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Analysis on the influence factors of Bitcoin’s price based on VEC model

Author

Listed:
  • Yechen Zhu

    (School of Finance, Central University of Finance and Economics)

  • David Dickinson

    (University of Birmingham)

  • Jianjun Li

    (School of Finance, Central University of Finance and Economics)

Abstract

Background Bitcoin, the most innovate digital currency as of now, created since 2008, even through experienced its ups and downs, still keeps drawing attentions to all parts of society. It relies on peer-to-peer network, achieved decentralization, anonymous and transparent. As the most representative digital currency, people curious to study how Bitcoin’ price changes in the past. Methods In this paper, we use monthly data from 2011 to 2016 to build a VEC model to exam how economic factors such as Custom price index, US dollar index, Dow jones industry average, Federal Funds Rate and gold price influence Bitcoin price. Result From empirical analysis we find that all these variables do have a long-term influence. US dollar index is the biggest influence on Bitcoin price while gold price influence the least. Conclusion From our result, we conclude that for now Bitcoin can be treated as a speculative asset, however, it is far from being a proper credit currency.

Suggested Citation

  • Yechen Zhu & David Dickinson & Jianjun Li, 2017. "Analysis on the influence factors of Bitcoin’s price based on VEC model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-13, December.
    • Handle: RePEc:spr:fininn:v:3:y:2017:i:1:d:10.1186_s40854-017-0054-0
    DOI: 10.1186/s40854-017-0054-0
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    References listed on IDEAS

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    1. Maria Herrerias, 2010. "The causal relationship between equipment investment and infrastructures on economic growth in China," Frontiers of Economics in China, Springer;Higher Education Press, vol. 5(4), pages 509-526, December.
    2. David Yermack, 2013. "Is Bitcoin a Real Currency? An economic appraisal," NBER Working Papers 19747, National Bureau of Economic Research, Inc.
    3. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    4. Aaron Yelowitz & Matthew Wilson, 2015. "Characteristics of Bitcoin users: an analysis of Google search data," Applied Economics Letters, Taylor & Francis Journals, vol. 22(13), pages 1030-1036, September.
    5. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    6. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    7. Anne Haubo Dyhrberg, 2015. "Bitcoin, Gold and the Dollar – a GARCH Volatility Analysis," Working Papers 201520, School of Economics, University College Dublin.
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