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 / Cerqueti, Roy; Ficcadenti, Valerio; Mattera, Raffaele. - In: SOCIO-ECONOMIC PLANNING SCIENCES. - ISSN 0038-0121. - 95:(2024). [10.1016/j.seps.2024.102023]

Investors’ attention and network spillover for commodity market forecasting

Cerqueti, Roy;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.
2024
dynamic network model; Google Trends; factor model; prediction; principal components; commodity returns
01 Pubblicazione su rivista::01a Articolo in rivista
Investors’ attention and network spillover for commodity market forecasting / Cerqueti, Roy; Ficcadenti, Valerio; Mattera, Raffaele. - In: SOCIO-ECONOMIC PLANNING SCIENCES. - ISSN 0038-0121. - 95:(2024). [10.1016/j.seps.2024.102023]
File allegati a questo prodotto
File Dimensione Formato  
SEPS 2024 Ficcadenti Mattera.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 961.43 kB
Formato Adobe PDF
961.43 kB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1721732
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 0
social impact