Financial networks of cryptocurrency prices in time-frequency domains

Paolo Pagnottoni (), Angelo Famà () and Jong-Min Kim ()
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Paolo Pagnottoni: University of Pavia
Angelo Famà: Catholic University of the Sacred Heart
Jong-Min Kim: University of Minnesota-Morris

Quality & Quantity: International Journal of Methodology, 2024, vol. 58, issue 2, No 18, 1389-1407

Abstract: 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.

Keywords: Financial networks; Forecast error variance decomposition; Cryptocurrency market; Connectedness; Frequency connectedness (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11135-023-01704-w

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