Media influences on corn futures pricing

Author First name, Last name, Institution

Xinquan Zhou, Tsinghua University
Guillaume Bagnarosa, Rennes School of Business; National Research Institute for Agriculture, Food and Environment
Michael Dowling, Dublin City University
Jagadish Dandu, Zayed University

Document Type

Article

Source of Publication

European Review of Agricultural Economics

Publication Date

3-16-2024

Abstract

Abstract Understanding agricultural commodity futures is crucial for efficient business operations. This study employs textual machine learning on 290,271 articles (2009–2020) focusing on corn markets, aiming to model the impact of news on corn futures pricing. Our novel approach enables the identification of seven distinct topics within corn news, offering a comprehensive view of the news coverage spectrum. Soybean biofuel news notably influences corn prices, while exports, weather and wheat news significantly impact pricing uncertainty. These insights deepen our understanding of factors shaping corn futures and highlight machine learning’s potential in agricultural economic analysis, enabling more accurate market predictions and policy decisions.

DOI Link

10.1093/erae/jbae002

ISSN

0165-3618

Publisher

Oxford University Press (OUP)

First Page

jbae002

Last Page

jbae002

Disciplines

Business

Keywords

Commodity futures, Agricultural economics, Textual machine learning, Market predictions, Policy decisions

Recommended Citation

Zhou, Xinquan; Bagnarosa, Guillaume; Dowling, Michael; and Dandu, Jagadish, "Media influences on corn futures pricing" (2024). All Works. 6498.
https://zuscholars.zu.ac.ae/works/6498

Indexed in Scopus

no

Open Access

no