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High frequency multiscale relationships among major cryptocurrencies: portfolio management implications

Author

Listed:
  • Walid Mensi

    (Sultan Qaboos University
    South Ural State University)

  • Mobeen Ur Rehman

    (Shaheed Zulfikar Ali Bhutto Institute of Science and Technology (SZABIST))

  • Muhammad Shafiullah

    (University of Nottingham Malaysia)

  • Khamis Hamed Al-Yahyaee

    (Muscat University)

  • Ahmet Sensoy

    (Bilkent University)

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.

Suggested Citation

  • Walid Mensi & Mobeen Ur Rehman & Muhammad Shafiullah & Khamis Hamed Al-Yahyaee & Ahmet Sensoy, 2021. "High frequency multiscale relationships among major cryptocurrencies: portfolio management implications," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-21, December.
    • Handle: RePEc:spr:fininn:v:7:y:2021:i:1:d:10.1186_s40854-021-00290-w
    DOI: 10.1186/s40854-021-00290-w
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    References listed on IDEAS

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    2. Živkov, Dejan & Manić, Slavica & Gajić-Glamočlija, Marina, 2024. "How do precious and industrial metals hedge oil in a multi-frequency semiparametric CVaR portfolio?," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    3. Ruzita Abdul-Rahim & Airil Khalid & Zulkefly Abdul Karim & Mamunur Rashid, 2022. "Exploring the Driving Forces of Stock-Cryptocurrency Comovements during COVID-19 Pandemic: An Analysis Using Wavelet Coherence and Seemingly Unrelated Regression," Mathematics, MDPI, vol. 10(12), pages 1-19, June.
    4. Tim Leung & Theodore Zhao, 2024. "A Noisy Fractional Brownian Motion Model for Multiscale Correlation Analysis of High-Frequency Prices," Mathematics, MDPI, vol. 12(6), pages 1-21, March.
    5. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.
    6. Živkov, Dejan & Balaban, Suzana & Simić, Milica, 2024. "Hedging gas in a multi-frequency semiparametric CVaR portfolio," Research in International Business and Finance, Elsevier, vol. 67(PA).

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    More about this item

    Keywords

    Cryptocurrency; High frequency analysis; Nonlinear multiscale causality; Rolling window wavelet correlation;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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