@inproceedings{zhai-zhang-2019-forecasting,
title = "Forecasting Firm Material Events from 8-K Reports",
author = "Zhai, Shuang (Sophie) and
Zhang, Zhu (Drew)",
editor = "Hahn, Udo and
Hoste, V{\'e}ronique and
Zhang, Zhu",
booktitle = "Proceedings of the Second Workshop on Economics and Natural Language Processing",
month = nov,
year = "2019",
address = "Hong Kong",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-5104",
doi = "10.18653/v1/D19-5104",
pages = "22--30",
abstract = "In this paper, we show deep learning models can be used to forecast firm material event sequences based on the contents in the company{'}s 8-K Current Reports. Specifically, we exploit state-of-the-art neural architectures, including sequence-to-sequence (Seq2Seq) architecture and attention mechanisms, in the model. Our 8K-powered deep learning model demonstrates promising performance in forecasting firm future event sequences. The model is poised to benefit various stakeholders, including management and investors, by facilitating risk management and decision making.",
}
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%0 Conference Proceedings
%T Forecasting Firm Material Events from 8-K Reports
%A Zhai, Shuang (Sophie)
%A Zhang, Zhu (Drew)
%Y Hahn, Udo
%Y Hoste, Véronique
%Y Zhang, Zhu
%S Proceedings of the Second Workshop on Economics and Natural Language Processing
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong
%F zhai-zhang-2019-forecasting
%X In this paper, we show deep learning models can be used to forecast firm material event sequences based on the contents in the company’s 8-K Current Reports. Specifically, we exploit state-of-the-art neural architectures, including sequence-to-sequence (Seq2Seq) architecture and attention mechanisms, in the model. Our 8K-powered deep learning model demonstrates promising performance in forecasting firm future event sequences. The model is poised to benefit various stakeholders, including management and investors, by facilitating risk management and decision making.
%R 10.18653/v1/D19-5104
%U https://aclanthology.org/D19-5104
%U https://doi.org/10.18653/v1/D19-5104
%P 22-30
Markdown (Informal)
[Forecasting Firm Material Events from 8-K Reports](https://aclanthology.org/D19-5104) (Zhai & Zhang, 2019)
ACL
- Shuang (Sophie) Zhai and Zhu (Drew) Zhang. 2019. Forecasting Firm Material Events from 8-K Reports. In Proceedings of the Second Workshop on Economics and Natural Language Processing, pages 22–30, Hong Kong. Association for Computational Linguistics.