IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v38y2021ics1544612319310189.html
   My bibliography  Save this article

Economic policy uncertainty and cryptocurrency volatility

Author

Listed:
  • Yen, Kuang-Chieh
  • Cheng, Hui-Pei

Abstract

We investigate the relationship between the economic policy uncertainty index (EPU) and cryptocurrency volatility. We find that a change in EPU of China predicts cryptocurrency volatility, but a change in the EPU of the U.S., Japan, or Korea has no such effect. Moreover, changes in the China EPU are negatively associated with Bitcoin and Litecoin future volatility, which may imply that Bitcoin and Litecoin are hedging tools against the EPU risk. However, changes in China EPU may not affect the cryptocurrency volatility after the Chinese government's regulation of crypto-trading.

Suggested Citation

  • Yen, Kuang-Chieh & Cheng, Hui-Pei, 2021. "Economic policy uncertainty and cryptocurrency volatility," Finance Research Letters, Elsevier, vol. 38(C).
    • Handle: RePEc:eee:finlet:v:38:y:2021:i:c:s1544612319310189
    DOI: 10.1016/j.frl.2020.101428
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612319310189
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2020.101428?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    2. Bouri, Elie & Gupta, Rangan & Tiwari, Aviral Kumar & Roubaud, David, 2017. "Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions," Finance Research Letters, Elsevier, vol. 23(C), pages 87-95.
    3. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    4. June Ma & Joshua S. Gans & Rabee Tourky, 2018. "Market Structure in Bitcoin Mining," NBER Working Papers 24242, National Bureau of Economic Research, Inc.
    5. Yaw‐Huei Wang & Kuang‐Chieh Yen, 2019. "The information content of the implied volatility term structure on future returns," European Financial Management, European Financial Management Association, vol. 25(2), pages 380-406, March.
    6. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    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. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    2. Umar, Muhammad & Shahzad, Fakhar & Ullah, Irfan & Fanghua, Tong, 2023. "A comparative analysis of cryptocurrency returns and economic policy uncertainty pre- and post-Covid-19," Research in International Business and Finance, Elsevier, vol. 65(C).
    3. Cheng, Hui-Pei & Yen, Kuang-Chieh, 2020. "The relationship between the economic policy uncertainty and the cryptocurrency market," Finance Research Letters, Elsevier, vol. 35(C).
    4. Raza, Syed Ali & Masood, Amna & Benkraiem, Ramzi & Urom, Christian, 2023. "Forecasting the volatility of precious metals prices with global economic policy uncertainty in pre and during the COVID-19 period: Novel evidence from the GARCH-MIDAS approach," Energy Economics, Elsevier, vol. 120(C).
    5. Jiang, Yonghong & Wu, Lanxin & Tian, Gengyu & Nie, He, 2021. "Do cryptocurrencies hedge against EPU and the equity market volatility during COVID-19? – New evidence from quantile coherency analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    6. Jareño, Francisco & González, María de la O & Tolentino, Marta & Sierra, Karen, 2020. "Bitcoin and gold price returns: A quantile regression and NARDL analysis," Resources Policy, Elsevier, vol. 67(C).
    7. Zhou, Siwen, 2018. "Exploring the Driving Forces of the Bitcoin Exchange Rate Dynamics: An EGARCH Approach," MPRA Paper 89445, University Library of Munich, Germany.
    8. Elsayed, Ahmed H. & Gozgor, Giray & Yarovaya, Larisa, 2022. "Volatility and return connectedness of cryptocurrency, gold, and uncertainty: Evidence from the cryptocurrency uncertainty indices," Finance Research Letters, Elsevier, vol. 47(PB).
    9. Mokni, Khaled & Ajmi, Ahdi Noomen & Bouri, Elie & Vo, Xuan Vinh, 2020. "Economic policy uncertainty and the Bitcoin-US stock nexus," Journal of Multinational Financial Management, Elsevier, vol. 57.
    10. Kamal, Javed Bin & Hassan, M. Kabir, 2022. "Asymmetric connectedness between cryptocurrency environment attention index and green assets," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    11. Wu, Wanshan & Tiwari, Aviral Kumar & Gozgor, Giray & Leping, Huang, 2021. "Does economic policy uncertainty affect cryptocurrency markets? Evidence from Twitter-based uncertainty measures," Research in International Business and Finance, Elsevier, vol. 58(C).
    12. Rudkin, Simon & Rudkin, Wanling & Dłotko, Paweł, 2023. "On the topology of cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 89(C).
    13. Cagli, Efe Caglar & Mandaci, Pinar Evrim, 2023. "Time and frequency connectedness of uncertainties in cryptocurrency, stock, currency, energy, and precious metals markets," Emerging Markets Review, Elsevier, vol. 55(C).
    14. Al-Shboul, Mohammad & Assaf, Ata & Mokni, Khaled, 2022. "When bitcoin lost its position: Cryptocurrency uncertainty and the dynamic spillover among cryptocurrencies before and during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    15. Papadamou, Stephanos & Kyriazis, Nikolaos A. & Tzeremes, Panayiotis G., 2021. "Non-linear causal linkages of EPU and gold with major cryptocurrencies during bull and bear markets," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    16. Bouri, Elie & Gupta, Rangan, 2021. "Predicting Bitcoin returns: Comparing the roles of newspaper- and internet search-based measures of uncertainty," Finance Research Letters, Elsevier, vol. 38(C).
    17. Su, Chi-Wei & Qin, Meng & Tao, Ran & Umar, Muhammad, 2020. "Financial implications of fourth industrial revolution: Can bitcoin improve prospects of energy investment?," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    18. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
    19. Tobias Burggraf, 2020. "Bitcoin and Global Political Uncertainty – Evidence from the U.S. Election Cycle," Economics Bulletin, AccessEcon, vol. 40(1), pages 727-742.
    20. Smales, L.A., 2022. "Investor attention in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 79(C).

    More about this item

    Keywords

    Bitcoin; Cryptocurrencies; Economic policy uncertainty; China; Volatility;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    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:eee:finlet:v:38:y:2021:i:c:s1544612319310189. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.