arXiv:2607. 19385v1 Announce Type: new Abstract: This paper tackles the problem of stock ranking and portfolio construction under realistic investment settings by jointly modeling temporal dynamics and cross-sectional dependencies.
By Haoran Guo, Yutong Lu, Li Zhang
arXiv:2608. 07158v1 Announce Type: new Abstract: Temporal graph learning has become essential for analyzing real-world systems whose interactions continuously evolve over time, including financial transaction networks, communication systems, and online social platforms.
By Poupak Azad, Cuneyt Gurcan Akcora, Kiarash Shamsi
arXiv:2602. 03981v2 Announce Type: replace-cross Abstract: Credit exposure in Decentralized Finance (DeFi) is often implicit and token-mediated, creating a dense web of inter-protocol dependencies.
By Aijie Shu, Wenbin Wu, Gbenga Ibikunle, Fengxiang He
arXiv:2606. 25811v1 Announce Type: cross Abstract: Commodity futures can be represented hierarchically, with underlying assets at the upper level and individual futures contracts at the lower level.
By Yoonsik Hong, Diego Klabjan
arXiv:2606. 24509v1 Announce Type: cross Abstract: Due to the wide use of graph-structured data in different fields of industry and science, the development of Graph Foundation Models (GFMs) has recently attracted a lot of attention.
By Oleg Platonov, Gleb Bazhenov, Dmitry Eremeev, Liudmila Prokhorenkova
arXiv:2606. 30997v1 Announce Type: new Abstract: We present a three-phase deep reinforcement learning system for personalized portfolio management that addresses three limitations shared by all prior financial RL work: 1) ticker lock-in, 2) monolithic objectives , and 3) static user models.
By Ramin Pishehvar