This paper explores the role of network spillovers in commodity market forecasting and proposes a novel factoraugmented dynamic network model. We focus on a novel network definition based on investors’ attention to commodities, positing that commodities exhibit spillovers if they share a similar level of interest. To this aim, we employ Google Trends search data as an instrumental measure for attention. The results reveal that including attention-driven spillovers significantly enhances the forecasting accuracy of commodity returns.

Investors’ attention and network spillover for commodity market forecasting

Mattera, Raffaele
2024

Abstract

This paper explores the role of network spillovers in commodity market forecasting and proposes a novel factoraugmented dynamic network model. We focus on a novel network definition based on investors’ attention to commodities, positing that commodities exhibit spillovers if they share a similar level of interest. To this aim, we employ Google Trends search data as an instrumental measure for attention. The results reveal that including attention-driven spillovers significantly enhances the forecasting accuracy of commodity returns.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/546430
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