IDEAS home Printed from https://ideas.repec.org/p/zbw/irtgdp/2018005.html
   My bibliography  Save this paper

Testing for bubbles in cryptocurrencies with time-varying volatility

Author

Listed:
  • Hafner, Christian M.

Abstract

The recent evolution of cryptocurrencies has been characterized by bubble-like behavior and extreme volatility. While it is difficult to assess an intrinsic value to a specific cryptocurrency, one can employ recently proposed bubble tests that rely on recursive applications of classical unit root tests. This paper extends this approach to the case where volatility is time varying, assuming a deterministic longrun component that may take into account a decrease of unconditional volatility when the cryptocurrency matures with a higher market dissemination. Volatility also includes a stochastic short-run component to capture volatility clustering. The wild bootstrap is shown to correctly adjust the size properties of the bubble test, which retains good power properties. In an empirical application using eleven of the largest cryptocurrencies and the CRIX index, the general evidence in favor of bubbles is confirmed, but much less pronounced than under constant volatility.

Suggested Citation

  • Hafner, Christian M., 2018. "Testing for bubbles in cryptocurrencies with time-varying volatility," IRTG 1792 Discussion Papers 2018-005, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  • Handle: RePEc:zbw:irtgdp:2018005
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/230716/1/irtg1792dp2018-005.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Duan, Jin-Chuan, 1997. "Augmented GARCH (p,q) process and its diffusion limit," Journal of Econometrics, Elsevier, vol. 79(1), pages 97-127, July.
    2. Nelson, Daniel B., 1990. "ARCH models as diffusion approximations," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 7-38.
    3. Peter C. B. Phillips & Yangru Wu & Jun Yu, 2011. "EXPLOSIVE BEHAVIOR IN THE 1990s NASDAQ: WHEN DID EXUBERANCE ESCALATE ASSET VALUES?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(1), pages 201-226, February.
    4. David Yermack, 2013. "Is Bitcoin a Real Currency? An economic appraisal," NBER Working Papers 19747, National Bureau of Economic Research, Inc.
    5. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Limit Theory Of Real‐Time Detectors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 1079-1134, November.
    6. Nadarajah, Saralees & Chu, Jeffrey, 2017. "On the inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 150(C), pages 6-9.
    7. Bouri, Elie & Molnár, Peter & Azzi, Georges & Roubaud, David & Hagfors, Lars Ivar, 2017. "On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?," Finance Research Letters, Elsevier, vol. 20(C), pages 192-198.
    8. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    9. 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.
    10. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    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. Eross, Andrea & McGroarty, Frank & Urquhart, Andrew & Wolfe, Simon, 2019. "The intraday dynamics of bitcoin," Research in International Business and Finance, Elsevier, vol. 49(C), pages 71-81.
    2. Symitsi, Efthymia & Chalvatzis, Konstantinos J., 2019. "The economic value of Bitcoin: A portfolio analysis of currencies, gold, oil and stocks," Research in International Business and Finance, Elsevier, vol. 48(C), pages 97-110.
    3. Christie Smith & Aaron Kumar, 2018. "Crypto‐Currencies – An Introduction To Not‐So‐Funny Moneys," Journal of Economic Surveys, Wiley Blackwell, vol. 32(5), pages 1531-1559, December.
    4. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    5. Urquhart, Andrew & Zhang, Hanxiong, 2019. "Is Bitcoin a hedge or safe haven for currencies? An intraday analysis," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 49-57.
    6. Lennart Ante, 2020. "A place next to Satoshi: foundations of blockchain and cryptocurrency research in business and economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1305-1333, August.
    7. Chen, Yan & Zhang, Lei & Bouri, Elie, 2024. "Co-Bubble transmission across clean and dirty Cryptocurrencies: Network and portfolio analysis," Journal of International Money and Finance, Elsevier, vol. 145(C).
    8. Tetsuya Takaishi, 2017. "Statistical properties and multifractality of Bitcoin," Papers 1707.07618, arXiv.org, revised May 2018.
    9. Aslanidis, Nektarios & Fernández Bariviera, Aurelio & Savva, Christos S., 2020. "Weekly dynamic conditional correlations among cryptocurrencies and traditional assets," Working Papers 2072/417680, Universitat Rovira i Virgili, Department of Economics.
    10. Merediz-Solà, Ignasi & Bariviera, Aurelio F., 2019. "A bibliometric analysis of bitcoin scientific production," Research in International Business and Finance, Elsevier, vol. 50(C), pages 294-305.
    11. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    12. Takaishi, Tetsuya, 2018. "Statistical properties and multifractality of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 507-519.
    13. Corbet, Shaen & Katsiampa, Paraskevi, 2020. "Asymmetric mean reversion of Bitcoin price returns," International Review of Financial Analysis, Elsevier, vol. 71(C).
    14. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    15. Vidal-Tomás, David & Ibañez, Ana, 2018. "Semi-strong efficiency of Bitcoin," Finance Research Letters, Elsevier, vol. 27(C), pages 259-265.
    16. Pal, Debdatta & Mitra, Subrata K., 2019. "Hedging bitcoin with other financial assets," Finance Research Letters, Elsevier, vol. 30(C), pages 30-36.
    17. Kajtazi, Anton & Moro, Andrea, 2019. "The role of bitcoin in well diversified portfolios: A comparative global study," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 143-157.
    18. Panagiotidis, Theodore & Stengos, Thanasis & Vravosinos, Orestis, 2019. "The effects of markets, uncertainty and search intensity on bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 220-242.
    19. Dyhrberg, Anne H. & Foley, Sean & Svec, Jiri, 2018. "How investible is Bitcoin? Analyzing the liquidity and transaction costs of Bitcoin markets," Economics Letters, Elsevier, vol. 171(C), pages 140-143.
    20. Qin, Meng & Su, Chi-Wei & Tao, Ran, 2021. "BitCoin: A new basket for eggs?," Economic Modelling, Elsevier, vol. 94(C), pages 896-907.

    More about this item

    Keywords

    cryptocurrencies; speculative bubbles; wild bootstrap; volatility;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature

    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:zbw:irtgdp:2018005. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/wfhubde.html .

    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.