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Nonlinear Autoregressive Distributed Lag Approach: An Application on the Connectedness between Bitcoin Returns and the Other Ten Most Relevant Cryptocurrency Returns

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  • María de la O González

    (Department of Economics and Finance, Faculty of Economics and Business Sciences, University of Castilla-La Mancha, Plaza de la Universidad 1, 02071 Albacete, Spain)

  • Francisco Jareño

    (Department of Economics and Finance, Faculty of Economics and Business Sciences, University of Castilla-La Mancha, Plaza de la Universidad 1, 02071 Albacete, Spain)

  • Frank S. Skinner

    (Department of Economics and Finance, Brunel University, Uxbridge, Middlesex, London UB8 3PH, UK)

Abstract

This article examines the connectedness between Bitcoin returns and returns of ten additional cryptocurrencies for several frequencies—daily, weekly, and monthly—over the period January 2015–March 2020 using a nonlinear autoregressive distributed lag (NARDL) approach. We find important and positive interdependencies among cryptocurrencies and significant long-run relationships among most of them. In addition, non-Bitcoin cryptocurrency returns seem to react in the same way to positive and negative changes in Bitcoin returns, obtaining strong evidence of asymmetry in the short run. Finally, our results show high persistence in the impact of both positive and negative changes in Bitcoin returns on most of the other cryptocurrency returns. Thus, our model explains about 50% of the other cryptocurrency returns with changes in Bitcoin returns.

Suggested Citation

  • María de la O González & Francisco Jareño & Frank S. Skinner, 2020. "Nonlinear Autoregressive Distributed Lag Approach: An Application on the Connectedness between Bitcoin Returns and the Other Ten Most Relevant Cryptocurrency Returns," Mathematics, MDPI, vol. 8(5), pages 1-22, May.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:5:p:810-:d:359212
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    1. Bação Pedro & Duarte António Portugal & Sebastião Helder & Redzepagic Srdjan, 2018. "Information Transmission Between Cryptocurrencies: Does Bitcoin Rule the Cryptocurrency World?," Scientific Annals of Economics and Business, Sciendo, vol. 65(2), pages 97-117, June.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Ciaian, Pavel & Rajcaniova, Miroslava & Kancs, d'Artis, 2018. "Virtual relationships: Short- and long-run evidence from BitCoin and altcoin markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 173-195.
    4. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    5. Jareño, Francisco & González, María de la O & Tolentino, Marta & Sierra, Karen, 2020. "Bitcoin and gold price returns: A quantile regression and NARDL analysis," Resources Policy, Elsevier, vol. 67(C).
    6. Koutmos, Dimitrios, 2018. "Return and volatility spillovers among cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 122-127.
    7. Bouri, Elie & Hussain Shahzad, Syed Jawad & Roubaud, David, 2020. "Cryptocurrencies as hedges and safe-havens for US equity sectors," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 294-307.
    8. Beneki, Christina & Koulis, Alexandros & Kyriazis, Nikolaos A. & Papadamou, Stephanos, 2019. "Investigating volatility transmission and hedging properties between Bitcoin and Ethereum," Research in International Business and Finance, Elsevier, vol. 48(C), pages 219-227.
    9. Mensi, Walid & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Al-Jarrah, Idries Mohammad Wanas & Kang, Sang Hoon, 2019. "Time frequency analysis of the commonalities between Bitcoin and major Cryptocurrencies: Portfolio risk management implications," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 283-294.
    10. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    11. Köchling, Gerrit & Müller, Janis & Posch, Peter N., 2019. "Price delay and market frictions in cryptocurrency markets," Economics Letters, Elsevier, vol. 174(C), pages 39-41.
    12. Platanakis, Emmanouil & Urquhart, Andrew, 2019. "Portfolio management with cryptocurrencies: The role of estimation risk," Economics Letters, Elsevier, vol. 177(C), pages 76-80.
    13. Andrew Burnie, 2018. "Exploring the Interconnectedness of Cryptocurrencies using Correlation Networks," Papers 1806.06632, arXiv.org.
    14. Song, Jung Yoon & Chang, Woojin & Song, Jae Wook, 2019. "Cluster analysis on the structure of the cryptocurrency market via Bitcoin–Ethereum filtering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    15. Paresh Kumar Narayan, 2005. "The saving and investment nexus for China: evidence from cointegration tests," Applied Economics, Taylor & Francis Journals, vol. 37(17), pages 1979-1990.
    16. Nikolaos A. Kyriazis, 2019. "A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets," JRFM, MDPI, vol. 12(4), pages 1-17, November.
    17. Arize, Augustine C. & Malindretos, John & Igwe, Emmanuel U., 2017. "Do exchange rate changes improve the trade balance: An asymmetric nonlinear cointegration approach," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 313-326.
    18. Tu, Zhiyong & Xue, Changyong, 2019. "Effect of bifurcation on the interaction between Bitcoin and Litecoin," Finance Research Letters, Elsevier, vol. 31(C).
    19. Symitsi, Efthymia & Chalvatzis, Konstantinos J., 2018. "Return, volatility and shock spillovers of Bitcoin with energy and technology companies," Economics Letters, Elsevier, vol. 170(C), pages 127-130.
    20. Charfeddine, Lanouar & Benlagha, Noureddine & Maouchi, Youcef, 2020. "Investigating the dynamic relationship between cryptocurrencies and conventional assets: Implications for financial investors," Economic Modelling, Elsevier, vol. 85(C), pages 198-217.
    21. Anoop S Kumar & Taufeeq Ajaz, 2019. "Co-movement in crypto-currency markets: evidences from wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-17, December.
    22. White, Reilly & Marinakis, Yorgos & Islam, Nazrul & Walsh, Steven, 2020. "Is Bitcoin a currency, a technology-based product, or something else?," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    23. Katsiampa, Paraskevi, 2019. "Volatility co-movement between Bitcoin and Ether," Finance Research Letters, Elsevier, vol. 30(C), pages 221-227.
    24. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    25. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    26. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis," Finance Research Letters, Elsevier, vol. 29(C), pages 68-74.
    27. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    28. 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).
    29. Nguyen, Thai Vu Hong & Nguyen, Binh Thanh & Nguyen, Thanh Cong & Nguyen, Quang Quoc, 2019. "Bitcoin return: Impacts from the introduction of new altcoins," Research in International Business and Finance, Elsevier, vol. 48(C), pages 420-425.
    30. Vidal-Tomás, David & Ibáñez, Ana M. & Farinós, José E., 2019. "Herding in the cryptocurrency market: CSSD and CSAD approaches," Finance Research Letters, Elsevier, vol. 30(C), pages 181-186.
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