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Bitcoin and liquidity risk diversification

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  • Ghabri, Yosra
  • Guesmi, Khaled
  • Zantour, Ahlem

Abstract

This paper investigates the potential diversification benefits of adding Bitcoin from a liquidity perspective. Using different multivariate GARCH-Type specifications to model the joint dynamics of the selected financial assets, we find that VARMA (1, 1)-cDCC-GARCH is the best-fit model. By examining the dependence structure between Bitcoin and several financial assets, we find evidence of a low time-varying correlation of liquidity innovations over the period 2014–2019. This finding suggests the existence of a potential gain in diversifying the liquidity risk using Bitcoin instead of traditional assets. The results of the portfolio optimization problem when adding the liquidity constraint show that holding Bitcoin can reduce the liquidity risk under the Mean-Variance-Liquidity framework.

Suggested Citation

  • Ghabri, Yosra & Guesmi, Khaled & Zantour, Ahlem, 2021. "Bitcoin and liquidity risk diversification," Finance Research Letters, Elsevier, vol. 40(C).
    • Handle: RePEc:eee:finlet:v:40:y:2021:i:c:s154461232030012x
    DOI: 10.1016/j.frl.2020.101679
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    Cited by:

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    2. Kong, Xiaolin & Ma, Chaoqun & Ren, Yi-Shuai & Baltas, Konstantinos & Narayan, Seema, 2024. "A comparative analysis of the price explosiveness in Bitcoin and forked coins," Finance Research Letters, Elsevier, vol. 61(C).
    3. Khalfaoui, Rabeh & Hammoudeh, Shawkat & Rehman, Mohd Ziaur, 2023. "Spillovers and connectedness among BRICS stock markets, cryptocurrencies, and uncertainty: Evidence from the quantile vector autoregression network," Emerging Markets Review, Elsevier, vol. 54(C).
    4. Fernandes, Leonardo H.S. & Bouri, Elie & Silva, José W.L. & Bejan, Lucian & de Araujo, Fernando H.A., 2022. "The resilience of cryptocurrency market efficiency to COVID-19 shock," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    5. Patel, Ritesh & Gubareva, Mariya & Chishti, Muhammad Zubair & Teplova, Tamara, 2024. "Connectedness between healthcare cryptocurrencies and major asset classes: Implications for hedging and investments strategies," International Review of Financial Analysis, Elsevier, vol. 93(C).
    6. 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).
    7. David E. Allen, 2022. "Cryptocurrencies, Diversification and the COVID-19 Pandemic," JRFM, MDPI, vol. 15(3), pages 1-25, February.
    8. Kyriazis, Nikolaos & Papadamou, Stephanos & Tzeremes, Panayiotis & Corbet, Shaen, 2023. "Can cryptocurrencies provide a viable hedging mechanism for benchmark index investors?," Research in International Business and Finance, Elsevier, vol. 64(C).
    9. Nguyen, An Pham Ngoc & Mai, Tai Tan & Bezbradica, Marija & Crane, Martin, 2023. "Volatility and returns connectedness in cryptocurrency markets: Insights from graph-based methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).

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    More about this item

    Keywords

    Bitcoin; diversification; liquidity innovations; liquidity risk; dynamic multivariate GARCH;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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