Achim, M.A.; Belbe, Ș.; Mare, C. & Otto, P. (2026) Finance Research Letters [Core Economics, Q1]

Publicat: 02 Octombrie 2026

Achim, M.A.; Belbe, Ș.; Mare, C. & Otto, P. (2026) Spatial effects and uncertainty in cryptocurrencies – the case of network ARCH models. Finance Research Letters, 111, 110729.

DOI: https://doi.org/10.1016/j.frl.2026.110729

✓ Publisher: Elsevier
✓ Categories: Business, Finance
✓ Article Influence Score (AIS): 1,004 (2025) / Q1

Abstract:
Cryptocurrency markets form tightly interconnected networks in which volatility spills immediately across coins, yet conventional GARCH models treat each asset in isolation. Building on the Spatial ARCH approach, we model these spillovers with a dynamic network ARCH framework, defining neighbours through return-correlation adjacency matrices. Using a balanced daily panel of 50 cryptocurrencies over 1517 trading days (2021–2025), we estimate volatility dependence across network, time and network diffusion effects by quasi-maximum likelihood after a multivariate ARMA mean filter. Price volatility exhibits strong contemporaneous network spillover (ρ≈0.43), whereas volume volatility is largely idiosyncratic (ρ≈0.12). Diagnostics confirm the model properly addresses the cryptocurrencies features as it removes remaining ARCH dependence from residuals.

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