Impact of media hype and fake news on commodity futures prices: A deep learning approach over the COVID-19 period

Ameet Kumar Banerjee, Ahmet Sensoy, John W. Goodell and Biplab Mahapatra

Finance Research Letters, 2024, vol. 59, issue C

Abstract: We investigate the reactions of eight commodity futures to media hype and fake news during COVID-19, utilising the Ravenpack news database, along with deep learning algorithms. Results identify a significant impact on commodity prices of media hype and fake news, with this reaction amplified during COVID-19. Compared to alternative deep learning algorithms, bi-directional long-short-term memory is adaptive to forecasting the returns of the commodity futures contracts with lower mean absolute error and root mean square error. Findings, confirmed by Diebold-Mariano testing, as well as alternative data partitioning, show commodity markets are susceptible to fake news and media hype.

Keywords: Commodity futures; Media hype; Fake news; Ravenpack database; COVID-19 (search for similar items in EconPapers)
JEL-codes: G12 G13 G14 G15 G17 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:59:y:2024:i:c:s1544612323010309

DOI: 10.1016/j.frl.2023.104658

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