Multimodal Multi-Speaker Merger & Acquisition Financial Modeling: A New Task, Dataset, and Neural Baselines

Ramit Sawhney, Mihir Goyal, Prakhar Goel, Puneet Mathur, Rajiv Ratn Shah


Abstract
Risk prediction is an essential task in financial markets. Merger and Acquisition (M&A) calls provide key insights into the claims made by company executives about the restructuring of the financial firms. Extracting vocal and textual cues from M&A calls can help model the risk associated with such financial activities. To aid the analysis of M&A calls, we curate a dataset of conference call transcripts and their corresponding audio recordings for the time period ranging from 2016 to 2020. We introduce M3ANet, a baseline architecture that takes advantage of the multimodal multi-speaker input to forecast the financial risk associated with the M&A calls. Empirical results prove that the task is challenging, with the pro-posed architecture performing marginally better than strong BERT-based baselines. We release the M3A dataset and benchmark models to motivate future research on this challenging problem domain.
Anthology ID:
2021.acl-long.526
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Month:
August
Year:
2021
Address:
Online
Editors:
Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6751–6762
Language:
URL:
https://aclanthology.org/2021.acl-long.526
DOI:
10.18653/v1/2021.acl-long.526
Bibkey:
Cite (ACL):
Ramit Sawhney, Mihir Goyal, Prakhar Goel, Puneet Mathur, and Rajiv Ratn Shah. 2021. Multimodal Multi-Speaker Merger & Acquisition Financial Modeling: A New Task, Dataset, and Neural Baselines. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 6751–6762, Online. Association for Computational Linguistics.
Cite (Informal):
Multimodal Multi-Speaker Merger & Acquisition Financial Modeling: A New Task, Dataset, and Neural Baselines (Sawhney et al., ACL-IJCNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.acl-long.526.pdf
Video:
 https://aclanthology.org/2021.acl-long.526.mp4