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Future of Information and Communication Conference

FICC 2021: Advances in Information and Communication pp 589–601Cite as

Impact of News on the Commodity Market: Dataset and Results

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 1364)

Abstract

Over the last few years, machine learning based methods have been applied to extract information from news flow in the financial domain. However, this information has mostly been in the form of the financial sentiments contained in the news headlines, primarily for the stock prices. In our current work, we propose that various other dimensions of information can be extracted from news headlines, which will be of interest to investors, policy-makers and other practitioners. We propose a framework that extracts information such as past movements and expected directionality in prices, asset comparison and other general information that the news is referring to. We apply this framework to the commodity “Gold” and train the machine learning models using a dataset of 11,412 human-annotated news headlines (released with this study), collected from the period 2000–2019. We experiment to validate the causal effect of news flow on gold prices and observe that the information produced from our framework significantly impacts the future gold price.

Keywords

  • Machine learning
  • Natural Language Processing
  • Text mining

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Acknowledgments

Ankur Sinha would like to acknowledge India Gold Policy Centre (IGPC) for supporting this study under grant number 1815012.

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Authors and Affiliations

  1. Production and Quantitative Methods, Indian Institute of Management Ahmedabad, Ahmedabad, 380015, India

    Ankur Sinha & Tanmay Khandait

Authors
  1. Ankur Sinha
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  2. Tanmay Khandait
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Corresponding author

Correspondence to Tanmay Khandait .

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Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Prof. Dr. Kohei Arai

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Sinha, A., Khandait, T. (2021). Impact of News on the Commodity Market: Dataset and Results. In: Arai, K. (eds) Advances in Information and Communication. FICC 2021. Advances in Intelligent Systems and Computing, vol 1364. Springer, Cham. https://doi.org/10.1007/978-3-030-73103-8_41

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