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Connectedness between cryptocurrencies using high-frequency data: A novel insight from the Silicon Valley Banks collapse

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Listed:
  • Ali, Shoaib
  • Moussa, Faten
  • Youssef, Manel

Abstract

The collapse of Silicon Valley Bank (SVB), a tech industry bank, has shaken the global financial markets, including cryptocurrencies; therefore, this study intends to investigate the return and volatility spillovers between leading cryptocurrencies using high-frequency data and the TVP-VAR model. The results indicate that the total return connectedness had increased in the aftermath of the collapse, but the volatility connectedness remains unchanged. Moreover, conventional (stablecoins) cryptocurrencies are the net transmitter (recipient) of return and volatility spillovers from the system. The results of this study have important implications for investors and portfolio managers seeking to safeguard their investments.

Suggested Citation

  • Ali, Shoaib & Moussa, Faten & Youssef, Manel, 2023. "Connectedness between cryptocurrencies using high-frequency data: A novel insight from the Silicon Valley Banks collapse," Finance Research Letters, Elsevier, vol. 58(PB).
    • Handle: RePEc:eee:finlet:v:58:y:2023:i:pb:s1544612323007249
    DOI: 10.1016/j.frl.2023.104352
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    Keywords

    SVB; Cryptocurrencies; Connectedness; High-frequency data;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • F3 - International Economics - - International Finance
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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