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Vine copula-based dependence and portfolio value-at-risk analysis of the cryptocurrency market

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  • Boako, Gideon
  • Tiwari, Aviral Kumar
  • Roubaud, David

Abstract

In this paper, we use vine copula approaches to model the co-dependence and portfolio value-at-risk (VaR) of six cryptocurrencies using data of daily periodicity from September 2015 to June 2018. We establish evidence of strong dependencies among the virtual currencies with a dynamic dependency structure. We find that among the class of cryptocurrencies examined, Ethereum offers the best optimal and economically risk-reward trade-off subject to a no-shorting constraint for portfolio investors using the efficient frontier. Given the paucity of empirical research on the cryptocurrency markets, this paper provides new insights, which could be useful in developing dependence and risk strategies for investment and hedging purposes, especially during more volatile periods in the markets.

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  • Boako, Gideon & Tiwari, Aviral Kumar & Roubaud, David, 2019. "Vine copula-based dependence and portfolio value-at-risk analysis of the cryptocurrency market," International Economics, Elsevier, vol. 158(C), pages 77-90.
    • Handle: RePEc:eee:inteco:v:158:y:2019:i:c:p:77-90
    DOI: 10.1016/j.inteco.2019.03.002
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    Cited by:

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    2. Garcia-Jorcano, Laura & Benito, Sonia, 2020. "Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying," Research in International Business and Finance, Elsevier, vol. 54(C).
    3. Bouri, Elie & Vo, Xuan Vinh & Saeed, Tareq, 2021. "Return equicorrelation in the cryptocurrency market: Analysis and determinants," Finance Research Letters, Elsevier, vol. 38(C).
    4. Syuhada, Khreshna & Hakim, Arief & Suprijanto, Djoko & Muchtadi-Alamsyah, Intan & Arbi, Lukman, 2022. "Is Tether a safe haven of safe haven amid COVID-19? An assessment against Bitcoin and oil using improved measures of risk," Resources Policy, Elsevier, vol. 79(C).
    5. Vahidin Jeleskovic & Mirko Meloni & Zahid Irshad Younas, 2020. "Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations," MAGKS Papers on Economics 202034, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Abid, Ilyes & Bouri, Elie & Galariotis, Emilios & Guesmi, Khaled & Mzoughi, Hela, 2023. "Bitcoin vs. fiat currencies: Insights from extreme dependence and risk spillover analysis with financial markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    7. Osman, Myriam Ben & Galariotis, Emilios & Guesmi, Khaled & Hamdi, Haykel & Naoui, Kamel, 2023. "Diversification in financial and crypto markets," International Review of Financial Analysis, Elsevier, vol. 89(C).
    8. Caporale, Guglielmo Maria & Kang, Woo-Young & Spagnolo, Fabio & Spagnolo, Nicola, 2021. "Cyber-attacks, spillovers and contagion in the cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    9. Chemkha, Rahma & BenSaïda, Ahmed & Ghorbel, Ahmed, 2021. "Connectedness between cryptocurrencies and foreign exchange markets: Implication for risk management," Journal of Multinational Financial Management, Elsevier, vol. 59(C).
    10. Zhao, Junming & Zhang, Tianding, 2023. "Exploring the time-varying dependence between Bitcoin and the global stock market: Evidence from a TVP-VAR approach," Finance Research Letters, Elsevier, vol. 58(PA).
    11. Jie Cheng, 2023. "Modelling and forecasting risk dependence and portfolio VaR for cryptocurrencies," Empirical Economics, Springer, vol. 65(2), pages 899-924, August.
    12. Díaz, Antonio & Esparcia, Carlos & Huélamo, Diego, 2023. "Stablecoins as a tool to mitigate the downside risk of cryptocurrency portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    13. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.

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    More about this item

    Keywords

    Cryptocurrency; Vine copula; Dependence; Value-at-risk;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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