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Portfolio management and dependence structure between cryptocurrencies and traditional assets: evidence from FIEGARCH-EVT-Copula

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Abstract

The purpose of this paper is twofold. Firstly, it discusses the relationship between five cryptocurrencies, oil prices, and US indices. Secondly, it focuses on determining the best portfolio hedging strategy. Using daily data relevant to the period ranging from January 4, 2016, to November 29, 2019, this study applies the FIEGARCH-EVT-Copula and Hedge ratios analysis. The findings obtained have shown that the crude oil (WTI) and the US indices return highlights the persistence of a negative and significant leverage effect while the cryptocurrency markets present a positive asymmetric volatility effect. Moreover, this paper show evidence of very weak dependence between all the different pairs considered before and after the introduction of Bitcoin Futures. Based on the Hedging ratio and mean-variance approach, this article suggests that to minimize the risk while keeping the same expected returns of the digital-conventional financial asset portfolio, the investor should hold more conventional financial assets than digital assets except for WTI-Bitcoin, WTI- Dash and WTI-Ethereum pairs which the values of their hedge ratios are rather important with respect to OLS regression.

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Notes

  1. Although CBOE opened a futures market on December 10, trading volume was too small until the CME launched Bitcoin futures (Hale et al. 2018) on December 18, 2017, so we choose December 18, 2017, as the day when Bitcoin futures were introduced.

References

  • AslanidisBarivieraMartínez-Iban˜ez, N.A.F.O. 2019. An analysis of cryptocurrencies conditional cross correlations. Finance Research Letters 31: 130–137.

    Article  Google Scholar 

  • Avramov, D., T. Chordia, and A. Goyal. 2006. The impact of trades on daily volatility. Review of Financial Studies 19: 1241–1277.

    Article  Google Scholar 

  • Baur, D. G., Dimpfl T., 2018. Asymmetric volatility in crypto-currencies, Economic letters, 1–15.

  • Bollerslev, T., and H.O. Mikkelsen. 1996. Modeling and pricing long memory in stock market volatility. Journal of Econometrics 73: 151–184.

    Article  Google Scholar 

  • Bouoiyour, J., Selmi, R., 2015. Bitcoin price: Is it really that new round of volatility can be on way? Munich Pers. RePEc Arch. 65580 (August).

  • Bouoiyour, J., and R. Selmi. 2016. Bitcoin: A beginning of a new phase?. Econmics Bulletin 36 (3): 1430–1440.

    Google Scholar 

  • Bouri, E., G. Azzi, and A.H. Dyhrberg. 2017. On the return-volatility relationship in the Bitcoin market around the price crash of 2013. Economics. 11 (2): 1–16.

    Google Scholar 

  • Brière, M., K. Oosterlinck, and A. Szafarz. 2015. Virtual Currency Tangible Return: Portfolio Diversification with Bitcoin. Journal of Asset Management 16 (6): 365–373.

    Article  Google Scholar 

  • Chang, C.-L., M. McAleer, and R. Tansuchat. 2011. Crude oil hedging strategies using dynamic multivariate GARCH. Energy Econ. 33: 912–923.

    Article  Google Scholar 

  • Charfeddine, L., N. Benlagha, and Y. Maouchi. 2020. Investigating the dynamic relationship between cryptocurrencies and conventional assets: Implications for financial investors. Economic Modelling 85: 198–217.

    Article  Google Scholar 

  • Choi, J.-E., Shin, D.W., 2018. Quantile forecasts for financial volatilities based on parametric and asymmetric models, Journal of the Korean Statistical Society, 1–16.

  • Corbet, S., B.M. Lucey, M. Peat, and S. Vigne. 2018a. a. Bitcoin futures - what use are they?. Economic Letters 172: 23–27.

    Article  Google Scholar 

  • Corbet, S., A. Meegan, C. Larkin, B. Lucey, and L. Yarovaya. 2018b. b. Exploring the dynamic relationships between cryptocurrencies and other financial assets. Economic Letters 165: 28–34.

    Article  Google Scholar 

  • Corbet, S., B. Lucey, A. Urquhart, and L. Yarovaya. 2019. Cryptocurrencies as a financial asset: A systematic analysis. International Review of Financial Analysis 62: 182–199.

    Article  Google Scholar 

  • Dorfleitner, G., and C. Lung. 2018. Cryptocurrencies from the perspective of euro investors: a reexamination of diversification benefits and a new day-of-the-week effect. Journal of Asset Management 19: 472–494.

    Article  Google Scholar 

  • Dyhrberg, A.H. 2016. Hedging capabilities of Bitcoin. Is it the virtual gold?. Finance Research Letters 16: 139–144.

    Article  Google Scholar 

  • Fakhfekh, M., N. Hachicha, F. Jawadi, N. Selmi, and Cheffou A. Idi. 2016. Measuring volatility persistence for conventional and Islamic banks : An FI-EGARCH Approach. Emerging Market Review 27: 84–99.

