1 citations · 2 across the 5 of their papers we have counts for
5 papers
GuruAgents: Emulating Wise Investors with Prompt-Guided LLM Agents
Yejin Kim, Youngbin Lee, Juhyeong Kim +1
This study demonstrates that GuruAgents, prompt-guided AI agents, can systematically operationalize the strategies of legendary investment gurus. We develop five distinct GuruAgent…
LLM-Enhanced Black-Litterman Portfolio Optimization
Youngbin Lee, Yejin Kim, Juhyeong Kim +2
The Black-Litterman model addresses the sensitivity issues of tra- ditional mean-variance optimization by incorporating investor views, but systematically generating these views re…
A Recommender System for NFT Collectibles with Item Feature
Minjoo Choi, Seonmi Kim, Yejin Kim +3
Recommender systems have been actively studied and applied in various domains to deal with information overload. Although there are numerous studies on recommender systems for movi…
Temporal Graph Networks for Graph Anomaly Detection in Financial Networks
Yejin Kim, Youngbin Lee, Minyoung Choe +2
This paper explores the utilization of Temporal Graph Networks (TGN) for financial anomaly detection, a pressing need in the era of fintech and digitized financial transactions. We…
A Temporal Graph Network Framework for Dynamic Recommendation
Yejin Kim, Youngbin Lee, Vincent Yuan +2
Recommender systems, crucial for user engagement on platforms like e-commerce and streaming services, often lag behind users' evolving preferences due to static data reliance. Afte…