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Financial networks of cryptocurrency prices in time-frequency domains

Author

Listed:
  • Paolo Pagnottoni

    (University of Pavia)

  • Angelo Famà

    (Catholic University of the Sacred Heart)

  • Jong-Min Kim

    (University of Minnesota-Morris)

Abstract

This paper explores financial networks of cryptocurrency prices in both time and frequency domains. We complement the generalized forecast error variance decomposition method based on a large VAR model with network theory to analyze the dynamic network structure and the shock propagation mechanisms across a set of 40 cryptocurrency prices. Results show that the evolving network topology of spillovers in both time and frequency domains helps towards a more comprehensive understanding of the interactions among cryptocurrencies, and that overall spillovers in the cryptocurrency market have significantly increased in the aftermath of COVID-19. Our findings indicate that a significant portion of these spillovers dissipate in the short-run (1–5 days), highlighting the need to consider the frequency persistence of shocks in the network for effective risk management at different target horizons.

Suggested Citation

  • Paolo Pagnottoni & Angelo Famà & Jong-Min Kim, 2024. "Financial networks of cryptocurrency prices in time-frequency domains," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(2), pages 1389-1407, April.
    • Handle: RePEc:spr:qualqt:v:58:y:2024:i:2:d:10.1007_s11135-023-01704-w
    DOI: 10.1007/s11135-023-01704-w
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    References listed on IDEAS

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