The Portfolio Management Properties of Bitcoin During the Coronavirus Crisis

Document Type : Review article

Authors

1 Department of Finance and Accounting Methods, Institute of Higher Commercial Studies of Sfax (IHEC), University of Sfax, Sidi Mansour-sfax

2 Department of Quantitative Methods, Faculty of Economics and Management Mahdia-Tunisia, University of Monastir Sidi Messaoud - Mahdia

10.22059/ijms.2024.375551.676692

Abstract

This study raises concerns about the potential of Bitcoin as a new alternative investment. This article aims to analyze the properties of Bitcoin in terms of speculation, diversification, hedging, safe haven, and it is qualified as efficient in a well-diversified portfolio during the COVID-19 epidemic using the GARCH model, the DCC model -GARCH, and the BDS test for the period from March 1, 2019 to March 31, 2022. The results indicate that Bitcoin can play an important role in portfolio diversification and that it can serve as a speculative asset. However, the authors argue that Bitcoin is a safe haven, a hedge, and is efficient. The conclusions of our results have important implications for investors and market participants who are deeply concerned about investment strategies and risk management.

Keywords

Main Subjects


Abdelmalek, W. (2024). Cryptocurrencies and portfolio diversification before and during COVID-19. EuroMed Journal of Business, 19(4), 1084-1120. https://doi.org/10.1108/EMJB-10-2022-0182
 Al-Yahyaee, K. H.,  Mensi, W.,  Ko, H.U.,  Yoon, S.M.,  Kang, S.H, 2020. "Why cryptocurrency markets are inefficient: The impact of liquidity and volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52, .DOI: 10.1016/j.najef.2020.101168.
Baek, C. and  Elbeck M. (2015). Bitcoins as an investment or speculative vehicle? A first look. Applied Economics Letters, 2015, vol. 22, issue 1, 30-34. DOI: 10.1080/13504851.2014.916379.
Balcilar, M., Bouri, E., Gupta, R. and Roubaud, D. (2017). Can volume predict Bitcoin returns and volatility? A quantiles-based approach. Economic Modelling, 64, 74-81. https://doi.org/10.1016/j.econmod.2017.03.019.
Baur, D. G., & Lucey, B. M. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. The Financial Review, 45(2), 217-229. https://doi.org/10.1111/j.1540-6288.2010.00244.x.
Baur, D. G., Lee, A. D., & Hong, K. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions & Money, 54(c), 177–189. http://dx.doi.org/10.1016/j.intfin.2017.12.004
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. https://doi.org/10.1016/0304-4076(86)90063-1.
Bouri, E., Azzi, G., & Dyhrberg, A. H. (2017). On the return-volatility relationship in the Bitcoin market around the price crash of 2013. Open Access Open Assess E-Journal of Economics, 11(2), 1-16. DOI: 10.5018/economics-ejournal.ja.2017-2
Brauneis, A., Mestel, R., Riordan, R., & Theissen, E. (2022). Bitcoin unchained: Determinants of cryptocurrency exchange liquidity. Journal of Empirical Finance, 69, 106-122. https://doi.org/10.1016/j.jempfin.2022.08.004.
Brière, M., Oosterlinck, K., & Szafarz, A. (2015). Virtual currency, tangible return: Portfolio diversification with Bitcoin. Journal of Asset Management, 16(6), 365–373. http://dx.doi.org/10.2139/ssrn.2324780
Broock, W. A., Scheinkman, J. A., Dechert, W. D., & LeBaron, B. (1996). A test for independence based on the correlation dimension. Econometric reviews, 15(3), 197-235 . https://doi.org/10.1080/07474939608800353.
Carpenter, A. (2016). Portfolio diversification with Bitcoin. Journal of Undergraduate Research in Finance, 6(1), 1-27. https://jurf.org/wp-content/uploads/2017/01/carpenter-andrew-2016.pdf
Chan, N. H., Yau, C. Y., & Zhang, R.-M. (2014). Group LASSO for structural break time series. Journal of the American Statistical Association, 109(506), 590–599. https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F01621459.2013.866566;h=repec:taf:jnlasa:v:109:y:2014:i:506:p:590-599.
