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Bitcoin as Hedge or Safe Haven: Evidence from Stock, Currency, Bond and Derivatives Markets

Author

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  • Sang Hoon Kang

    (Pusan National University)

  • Seong-Min Yoon

    (Pusan National University)

  • Stelios Bekiros

    (Athens University of Economics and Business)

  • Gazi S. Uddin

    (Linköping University)

Abstract

It is crucial for investors to manage their investment risk. This paper examines the dynamic equicorrelation relationship between Bitcoin and four major investment assets, namely, US stock (S&P 500), US dollar, Treasury bonds and gold futures. Our empirical analysis reveals an asymmetric causality between Bitcoin and other asset classes. The results indicate that Bitcoin may be employed as an effective safe haven for investors by providing invaluable information to reduce downside risk, hence strengthening diversification benefits in optimal asset allocation and portfolio risk management.

Suggested Citation

  • Sang Hoon Kang & Seong-Min Yoon & Stelios Bekiros & Gazi S. Uddin, 2020. "Bitcoin as Hedge or Safe Haven: Evidence from Stock, Currency, Bond and Derivatives Markets," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 529-545, August.
  • Handle: RePEc:kap:compec:v:56:y:2020:i:2:d:10.1007_s10614-019-09935-6
    DOI: 10.1007/s10614-019-09935-6
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    as
    1. Reboredo, Juan C., 2013. "Is gold a safe haven or a hedge for the US dollar? Implications for risk management," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 2665-2676.
    2. A. Hatemi-J, 2003. "A new method to choose optimal lag order in stable and unstable VAR models," Applied Economics Letters, Taylor & Francis Journals, vol. 10(3), pages 135-137.
    3. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    4. Baur, Dirk G. & McDermott, Thomas K., 2010. "Is gold a safe haven? International evidence," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1886-1898, August.
    5. repec:taf:jnlbes:v:30:y:2012:i:2:p:212-228 is not listed on IDEAS
    6. Aguiar-Conraria, LuI´s & Joana Soares, Maria, 2011. "Business cycle synchronization and the Euro: A wavelet analysis," Journal of Macroeconomics, Elsevier, vol. 33(3), pages 477-489, September.
    7. Dirk G. Baur & Brian M. Lucey, 2010. "Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold," The Financial Review, Eastern Finance Association, vol. 45(2), pages 217-229, May.
    8. 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.
    9. Abdulnasser Hatemi-J, 2012. "Asymmetric causality tests with an application," Empirical Economics, Springer, vol. 43(1), pages 447-456, August.
    10. Alagidede, Paul, 2011. "Return behaviour in Africa's emerging equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(2), pages 133-140, May.
    11. Robert F. Engle & Kevin Sheppard, 2001. "Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH," NBER Working Papers 8554, National Bureau of Economic Research, Inc.
    12. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    13. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    14. Gian Piero Aielli, 2013. "Dynamic Conditional Correlation: On Properties and Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 282-299, July.
    15. Luther, William J. & Salter, Alexander W., 2017. "Bitcoin and the bailout," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 50-56.
    16. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    17. Elie Bouri & Luis A. Gil‐Alana & Rangan Gupta & David Roubaud, 2019. "Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 412-426, January.
    18. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    19. 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.
    20. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    21. Sang Hoon Kang & Ron McIver & Seong-Min Yoon, 2016. "Modeling Time-Varying Correlations in Volatility Between BRICS and Commodity Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(7), pages 1698-1723, July.
    22. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    23. Beat Weber, 2016. "Bitcoin and the legitimacy crisis of money," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 40(1), pages 17-41.
    24. Dwyer, Gerald P., 2015. "The economics of Bitcoin and similar private digital currencies," Journal of Financial Stability, Elsevier, vol. 17(C), pages 81-91.
    25. Nguyen, Duc Khuong & Sousa, Ricardo M. & Uddin, Gazi Salah, 2015. "Testing for asymmetric causality between U.S. equity returns and commodity futures returns," Finance Research Letters, Elsevier, vol. 12(C), pages 38-47.
    26. Mark, Joy, 2011. "Gold and the US dollar: Hedge or haven?," Finance Research Letters, Elsevier, vol. 8(3), pages 120-131, September.
    27. Fry, John & Cheah, Eng-Tuck, 2016. "Negative bubbles and shocks in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 343-352.
    28. Brandvold, Morten & Molnár, Peter & Vagstad, Kristian & Andreas Valstad, Ole Christian, 2015. "Price discovery on Bitcoin exchanges," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 36(C), pages 18-35.
    29. Angela ROGOJANU & Liana BADEA, 2014. "The issue of competing currencies. Case study – Bitcoin," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(590)), pages 103-114, January.
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    Cited by:

    1. Satya Prakash Yadav & Krishna Kant Agrawal & Bhoopesh Singh Bhati & Fadi Al-Turjman & Leonardo Mostarda, 2022. "Blockchain-Based Cryptocurrency Regulation: An Overview," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1659-1675, April.
    2. Xu, Lei & Kinkyo, Takuji, 2023. "Hedging effectiveness of bitcoin and gold: Evidence from G7 stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    3. 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).
    4. Lei Wang & Provash Kumer Sarker & Elie Bouri, 2023. "Short- and Long-Term Interactions Between Bitcoin and Economic Variables: Evidence from the US," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1305-1330, April.
    5. Będowska-Sójka, Barbara & Kliber, Agata, 2021. "Is there one safe-haven for various turbulences? The evidence from gold, Bitcoin and Ether," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    6. Stelios Bekiros & Axel Hedström & Evgeniia Jayasekera & Tapas Mishra & Gazi Salah Uddin, 2021. "Correlated at the Tail: Implications of Asymmetric Tail-Dependence Across Bitcoin Markets," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1289-1299, December.

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    More about this item

    Keywords

    Bitcoin; Downside risk; Portfolio management; Quantile regression;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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