High frequency multiscale relationships among major cryptocurrencies: portfolio management implications

Walid Mensi (), Mobeen Ur Rehman (), Muhammad Shafiullah, Khamis Hamed Al-Yahyaee () and Ahmet Sensoy
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Walid Mensi: Sultan Qaboos University
Mobeen Ur Rehman: Shaheed Zulfikar Ali Bhutto Institute of Science and Technology (SZABIST)
Khamis Hamed Al-Yahyaee: Muscat University

Financial Innovation, 2021, vol. 7, issue 1, 1-21

Abstract: Abstract This paper examines the high frequency multiscale relationships and nonlinear multiscale causality between Bitcoin, Ethereum, Monero, Dash, Ripple, and Litecoin. We apply nonlinear Granger causality and rolling window wavelet correlation (RWCC) to 15 min—data. Empirical RWCC results indicate mostly positive co-movements and long-term memory between the cryptocurrencies, especially between Bitcoin, Ethereum, and Monero. The nonlinear Granger causality tests reveal dual causation between most of the cryptocurrency pairs. We advance evidence to improve portfolio risk assessment, and hedging strategies.

Keywords: Cryptocurrency; High frequency analysis; Nonlinear multiscale causality; Rolling window wavelet correlation (search for similar items in EconPapers)
JEL-codes: G14 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:fininn:v:7:y:2021:i:1:d:10.1186_s40854-021-00290-w

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DOI: 10.1186/s40854-021-00290-w

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