Charfeddine, L., Benlagha, N., Maouchi, Y. (2020).Investigating the dynamic relationship between cryptocurren-cies and conventional assets: implications for financial investors. Econ. Model. 85, 198–217 https://doi.org/10.1016/j.econmod.2019.05.016.
Cheah, E.-T., & Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters, 130, 32–36. http://dx.doi.org/10.1016/j.econlet.2015.02.029
Cheung, A.-K., Roca, E., & Su, J.-J. (2015). Crypto-currency bubbles: an application of the Phillips-ShiYu (2013) methodology on Mt. Gox bitcoin prices. Applied Economics, 47(23), 2348-2358. doi:https://doi.org/10.1080/00036846.2015.1005827.
Conlon, T., & McGee, R. (2020). Safe haven or risky hazard? Bitcoin during the COVID-19 bear market. Finance Research Letters, 35, 101607. http://dx.doi.org/10.2139/ssrn.3560361
Corbet, S., Lucey, B., Urquhart, A., & Yarovaya, L. (2019). Cryptocurrencies as a financial asset: A systematic analysis. International Review of Financial Analysis, 62, 182–199. https://doi.org/10.1016/j.irfa.2018.09.003
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427–431. https://doi.org/10.2307/2286348.
Dyhrberg, A. H. (2016). Bitcoin, or et dollar - une analyse de volatilité GARCH. Finance Research Letters, 16(2), 85–92. http://dx.doi.org/10.1016/j.frl.2015.10.008
Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339–350. https://www.jstor.org/stable/1392121.
Engle, R.F., (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica, 50(4), 987-1007. https://doi.org/10.2307/1912773.
Glaser, F., Zimmermann, K., Haferkorn, M., Weber, M. C., & Siering, M. (2014). Bitcoin-asset or currency? revealing users' hidden intentions. Revealing Users' Hidden Intentions (April 15, 2014). ECIS. https://ssrn.com/abstract=2425247
Gronwald, M. (2014). The Economics of Bitcoins-Market characteristics and price jumps (No. 5121). CESifo Group Munich. Working Paper Series No. 5121, Available at SSRN: https://ssrn.com/abstract=2548999 or http://dx.doi.org/10.2139/ssrn.2548999
Guesmi, K., Saadi, S., Abid, I., & Ftiti, Z. (2019). Portfolio diversification with virtual currency: Evidence from Bitcoin. International Review of Financial Analysis, 63, 431–437. DOI: 10.1016/j.irfa.2018.03.004.
Kajtazi, A., & Moro, A. (2019). The role of Bitcoin in well-diversified portfolios: A comparative global study. International Review of Financial Analysis, 61, 143–157. http://dx.doi.org/10.1016/j.irfa.2018.10.003
Katsiampa, P. (2017). Volatility estimation for Bitcoin: A comparison of GARCH models. Economics Letters, 158, 3–6. https://doi.org/10.1016/j.econlet.2017.06.023.
Katsiampa, P., Corbet, S., & Lucey, B. (2019). High frequency volatility co-movements in cryptocurrency markets. Journal of International Financial Markets, Institutions and Money, 62, 35–52.  DOI: 10.1016/j.intfin.2019.05.003.
Kliber, A., Marszałek, P., Musiałkowska, I., & Świerczyńska, K. (2019). Bitcoin: Safe haven, hedge or diversifier? Perception of bitcoin in the context of a country’s economic situation—A stochastic volatility approach. Physica A: Statistical Mechanics and Its Applications, 524, 246-257. DOI: 10.1016/j.physa.2019.04.145.
Kristoufek, L., (2015). “What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis”. In: PloS one 10.4, e0123923. DOI: 10.1371/journal.pone.0123923.
Kyriazis, N. A. (2019). Une enquête sur les résultats empiriques sur les retombées sur les marchés de la crypto-monnaie. Journal of Risk and Financial Management, 12(4), 170.
Loukil, S., Aloui, M., Jeribi, A., & Jarboui, A. (2021). Are digital assets backstops for GCC stock markets in COVID-19-led financial crisis? International Journal of Electronic Finance, 10(4), 232–259. DOI: 10.1504/IJEF.2021.10043433
Makarov, I., & Schoar, A. (2020). Trading et arbitrage sur les marchés des crypto-monnaies. Journal of Finance and Economics, 135(2), 293–319. 10.1016/j.jfineco.2019.07.001.
