What’s Really in a Deal? Evidence from Textual Analysis

Hu, Wenyao; Shohfi, Thomas; Wang, Runzu

doi:10.2139/ssrn.3292343

Cited by 3 publications

(2 citation statements)

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“…M&A Conference Calls Financial reports and conference calls have been shown to have a correlation with the stock market and improve financial predictions (Bowen et al, 2001;Kogan et al, 2009). Studies have also been carried out specifically for M&A calls, showing their effect on the market (Dasgupta et al, 2020;Hu et al, 2018). However, there exists a gap in leveraging neural predictive modeling on using verbal and vocal cues pertaining to M&A calls for financial forecasting.…”

Section: Related Workmentioning

confidence: 99%

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

Sawhney¹,

Goyal²,

Goel³

et al. 2021

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Confer

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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 multispeaker input to forecast the financial risk associated with the M&A calls. Empirical results prove that the task is challenging, with the proposed 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.

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Section: Related Workmentioning

confidence: 99%

“…Studies have also been carried out specifically for M&A calls, showing their effect on the market (Dasgupta et al, 2020;Hu et al, 2018). However, there exists a gap in leveraging neural predictive modeling on using verbal and vocal cues pertaining to M&A calls for financial forecasting.…”

Section: Related Workmentioning

confidence: 99%