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Forecasting Global Volatility with Predictive Spillover Networks: A Neuro-Econometric Spatio-Temporal Transformer for Asynchronous Financial Markets
Forecasting global realized volatility requires a model that can learn from interconnected markets without treating zero-coded exchange closures as observed zero volatility. We develop PGA-Trans-HAR, a neuro-econometric architecture that combines a rolling ridge-VAR/GFEVD predictive-connectedness ne
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