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Dynamic volatility transmission and portfolio management across major cryptocurrencies: Evidence from hourly data

Walid Mensi, Khamis Hamed Al-Yahyaee, Idries Mohammad Wanas Al-Jarrah, Xuan Vinh Vo and Sang Hoon Kang

The North American Journal of Economics and Finance, 2020, vol. 54, issue C

Abstract: This 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.

Keywords: Hourly data; Cryptocurrencies; Portfolio risk management; multivariate GARCH model; Dynamic conditional correlations; Hedge strategy (search for similar items in EconPapers)
JEL-codes: G14 G15 (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:54:y:2020:i:c:s1062940820301777

DOI: 10.1016/j.najef.2020.101285

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