VolTAGE: Volatility Forecasting via Text Audio Fusion with Graph Convolution Networks for Earnings Calls

Ramit Sawhney, Piyush Khanna, Arshiya Aggarwal, Taru Jain, Puneet Mathur, Rajiv Ratn Shah


Abstract
Natural language processing has recently made stock movement forecasting and volatility forecasting advances, leading to improved financial forecasting. Transcripts of companies’ earnings calls are well studied for risk modeling, offering unique investment insight into stock performance. However, vocal cues in the speech of company executives present an underexplored rich source of natural language data for estimating financial risk. Additionally, most existing approaches ignore the correlations between stocks. Building on existing work, we introduce a neural model for stock volatility prediction that accounts for stock interdependence via graph convolutions while fusing verbal, vocal, and financial features in a semi-supervised multi-task risk forecasting formulation. Our proposed model, VolTAGE, outperforms existing methods demonstrating the effectiveness of multimodal learning for volatility prediction.
Anthology ID:
2020.emnlp-main.643
Volume:
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Month:
November
Year:
2020
Address:
Online
Editors:
Bonnie Webber, Trevor Cohn, Yulan He, Yang Liu
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
8001–8013
Language:
URL:
https://aclanthology.org/2020.emnlp-main.643
DOI:
10.18653/v1/2020.emnlp-main.643
Bibkey:
Cite (ACL):
Ramit Sawhney, Piyush Khanna, Arshiya Aggarwal, Taru Jain, Puneet Mathur, and Rajiv Ratn Shah. 2020. VolTAGE: Volatility Forecasting via Text Audio Fusion with Graph Convolution Networks for Earnings Calls. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 8001–8013, Online. Association for Computational Linguistics.
Cite (Informal):
VolTAGE: Volatility Forecasting via Text Audio Fusion with Graph Convolution Networks for Earnings Calls (Sawhney et al., EMNLP 2020)
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PDF:
https://aclanthology.org/2020.emnlp-main.643.pdf
Video:
 https://slideslive.com/38939137