Mgadmi, N., Moussa, W., Mohammedi, W., Abidi, A., & Wahada, M. (2024). The impact of social media on the cryptocurrency markets during the COVID-19 pandemic and the Russia-Ukraine conflict. Knowledge and Information Systems. 1-18. https://doi.org/10.1007/s10115-024-02236-x
Nadarajah, S., & Chu, J. (2017). Sur l'inefficacité du Bitcoin. Economics Letters, 150(c), 6–9. https://doi.org/10.1016/j.econlet.2016.10.033
Naeem, M. A., Mbarki, I., Alharthi, M., Omri, A., & Shahzad, S. J. H. (2021). Did COVID19 Impact the Connectedness Between Green Bonds and Other Financial Markets? Evidence From Time-Frequency Domain With Portfolio Implications. Frontiers in Environmental Science, 9, 180. https://doi.org/10.3389/fenvs.2021.657533.
Nan, Z., and  Kaizoji, T. (2019). Market efficiency of the Bitcoin exchange rate: Weak and semi-strong form tests with the spot, futures and forward foreign exchange rates. International Review of Financial Analysis, 64, 273-281. https://doi.org/10.1016/j.irfa.2019.06.003.
Ngene, G., Post, J., & Mungai, A. (2018). Volatility and shock interactions and risk management implications: Evidence from the US and frontier markets. Emerging Markets Review, 37, 181–198. https://doi.org/10.1016/j.ememar.2018.09.001.
Pavković, A., Andelinović, M., & Pavković, I. (2019). Achieving Portfolio Diversification through Cryptocurrencies in European Markets. Business Systems Research, 10(2). https://doi.org/10.2478/bsrj-2019-020.
Selmi, R., Mensi, W., Hammoudeh, S., & Bouoiyour, J. (2018). Is Bitcoin a hedge, a safe haven or a diversifier for oil price movements? A comparison with gold. Energy Economics, 74, 787-801.  10.1016/j.eneco.2018.07.007.
Sensoy, A. (2019). L'inefficacité du Bitcoin revisitée: Une analyse à haute fréquence avec les monnaies alternatives. Finance Research Letters, 28(c), 68–73. DOI: 10.1016/j.frl.2018.04.002.
Symitsi, E., & Chalvatzis, K. J. (2019). The economic value of Bitcoin: A portfolio analysis of currencies, gold, oil, and stocks. Research in International Business and Finance, 48, 97–110. http://dx.doi.org/10.2139/ssrn.3127534
Tiwari, A. K., Jana, R. K., Das, D., & Roubaud, D. (2018). Efficacité informationnelle de Bitcoin - une extension. Economics Letters, 163, 106–109. 10.1016/j.econlet.2017.12.006.
Tse., Y. K., and  Tsui., K.C. (2002). A multivariate generalized autoregressive conditional heteroscedasticity model with time-varying correlations. Journal of Business and Economic Statistics, 20, 351–362. 10.1198/073500102288618496.
  Urquhart, A. (2016). The inefficiency of Bitcoin. Economics Letters, 148, 80-82. https://doi.org/10.1016/j.econlet.2016.09.019.
Wang, G.-J., Xie, C., Wen, D., & Zhao, L. (2018). When Bitcoin meets economic policy uncertainty (EPU): Measuring risk spillover effect from EPU to Bitcoin. Finance Research Letters. https://doi.org/10.1016/j.frl.2018.12.028.
Wei, W. C. (2018). Liquidity and market efficiency in cryptocurrencies. Economics Letters, 168, 21–24. https://doi.org/10.1016/j.econlet.2018.0 4.003.
Williamson, S. (2018). Is Bitcoin a Waste of Resources? Rev. Federal Reserve Bank St.Louis 100: 107–15. https://doi.org/10.20955/r.2018.107-15.
Yermack, D. (2015). Is Bitcoin a real currency? An economic appraisal. In D. L. K. Chuen & S. Diego (Eds.), Handbook of digital currency (pp. 31–43). Academic Press. https://doi.org/10.1016/B978-0-12-802117-0.00002-3.
Yi, S., Xu, Z. and Wang, G.J. (2018) .Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?’, International Review of Financial Analysis, Vol. 60, pp.98-114. https://doi.org/10.1016/j.irfa.2018.08.012.
Zhang, W., & Li, Y. 2023. Liquidity risk and expected crypto returns. International Journal of Finance & Economics, 28(1), 472-492. DOI: 10.1002/ijfe.2431.
Zhu, Y., Dickinson, D., & Li, J. (2017). Analysis on the influence factors of Bitcoin’s price based on VEC model. Financial Innovation, 3(1), 1–13. https:// doi. org/ 10. 1186/ s40854- 017- 0054-0