CR-COPEC: Causal Rationale of Corporate Performance Changes to learn from Financial Reports
Ye Chun, Sunjae Kwon, Kyunghwan Sohn, Nakwon Sung, Junyoup Lee, Byoung Seo, Kevin Compher, Seung-won Hwang, Jaesik Choi
Abstract
In this paper, we introduce CR-COPEC called Causal Rationale of Corporate Performance Changes from financial reports. This is a comprehensive large-scale domain-adaptation causal sentence dataset to detect financial performance changes of corporate. CR-COPEC contributes to two major achievements. First, it detects causal rationale from 10-K annual reports of the U.S. companies, which contain experts’ causal analysis following accounting standards in a formal manner. This dataset can be widely used by both individual investors and analysts as material information resources for investing and decision-making without tremendous effort to read through all the documents. Second, it carefully considers different characteristics which affect the financial performance of companies in twelve industries. As a result, CR-COPEC can distinguish causal sentences in various industries by taking unique narratives in each industry into consideration. We also provide an extensive analysis of how well CR-COPEC dataset is constructed and suited for classifying target sentences as causal ones with respect to industry characteristics.- Anthology ID:
- 2023.findings-emnlp.26
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2023
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 339–355
- Language:
- URL:
- https://aclanthology.org/2023.findings-emnlp.26
- DOI:
- 10.18653/v1/2023.findings-emnlp.26
- Cite (ACL):
- Ye Chun, Sunjae Kwon, Kyunghwan Sohn, Nakwon Sung, Junyoup Lee, Byoung Seo, Kevin Compher, Seung-won Hwang, and Jaesik Choi. 2023. CR-COPEC: Causal Rationale of Corporate Performance Changes to learn from Financial Reports. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 339–355, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- CR-COPEC: Causal Rationale of Corporate Performance Changes to learn from Financial Reports (Chun et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2023.findings-emnlp.26.pdf