4 papers
Decision by Supervised Learning with Deep Ensembles: A Practical Framework for Robust Portfolio Optimization
Juhyeong Kim, Sungyoon Choi, Youngbin Lee +3
We propose Decision by Supervised Learning (DSL), a practical framework for robust portfolio optimization. DSL reframes portfolio construction as a supervised learning problem: mod…
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…
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…
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…