IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v77y2022ics0301420722001301.html
   My bibliography  Save this article

On the relationship between Bitcoin and other assets during the outbreak of coronavirus: Evidence from fractional cointegration analysis

Author

Listed:
  • Bejaoui, Azza
  • Mgadmi, Nidhal
  • Moussa, Wajdi

Abstract

This article tries to investigate the connectedness between Bitcoin and Crude Oil, S&P500 and Natural Gas with the health crisis. That is why one might apply fractional cointegration analysis on daily data over the period 01/09/2019–30/04/2020. Our results indicate the presence of fractional integration in residual series, implying the existence of a fractional cointegration relationship. A short-run joint dynamics between Bitcoin and some other assets (Crude Oil, S&P500 and Natural Gas) is nevertheless well-pronounced. Such analysis of the long and short-term dependencies between different assets could be interesting from a portfolio perspective.

Suggested Citation

  • Bejaoui, Azza & Mgadmi, Nidhal & Moussa, Wajdi, 2022. "On the relationship between Bitcoin and other assets during the outbreak of coronavirus: Evidence from fractional cointegration analysis," Resources Policy, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:jrpoli:v:77:y:2022:i:c:s0301420722001301
    DOI: 10.1016/j.resourpol.2022.102682
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420722001301
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2022.102682?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. Carola Binder, 2020. "Coronavirus Fears and Macroeconomic Expectations," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 721-730, October.
    2. Stefano Ramelli & Alexander F Wagner, 2020. "Feverish Stock Price Reactions to COVID-19," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 9(3), pages 622-655.
    3. James, Nick & Menzies, Max & Chan, Jennifer, 2021. "Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    4. Niels Joachim Gormsen & Ralph S J Koijen & Nikolai Roussanov, 0. "Coronavirus: Impact on Stock Prices and Growth Expectations," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(4), pages 574-597.
    5. Arouxet, M. Belén & Bariviera, Aurelio F. & Pastor, Verónica E. & Vampa, Victoria, 2022. "Covid-19 impact on cryptocurrencies: Evidence from a wavelet-based Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    6. Jareño, Francisco & González, María de la O. & López, Raquel & Ramos, Ana Rosa, 2021. "Cryptocurrencies and oil price shocks: A NARDL analysis in the COVID-19 pandemic," Resources Policy, Elsevier, vol. 74(C).
    7. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    8. Yang, Yang & Zhang, Hongru & Chen, Xiang, 2020. "Coronavirus pandemic and tourism: Dynamic stochastic general equilibrium modeling of infectious disease outbreak," Annals of Tourism Research, Elsevier, vol. 83(C).
    9. Sandrine Lardic & Valérie Mignon, 2004. "Fractional cointegration and the term structure," Empirical Economics, Springer, vol. 29(4), pages 723-736, December.
    10. John Geweke & Susan Porter‐Hudak, 1983. "The Estimation And Application Of Long Memory Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 221-238, July.
    11. Iqbal, Najaf & Fareed, Zeeshan & Wan, Guangcai & Shahzad, Farrukh, 2021. "Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 73(C).
    12. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    13. Jamal Bouoiyour & Refk Selmi, 2017. "The Bitcoin price formation: Beyond the fundamental sources," Working Papers hal-01548710, HAL.
    14. Goodell, John W. & Goutte, Stephane, 2021. "Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 38(C).
    15. Bhuiyan, Rubaiyat Ahsan & Husain, Afzol & Zhang, Changyong, 2021. "A wavelet approach for causal relationship between bitcoin and conventional asset classes," Resources Policy, Elsevier, vol. 71(C).
    16. Claudiu Albulescu, 2020. "Coronavirus and financial volatility: 40 days of fasting and fear," Papers 2003.04005, arXiv.org.
    17. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Larkin, Charles & Lucey, Brian & Oxley, Les, 2022. "Cryptocurrency liquidity and volatility interrelationships during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    18. Raheem, Ibrahim D., 2021. "COVID-19 pandemic and the safe haven property of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 370-375.
    19. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
    20. Guo, Xiaochun & Lu, Fengbin & Wei, Yunjie, 2021. "Capture the contagion network of bitcoin – Evidence from pre and mid COVID-19," Research in International Business and Finance, Elsevier, vol. 58(C).
    21. Dutta, Anupam & Das, Debojyoti & Jana, R.K. & Vo, Xuan Vinh, 2020. "COVID-19 and oil market crash: Revisiting the safe haven property of gold and Bitcoin," Resources Policy, Elsevier, vol. 69(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Karimi, Parinaz & Mirzaee Ghazani, Majid & Ebrahimi, Seyed Babak, 2023. "Analyzing spillover effects of selected cryptocurrencies on gold and brent crude oil under COVID-19 pandemic: Evidence from GJR-GARCH and EVT copula methods," Resources Policy, Elsevier, vol. 85(PB).

