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

被引：6

作者：

Banerjee, Ameet Kumar ^{[1
]}

Sensoy, Ahmet ^{[2
,3
]}

Goodell, John W. ^{[4
]}

Mahapatra, Biplab ^{[5
]}

机构：

[1] XLRI Xavier Sch Management, Jamshedpur, Jharkhand, India

[2] Bilkent Univ, Fac Business Adm, Ankara, Turkiye

[3] Lebanese Amer Univ, Adnan Kassar Sch Business, Beirut, Lebanon

[4] Univ Akron, Akron, OH 44325 USA

[5] Xavier Univ, Xavier Inst Management, Bhubaneswar, Odisha, India

来源：

FINANCE RESEARCH LETTERS | 2024年 / 59卷

关键词：

Commodity futures; Media hype; Fake news; Ravenpack database; COVID-19; FINANCIALIZATION; INFORMATION; MARKETS;

D O I：

10.1016/j.frl.2023.104658

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

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.

引用

页数：8

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