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Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios

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  • Antonakakis, Nikolaos
  • Chatziantoniou, Ioannis
  • Gabauer, David

Abstract

In this study, we employ a TVP-FAVAR connectedness approach in order to investigate the transmission mechanism in the cryptocurrency market. To this end, we concentrate on the top 9 cryptocurrencies by virtue of market capitalization and one market factor – based on 45 additional digital currencies – capturing the co-movements in the cryptocurrency market. The period of study spans between August 7, 2015 and May 31, 2018. We find that the dynamic total connectedness across several cryptocurrencies exhibits large dynamic variability ranging between 25% and 75%. In particular, periods of high (low) market uncertainty correspond to strong (weak) connectedness. We show that these results could be explained on the basis of increased market uncertainty that is associated with periods of highly volatile prices. In addition, despite the fact that Bitcoin still influences the cryptocurrency market substantially, we note that, recently, Ethereum has become the number one net transmitting cryptocurrency. We further note that the market gradually becomes more complex considering our connectedness approach and that this might be attributed to the unique characteristics and possibilities inherent in the technology of each cryptocurrency. A simplified application concentrating on bivariate portfolios is indicative of potential hedging opportunities using dynamic hedge ratios and dynamic portfolio weights.

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  • Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Gabauer, David, 2019. "Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 37-51.
  • Handle: RePEc:eee:intfin:v:61:y:2019:i:c:p:37-51
    DOI: 10.1016/j.intfin.2019.02.003
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    Cited by:

    1. Peng Xie & Jiming Wu & Hongwei Du, 2019. "The relative importance of competition to contagion: evidence from the digital currency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-19, December.
    2. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    3. Deqing Wang & Yinqiu Song & Hongyan Zhang & Shengjie Pan, 2020. "The Effectiveness of Chinas Monetary Policy: Based on the Mixed-Frequency Data," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 10(3), pages 325-339, March.
    4. Natália Costa & César Silva & Paulo Ferreira, 2019. "Long-Range Behaviour and Correlation in DFA and DCCA Analysis of Cryptocurrencies," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 7(3), pages 1-12, September.
    5. Miglo, Anton, 2020. "Choice Between IEO and ICO: Speed vs. Liquidity vs. Risk," MPRA Paper 99600, University Library of Munich, Germany.
    6. Elie Bouri & Oguzhan Cepni & David Gabauer & Rangan Gupta, 2020. "Return Connectedness across Asset Classes around the COVID-19 Outbreak," Working Papers 202047, University of Pretoria, Department of Economics.
    7. Yue-Jun Zhang & Elie Bouri & Shu-Jiao Ma & Rangan Gupta, 2020. "Risk Spillover between Bitcoin and Conventional Financial Markets: An Expectile-Based Approach," Working Papers 202027, University of Pretoria, Department of Economics.
    8. Andrada-Félix, Julián & Fernandez-Perez, Adrian & Sosvilla-Rivero, Simón, 2020. "Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    9. Paulo Ferreira & Éder Pereira, 2019. "Contagion Effect in Cryptocurrency Market," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(3), pages 1-8, July.
    10. Ferreira, Paulo & Kristoufek, Ladislav & Pereira, Eder Johnson de Area Leão, 2020. "DCCA and DMCA correlations of cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    11. Guglielmo Maria Caporale & Woo-Young Kang & Fabio Spagnolo & Nicola Spagnolo, 2020. "Cyber Attacks, Spillovers and Contagion in the Cryptocurrency Markets," CESifo Working Paper Series 8324, CESifo.
    12. Paolo Giudici & Paolo Pagnottoni, 2019. "High Frequency Price Change Spillovers in Bitcoin Markets," Risks, MDPI, Open Access Journal, vol. 7(4), pages 1-18, November.
    13. Elie Bouri & David Gabauer & Rangan Gupta & Aviral Kumar Tiwari, 2020. "Volatility Connectedness of Major Cryptocurrencies: The Role of Investor Happiness," Working Papers 202059, University of Pretoria, Department of Economics.
    14. Ioannis Chatziantoniou & David Gabauer & Alexis Stenfors, 2019. "From CIP-Deviations to a Market for Risk Premia: A Dynamic Investigation of Cross-Currency Basis Swaps," Working Papers in Economics & Finance 2019-05, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    15. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 13(4), pages 1-23, April.
    16. Lee Alan Smales, 2020. "One Cryptocurrency to Explain Them All? Understanding the Importance of Bitcoin in Cryptocurrency Returns," Economic Papers, The Economic Society of Australia, vol. 39(2), pages 118-132, June.

    More about this item

    Keywords

    Cryptocurrencies; Connectedness; Contagion; TVP-FAVAR;

    JEL classification:

    • 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
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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