    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. Kai Meng & Khalid Khan, 2024. "Is cryptocurrency Efficient? A High-Frequency Asymmetric Multifractality Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2225-2246, June.
    2. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.
    3. Yarovaya, Larisa & Brzeszczyński, Janusz & Goodell, John W. & Lucey, Brian & Lau, Chi Keung Marco, 2022. "Rethinking financial contagion: Information transmission mechanism during the COVID-19 pandemic," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    4. Theodoros Daglis & Ioannis G. Melissaropoulos & Konstantinos N. Konstantakis & Panayotis G. Michaelides, 2022. "The impact of COVID-19 on global stock markets: early linear and non-linear evidence for Italy," Evolutionary and Institutional Economics Review, Springer, vol. 19(1), pages 485-495, April.
    5. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "Volatility spillovers and other dynamics between cryptocurrencies and the energy and bond markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 1-13.
    6. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    7. Wajdi Moussa, 2022. "Does Analyzing the Dynamics of Digital Currencies Help to Determine the Safe-Haven Crypto-Currency during the Covid-19 Outbreak?," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 12(3), pages 58-74.
    8. Maneejuk, Paravee & Kaewtathip, Nuttaphong & Jaipong, Peemmawat & Yamaka, Woraphon, 2022. "The transition of the global financial markets' connectedness during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    9. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2005. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Trinity Economics Papers tep20021, Trinity College Dublin, Department of Economics.
    10. Ștefan Cristian Gherghina & Daniel Ștefan Armeanu & Camelia Cătălina Joldeș, 2020. "Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis," IJERPH, MDPI, vol. 17(18), pages 1-35, September.
    11. Boubaker Heni & Canarella Giorgio & Miller Stephen M. & Gupta Rangan, 2017. "Time-varying persistence of inflation: evidence from a wavelet-based approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    12. Diniz-Maganini, Natalia & Diniz, Eduardo H. & Rasheed, Abdul A., 2021. "Bitcoin’s price efficiency and safe haven properties during the COVID-19 pandemic: A comparison," Research in International Business and Finance, Elsevier, vol. 58(C).
    13. Jr‐Wei Huang & Sharon S. Yang & Chuang‐Chang Chang, 2018. "Modeling temperature behaviors: Application to weather derivative valuation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1152-1175, September.
    14. Rim Ammar Lamouchi, 2020. "Long Memory and Stock Market Efficiency: Case of Saudi Arabia," International Journal of Economics and Financial Issues, Econjournals, vol. 10(3), pages 29-34.
    15. James, Nick & Menzies, Max, 2023. "Collective infectivity of the pandemic over time and association with vaccine coverage and economic development," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    16. Hasan, Mohammad Maruf & Du, Fang, 2023. "The role of foreign trade and technology innovation on economic recovery in China: The mediating role of natural resources development," Resources Policy, Elsevier, vol. 80(C).
    17. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    18. J. Eduardo Vera‐Valdés, 2020. "On long memory origins and forecast horizons," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 811-826, August.
    19. Rasa Kanapickiene & Deimante Teresiene & Daiva Budriene & Greta Keliuotytė-Staniulėnienė & Jekaterina Kartasova, 2020. "The Impact Of Covid-19 On European Financial Markets And Economic Sentiment," Economy & Business Journal, International Scientific Publications, Bulgaria, vol. 14(1), pages 144-163.
    20. Yousaf, Imran & Yarovaya, Larisa, 2022. "Spillovers between the Islamic gold-backed cryptocurrencies and equity markets during the COVID-19: A sectorial analysis," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).

    More about this item

    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:jrpoli:v:77:y:2022:i:c:s0301420722001301. 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/inca/30467 .

    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.