{"type":"ScholarlyArticle","title":"Heterogeneous Interactive Snapshot Network for Review-Enhanced Stock Profiling and Recommendation","authors":[{"name":"Heyuan Wang","slug":"heyuan-wang","given":"Heyuan","family":"Wang","affiliation":"School of Computer Science , National Engineering Laboratory for Big Data Analysis and Applications , Peking University , China; Institute of Computational Social Science , Peking University(Qingdao)"},{"name":"Tengjiao Wang","slug":"tengjiao-wang","given":"Tengjiao","family":"Wang","affiliation":"School of Computer Science , National Engineering Laboratory for Big Data Analysis and Applications , Peking University , China; Institute of Computational Social Science , Peking University(Qingdao)"},{"name":"Shun Li","slug":"shun-li","given":"Shun","family":"Li","affiliation":"University of International Relations"},{"name":"Shijie Guan","slug":"shijie-guan","given":"Shijie","family":"Guan","affiliation":"School of Computer Science , National Engineering Laboratory for Big Data Analysis and Applications , Peking University , China; Institute of Computational Social Science , Peking University(Qingdao)"},{"name":"Jiayi Zheng","slug":"jiayi-zheng","given":"Jiayi","family":"Zheng","affiliation":"School of Computer Science , National Engineering Laboratory for Big Data Analysis and Applications , Peking University , China; Institute of Computational Social Science , Peking University(Qingdao)"},{"name":"Wei Chen","slug":"wei-chen","given":"Wei","family":"Chen","affiliation":"School of Computer Science , National Engineering Laboratory for Big Data Analysis and Applications , Peking University , China; Institute of Computational Social Science , Peking University(Qingdao)"}],"abstract":"Stock recommendation plays a critical role in modern quantitative trading. The large volumes of social media information such as investment reviews that delegate emotion-driven factors, together with price technical indicators formulate a “snapshot” of the evolving stock market profile. However, previous studies usually model the temporal trajectories of price and media modalities separately while losing their interrelated influences. Moreover, they mainly extract review semantics via sequential or attentive models, whereas the rich text associated knowledge is largely neglected. In this paper, we propose a novel heterogeneous interactive snapshot network for stock profiling and recommendation. We model investment reviews in each snapshot as a heterogeneous document graph, and develop a flexible hierarchical attentive propagation framework to capture fine-grained proximity features. Further, to learn stock embedding for ranking, we introduce a novel twins-GRU method, which tightly couples the media and price parallel sequences in a cross-interactive fashion to catch dynamic dependencies between successive snapshots. Our approach excels state-of-the-arts over 7.6% in terms of cumulative and risk-adjusted returns in trading simulations on both English and Chinese benchmarks.","doi":"10.24963/ijcai.2022/550","url":"https://ijcai.org/proceedings/2022/550","pdf":"https://ijcai.org/proceedings/2022/0550.pdf","markdown":"https://ijcai.org/proceedings/2022/550.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/550","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Multidisciplinary Topics and Applications","track":"Main Track","number":550,"pages":{"first":3962,"last":3969},"keywords":["Multidisciplinary Topics and Applications: Finance","Data Mining: Applications"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38986782","length_sec":88,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38984925","length_sec":361,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Bacry et al., 2015] Emmanuel Bacry, Iacopo Mastromatteo, and Jean Fran?Ois Muzy. 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