Introduces the GNHAR model that augments the heterogeneous autoregressive framework with network-based spillovers to forecast multivariate realized variances, claiming better performance than standard HAR benchmarks on equity data.
arXiv preprint arXiv:2512.10446 , year=
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Network Time Series Models for Multivariate Volatility Forecasting
Introduces the GNHAR model that augments the heterogeneous autoregressive framework with network-based spillovers to forecast multivariate realized variances, claiming better performance than standard HAR benchmarks on equity data.