    Article  Google Scholar 

  • Fakhfekh, M., and A. Jeribi. 2020. Volatility dynamics of crypto-currencies returns: Evidence from asymmetric and long memory GARCH models. Research in International Business and Finance. 54: 2–8.

    Google Scholar 

  • Gajardo, G., W.D. Kristjanpoller, and M. Minutolo. 2018. Does Bitcoin exhibit the same asymmetric multifractal cross-correlations with crude oil, gold and DJIA as the Euro, Great British Pound and Yen?. Chaos, Solitons & Fractals 109: 195–205.

    Article  Google Scholar 

  • Ghorbel, A., and A. Trabelsi. 2014. Energy portfolio risk management using time-varying extreme value copula methods. Economic Modelling 38: 470–485.

    Article  Google Scholar 

  • Guesmi, K., S. Saadi, I. Abid, and Z. Ftiti. 2019. Portfolio diversification with virtual currency: evidence from bitcoin. International Review of Financial Analysis 63: 431–437.

    Article  Google Scholar 

  • Hale, G., A. Krishnamurthy, M. Kudlyak, and P. Shultz. 2018. How future trading changed Bitcoin prices. FRBSF Economic Letter. 2018-12. https://www.frbsf.org/economic-research/publications/economicletter/2018/may/how-futures-trading-changed-bitcoin-prices/.

  • Jeribi, A., M. Fakhfekh, and A. Jarboui. 2015. Tunisian Revolution and stock market volatility: evidence from FIEGARCH model. Managerial Finance 41: 1112–1135.

    Article  Google Scholar 

  • Kajtazi, A., and A. Moro. 2019. The role of bitcoin in well diversified portfolios: a comparative global study. International Review of Financial Analysis 61: 143–157.

    Article  Google Scholar 

  • Katsiampa, P., S. Corbet, and B. Lucey. 2019. Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis. Finance Research Letters 29: 68–74.

    Article  Google Scholar 

  • Kim, W., Lee, J., Kang, K. (2019). The effects of the introduction of Bitcoin futures on the volatility of Bitcoin returns. Finance Research Letters (in Press)

  • Klein, T., H. Pham Thu, and T. Walther. 2018. Bitcoin is not the New Gold a comparison of volatility, correlation, and portfolio performance. International Review of Financial Analysis 59: 105–116.

    Article  Google Scholar 

  • Kristoufek, L. 2014. Leverage effect in energy futures. Energy Economics 45: 1–9.

    Article  Google Scholar 

  • Kroner, K.F., and J. Sultan. 1993. Time dynamic varying distributions and dynamic hedging with foreign currency futures. Journal of Financial and Quantitative Analysis 28: 535–551.

    Article  Google Scholar 

  • Ku, Y.H., H.C. Chen, and K.H. Chen. 2007. On the application of the dynamic conditional correlation model in estimating optimal time-varying hedge ratios. Applied Economics Letters 14: 503–509.

    Article  Google Scholar 

  • Ruozhou, L., W. Shanfeng, Z. Zili, and Z. Xuejun. 2020. Is the introduction of future responsible for the crash of Bitcoin? Finance Research Letters 34: 101259.

    Article  Google Scholar 

  • Sklar, A. 1959. Fonctions de répartition à n-dimensions et leurs marges. Publ. Inst. Stat. Univ. Paris 8 (1959): 229–231.

    Google Scholar 

  • Stavroyiannis, S., and V. Babalos. 2017. Dynamic properties of the Bitcoin and the US market. https://ssrn.com/abstract=2966998. Accessed 11 May 2017.

  • Symitsi, E., and K.J. Chalvatzis. 2019. The economic value of Bitcoin: A portfolio analysis of currencies, gold, oil and stocks. Research in International Business and Finance 48: 97–110.

    Article  Google Scholar 

  • Tiwari, A.K., A.O. Adewuyi, C.T. Albulescu, and M.E. Wohar. 2020. Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies. North American Journal of Economics and Finance 51: 101083.

    Article  Google Scholar 

  • Yaya, O.S., A.E. Ogbonna, O.E. Olubusoye. 2019. How persistent and dynamic inter dependent are pricing of Bitcoin to other cryptocurrencies before and after 2017/18 crash? Physica A. 531: 121732.

    Article  Google Scholar 

  • Yermack, D. 2015. Is bitcoin a real currency? an economic appraisal. In Handbook of Digital Currency, 31–43. Elsevier.

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Correspondence to Ahmed Jeribi.

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Jeribi, A., Fakhfekh, M. Portfolio management and dependence structure between cryptocurrencies and traditional assets: evidence from FIEGARCH-EVT-Copula. J Asset Manag 22, 224–239 (2021). https://doi.org/10.1057/s41260-021-00211-7

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