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Is Bitcoin a bubble?

Author

Listed:
  • Chaim, Pedro
  • Laurini, Márcio P.

Abstract

The narrative of a Bitcoin is a bubble is very common. We employ statistical techniques to empirically evaluate such claim. A branch of literature links the existence of a bubble in some financial asset’s price to strict local martingales — a finitely lived asset has a bubble if, and only if, it is a strict local martingale under the equivalent risk-neutral measure. A diffusion process is a strict local martingale if its volatility increases faster than linearly as its level grows. We apply a nonparametric method to estimate the volatility function of Bitcoin daily and high frequency prices, as well as of more traditional financial assets. We then estimate the stochastic volatility model of Andersen and Piterbarg (2007), whose parameter space has a specific subset under which the asset’s price is a strict local martingale. Results suggest the existence of a bubble in Bitcoin prices from early 2013 to mid 2014, but, interestingly, not in late 2017.

Suggested Citation

  • Chaim, Pedro & Laurini, Márcio P., 2019. "Is Bitcoin a bubble?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 222-232.
    • Handle: RePEc:eee:phsmap:v:517:y:2019:i:c:p:222-232
    DOI: 10.1016/j.physa.2018.11.031
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    References listed on IDEAS

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    1. David Garcia & Claudio Juan Tessone & Pavlin Mavrodiev & Nicolas Perony, 2014. "The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy," Papers 1408.1494, arXiv.org.
    2. 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.
    3. Corbet, Shaen & Lucey, Brian & Yarovaya, Larisa, 2018. "Datestamping the Bitcoin and Ethereum bubbles," Finance Research Letters, Elsevier, vol. 26(C), pages 81-88.
    4. Chaim, Pedro & Laurini, Márcio P., 2018. "Volatility and return jumps in bitcoin," Economics Letters, Elsevier, vol. 173(C), pages 158-163.
    5. Baldeaux, Jan & Ignatieva, Katja & Platen, Eckhard, 2018. "Detecting money market bubbles," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 369-379.
    6. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    7. Camerer, Colin & Weigelt, Keith, 1991. "Information Mirages in Experimental Asset Markets," The Journal of Business, University of Chicago Press, vol. 64(4), pages 463-493, October.
    8. John H. Cochrane, 2002. "Stocks as Money: Convenience Yield and the Tech-Stock Bubble," NBER Working Papers 8987, National Bureau of Economic Research, Inc.
    9. Gandal, Neil & Hamrick, JT & Moore, Tyler & Oberman, Tali, 2018. "Price manipulation in the Bitcoin ecosystem," Journal of Monetary Economics, Elsevier, vol. 95(C), pages 86-96.
    10. Jiang, George J. & Knight, John L., 1997. "A Nonparametric Approach to the Estimation of Diffusion Processes, With an Application to a Short-Term Interest Rate Model," Econometric Theory, Cambridge University Press, vol. 13(5), pages 615-645, October.
    11. Flood, Robert P & Hodrick, Robert J, 1986. "Asset Price Volatility, Bubbles, and Process Switching," Journal of Finance, American Finance Association, vol. 41(4), pages 831-842, September.
    12. Robert Jarrow & Younes Kchia & Philip Protter, 2011. "Is there a bubble in LinkedIn's stock price?," Papers 1105.5717, arXiv.org.
    13. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    14. Su, Chi-Wei & Li, Zheng-Zheng & Tao, Ran & Si, Deng-Kui, 2018. "Testing for multiple bubbles in bitcoin markets: A generalized sup ADF test," Japan and the World Economy, Elsevier, vol. 46(C), pages 56-63.
    15. Leif Andersen & Vladimir Piterbarg, 2007. "Moment explosions in stochastic volatility models," Finance and Stochastics, Springer, vol. 11(1), pages 29-50, January.
    16. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Historical Episodes Of Exuberance And Collapse In The S&P 500," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 1043-1078, November.
    17. Camerer, Colin, 1989. "Bubbles and Fads in Asset Prices," Journal of Economic Surveys, Wiley Blackwell, vol. 3(1), pages 3-41.
    18. 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.
    19. 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.
    20. Smith, Vernon L & Suchanek, Gerry L & Williams, Arlington W, 1988. "Bubbles, Crashes, and Endogenous Expectations in Experimental Spot Asset Markets," Econometrica, Econometric Society, vol. 56(5), pages 1119-1151, September.
    21. Adrian (Wai-Kong) Cheung & Eduardo Roca & Jen-Je Su, 2015. "Crypto-currency bubbles: an application of the Phillips-Shi-Yu (2013) methodology on Mt. Gox bitcoin prices," Applied Economics, Taylor & Francis Journals, vol. 47(23), pages 2348-2358, May.
    22. Clifford M. Hurvich & Jeffrey S. Simonoff & Chih‐Ling Tsai, 1998. "Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 271-293.
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    More about this item

    Keywords

    Bitcoin; Cryptocurrencies; Financial bubbles; Strict local martingales;
    All these keywords.

    JEL classification:

    • G19 - Financial Economics - - General Financial Markets - - - Other

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