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

María de la O González, Francisco Jareño () and Frank S. Skinner
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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
Frank S. Skinner: Department of Economics and Finance, Brunel University, Uxbridge, Middlesex, London UB8 3PH, UK

Mathematics, 2020, vol. 8, issue 5, 1-22

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.

Keywords: Bitcoin; cryptocurrencies; NARDL; connectedness (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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