FAST: Financial News and Tweet Based Time Aware Network for Stock Trading

Ramit Sawhney, Arnav Wadhwa, Shivam Agarwal, Rajiv Ratn Shah


Abstract
Designing profitable trading strategies is complex as stock movements are highly stochastic; the market is influenced by large volumes of noisy data across diverse information sources like news and social media. Prior work mostly treats stock movement prediction as a regression or classification task and is not directly optimized towards profit-making. Further, they do not model the fine-grain temporal irregularities in the release of vast volumes of text that the market responds to quickly. Building on these limitations, we propose a novel hierarchical, learning to rank approach that uses textual data to make time-aware predictions for ranking stocks based on expected profit. Our approach outperforms state-of-the-art methods by over 8% in terms of cumulative profit and risk-adjusted returns in trading simulations on two benchmarks: English tweets and Chinese financial news spanning two major stock indexes and four global markets. Through ablative and qualitative analyses, we build the case for our method as a tool for daily stock trading.
Anthology ID:
2021.eacl-main.185
Volume:
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Month:
April
Year:
2021
Address:
Online
Editors:
Paola Merlo, Jorg Tiedemann, Reut Tsarfaty
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2164–2175
Language:
URL:
https://aclanthology.org/2021.eacl-main.185
DOI:
10.18653/v1/2021.eacl-main.185
Bibkey:
Cite (ACL):
Ramit Sawhney, Arnav Wadhwa, Shivam Agarwal, and Rajiv Ratn Shah. 2021. FAST: Financial News and Tweet Based Time Aware Network for Stock Trading. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 2164–2175, Online. Association for Computational Linguistics.
Cite (Informal):
FAST: Financial News and Tweet Based Time Aware Network for Stock Trading (Sawhney et al., EACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.eacl-main.185.pdf