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AuthorMensi, Walid
AuthorAl-Yahyaee, Khamis Hamed
AuthorAl-Jarrah, Idries Mohammad Wanas
AuthorVo, Xuan Vinh
AuthorKang, Sang Hoon
Available date2023-01-17T06:57:07Z
Publication Date2020
Publication NameNorth American Journal of Economics and Finance
ResourceScopus
URIhttp://dx.doi.org/10.1016/j.najef.2020.101285
URIhttp://hdl.handle.net/10576/38494
AbstractThis study used hourly data to examine the dynamic conditional correlations and hedging strategies in the main cryptocurrency markets: Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), and Ripple (XRP). Multivariate generalized autoregressive conditional heteroskedasticity family models provided evidence of significant positive dynamic conditional correlations among these markets. A weaker conditional correlation was observed for the LCT-XRP portfolio than for the BTC-ETH portfolio, which had the highest correlation value. The dynamic correlations intensified after the cryptocurrency crisis. The results of a portfolio risk analysis suggested that investors should hold less BTC than LTC, ETH, and XRP to minimize risk while maintaining consistent expected portfolio returns. Investors should hold less BTC than the other cryptocurrencies during a crisis. In addition, the cheapest hedge strategy is to hold long BTC and short XRP regardless of the period. Holding long BTC and short LTC was found to be the most expensive hedge strategy. Finally, the study showed that an optimally weighted diversified portfolio provides the greatest reduction in risk and downside risk for ETH and LTC. For XRP, portfolio hedging is the best mechanism for reducing risk. 2020 Elsevier Inc.
SponsorThe last author (Sang Hoon Kang) achnowledges the financial support by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea ( NRF-2020S1A5B8103268 ).
Languageen
PublisherElsevier
SubjectCryptocurrencies
Dynamic conditional correlations
Hedge strategy
Hourly data
multivariate GARCH model
Portfolio risk management
TitleDynamic volatility transmission and portfolio management across major cryptocurrencies: Evidence from hourly data
TypeArticle
Volume Number54
dc.accessType Abstract Only


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