virtual currency; Exchange rate; Supply and demand; Financial indicators; Attention-driven investment;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infsem:v:14:y:2016:i:4:d:10.1007_s10257-016-0304-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.