Investors attention and network spillover for commodity market forecasting
Journal article
Cerqueti, R., Ficcadenti, V. and Mattera, R. (2024). Investors attention and network spillover for commodity market forecasting. Socio-Economic Planning Sciences. 95, p. 102023. https://doi.org/10.1016/j.seps.2024.102023
Authors | Cerqueti, R., Ficcadenti, V. and Mattera, R. |
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Abstract | This paper explores the role of network spillovers in commodity market forecasting and proposes a novel factor-augmented 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 commodities’ returns. |
Keywords | Dynamic network model; Google trends; Factor model; Prediction; Principal components; Commodity returns |
Year | 2024 |
Journal | Socio-Economic Planning Sciences |
Journal citation | 95, p. 102023 |
Publisher | Elsevier |
ISSN | 0038-0121 |
1873-6041 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.seps.2024.102023 |
Web address (URL) | https://www.sciencedirect.com/science/article/pii/S0038012124002222?via%3Dihub |
Publication dates | |
Online | 22 Jul 2024 |
Publication process dates | |
Accepted | 15 Jul 2024 |
Deposited | 05 Aug 2024 |
Publisher's version | License File Access Level Open |
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