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Are cryptocurrencies connected to forex? A quantile cross-spectral approach

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  • Baumöhl, Eduard

Abstract

This paper analyzes the connectedness between forex and cryptocurrencies using the quantile cross-spectral approach. The sample covers six forex and six cryptocurrencies over the period of September 2015–December 2017. Compared with the results obtained from standard correlations and DMCA, the quantile cross-spectral approach provides richer information on the dependence structure across different quantiles and frequencies. The results show that there are some significant negative dependencies between forex and cryptocurrencies from both the short- and long-term perspectives; thus, it is worth diversifying between these two asset groups. Moreover, the connection between cryptocurrencies is not as strong as is widely believed.

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  • Baumöhl, Eduard, 2019. "Are cryptocurrencies connected to forex? A quantile cross-spectral approach," Finance Research Letters, Elsevier, vol. 29(C), pages 363-372.
    • Handle: RePEc:eee:finlet:v:29:y:2019:i:c:p:363-372
    DOI: 10.1016/j.frl.2018.09.002
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    3. Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 119-129.
    4. Kajtazi, Anton & Moro, Andrea, 2019. "The role of bitcoin in well diversified portfolios: A comparative global study," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 143-157.
    5. Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020. "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers 2003.09723, arXiv.org.
    6. Khanh Hoang & Cuong C. Nguyen & Kongchheng Poch & Thang X. Nguyen, 2020. "Does Bitcoin Hedge Commodity Uncertainty?," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 13(6), pages 1-14, June.
    7. Umar, Zaghum & Gubareva, Mariya, 2020. "A time–frequency analysis of the impact of the Covid-19 induced panic on the volatility of currency and cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    8. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    9. Nino Antulov-Fantulin & Tian Guo & Fabrizio Lillo, 2020. "Temporal mixture ensemble models for intraday volume forecasting in cryptocurrency exchange markets," Papers 2005.09356, arXiv.org, revised Dec 2020.
    10. Aalborg, Halvor Aarhus & Molnár, Peter & de Vries, Jon Erik, 2019. "What can explain the price, volatility and trading volume of Bitcoin?," Finance Research Letters, Elsevier, vol. 29(C), pages 255-265.
    11. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    12. 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.
    13. 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).

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    More about this item

    Keywords

    Cryptocurrencies; Forex; Quantile dependence; Cross-spectral; Diversification;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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