Attention Based Dynamic Graph Learning Framework for Asset Pricing

Ajim Uddin, Xinyuan Tao, Dantong Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent studies suggest that financial networks play an essential role in asset valuation and investment decisions. Unlike road networks, financial networks are neither given nor static, posing significant challenges in learning meaningful networks and promoting their applications in price prediction. In this paper, we first apply the attention mechanism to connect the "dots"(firms) and learn dynamic network structures among stocks over time. Next, the end-to-end graph neural networks pipeline diffuses and propagates the firms' accounting fundamentals into the learned networks and ultimately predicts stock future returns. The proposed model reduces the prediction errors by 6% compared to the state-of-the-art models. Our results are robust with different assessment measures. We also show that portfolios based on our model outperform the S&P-500 index by 34% in terms of Sharpe Ratio, suggesting that our model is better at capturing the dynamic inter-connection among firms and identifying stocks with fast recovery from major events. Further investigation on the learned networks reveals that the network structure aligns closely with the market conditions. Finally, with an ablation study, we investigate different alternative versions of our model and the contribution of each component.

Original languageEnglish (US)
Title of host publicationCIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages1844-1853
Number of pages10
ISBN (Electronic)9781450384469
DOIs
StatePublished - Oct 26 2021
Event30th ACM International Conference on Information and Knowledge Management, CIKM 2021 - Virtual, Online, Australia
Duration: Nov 1 2021Nov 5 2021

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference30th ACM International Conference on Information and Knowledge Management, CIKM 2021
Country/TerritoryAustralia
CityVirtual, Online
Period11/1/2111/5/21

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

Keywords

  • asset pricing
  • diffusion recurrent convolution
  • fintech
  • graph attention
  • graph neural networks
  • stock price prediction

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