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Safe havens for Bitcoin and Ethereum: evidence from high-frequency data

Author

Listed:
  • Fahad Ali

    (Zhejiang University of Finance and Economics)

  • Muhammad Usman Khurram

    (Zhejiang University
    Hangzhou City University)

  • Ahmet Sensoy

    (Bilkent University
    Lebanese American University)

Abstract

Investing in cryptocurrencies is progressively becoming a norm; however, these assets are excessively volatile and often decrease or increase in value instantly. Thus, rational investors holding cryptocurrencies for extended periods firmly search for assets that can diversify their risk, preferably with assets other than cryptocurrencies. In this study, we consider the two most studied cryptocurrencies with the highest capitalization and trading volume/value, namely Bitcoin and Ethereum. Specifically, we examine whether high-performing leading US tech stocks (Facebook, Amazon, Apple, Netflix, Google [FAANG]) can provide any diversification benefits to cryptocurrency investors. To do so, we employ dynamic conditional correlation (DCC), asymmetric DCC, time-varying parameter vector autoregression-based connectedness measures, dynamic correlation-based hedge and safe-haven regression analyses, portfolio optimization and hedging strategies, time- and frequency-based wavelet coherence, and high-frequency 10-min intraday data from January 1, 2018 to January 31, 2023. We find that FAANG stocks can be considered (at least weak) safe havens for Bitcoin and Ethereum during the sample period. Our subperiod analyses reveal that the safe-haven role of FAANG stocks, specifically for Bitcoin, has noticeably increased. While the safe-haven property of Facebook is the most promising, for Netflix it is blurred between a weak–safe-haven and a hedge. Our findings may help investors, policymakers, and academicians to invest in cryptocurrencies, formulate relevant investment guidelines, and extend the literature on cryptocurrencies, respectively.

Suggested Citation

  • Fahad Ali & Muhammad Usman Khurram & Ahmet Sensoy, 2025. "Safe havens for Bitcoin and Ethereum: evidence from high-frequency data," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-34, December.
    • Handle: RePEc:spr:fininn:v:11:y:2025:i:1:d:10.1186_s40854-024-00686-4
    DOI: 10.1186/s40854-024-00686-4
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    More about this item

    Keywords

    Cryptocurrency; FAANG stocks; High frequency data; Safe haven; COVID-19; Russia–Ukraine War; TVP–VAR; Diversification; Portfolio optimization;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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