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Market Trend Analysis Using Polarity Index Generated from Analyst Reports

Rei TAGUCHI, Hikaru WATANABE, Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI, Kiyoshi IZUMI, Kenji HIRAMATSU

2021 IEEE International Conference on Big Data (Big Data), pp. 3486-3494, Dec. 15, 2021

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Conference

The 4th International Workshop on Cross-disciplinary Data Exchange and Collaboration (CDEC2021) in conjunction with 2021 IEEE International Conference on Big Data (Big Data)

Abstract

This study demonstrates whether analysts’ sentiment toward individual stocks is useful in predicting the macroeconomic index. This can be achieved by using natural language processing to create polarity indexes from analyst reports. In this study, the created polarity indexes were analyzed using the Vector Autoregressive model with various macroeconomic indexes. Consequently, it was confirmed that the polarity indexes do have an impact on indexes such as prices, exchange rates, and government bonds.

Keywords

Analyst Report; BERT; Vector Autoregressive (VAR) Model;

doi

10.1109/BigData52589.2021.9671702

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bibtex

@inproceedings{Taguchi2021-cdec4,
  title={{Market Trend Analysis Using Polarity Index Generated from Analyst Reports}},
  author={Rei TAGUCHI and Hikaru WATANABE and Masanori HIRANO and Masahiro SUZUKI and Hiroki SAKAJI and Kiyoshi IZUMI and Kenji HIRAMATSU},
  booktitle={2021 IEEE International Conference on Big Data (Big Data)},
  pages={3486-3494},
  doi={10.1109/BigData52589.2021.9671702},
  year={2021}
}

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