Faculty Research Profile
Yongjae Lee
학력
· Ph.D. in Industrial & Systems Engineering, KAIST, 2016
· B.S. in Computer Science, KAIST, 2011
· B.S. in Mathematical Science, KAIST, 2011
주요 경력
· Associate Professor, Department of Industrial Engineering, Artificial Intelligence Graduate School, UNIST, Korea, 2024 to Present
· Editorial Advisory Board Member, Journal of Financial Data Science, 2020 to Present
· BK Assistant Professor, Department of Transdisciplinary Studies, Seoul National University, Korea, 2017 to 2018
· Post-doctoral Researcher, KAIST Center for Wealth Management Technologies, Korea, 2016 to 2017
수상/학회/외부활동
· Best Poster Award, 4th ACM International Conference on AI in Finance (ICAIF’23), November, 2023
· 2022 UNIST Outstanding Faculty Award (in Education), UNIST, April 2023
· Outstanding Paper Award, KIIE, 2016
· Best Management Science Ph.D. Thesis Award, KORMS, 2016
금융공학연구실
Financial Engineering Lab
UNIST 금융공학연구실에서는 개인 또는 기관의 재무설계(financial planning)를 위한 데이터 기반의 정량적인 기법들을 연구하고 개발합니다. 연구 분야는 크게 다음 세 가지로 구분될 수 있습니다.
1. 투자자(고객) 분석
- 재무설계를 위해서는 투자자(고객)의 상황 및 니즈를 정확하게 이해하는 것이 중요합니다. 투자자와 관련된 금융 데이터(예: 급여 기록, 은행 계좌 입출금내역, 신용카드 사용내역)와 비금융 데이터(예: 직업, 가족관계, 건강검진 기록)를 분석하여 맞춤형 재무설계를 위한 주요 요소들을 파악합니다.(예: 재무목표, 위험회피성향, 제약조건)
- 관련 기법: 데이터 사이언스; 통계학
2. 시장 분석
- 주식, 채권 등 금융자산을 포함해 상품, 데이터 등 비금융자산의 동적 특성을 분석하고 연구합니다.
- 관련 기법: 계량경제학; 확률과정; 기계학습
3. 의사결정 최적화
- 고객 정보와 시장 분석을 바탕으로 최적의 맞춤형 재무설계를 찾습니다. 특히 불확실성 하에서 다기간에 걸친 의사결정 문제를 주로 다룹니다.
- 관련 기법: 최적화; 기계학습
UNIST Financial Engineering Laboratory aim to identify various problems associated with finance industry and solve them via quantitative methods. Our research areas include:
- Customized financial planning for individuals/institutions: use ML/AI techniques to analyze clients, and use mathematical optimization or reinforcement learning techniques to derive optimal financial plans
- Analyzing and modeling financial markets: use probabilistic models, ML/AI techniques to analyze and model financial assets such as equities, bonds, real estates, commodities, or data.
UNIST Financial Engineering Laboratory aim to identify various problems associated with finance industry and solve them via quantitative methods. Our research areas include:
- Customized financial planning for individuals/institutions: use ML/AI techniques to analyze clients, and use mathematical optimization or reinforcement learning techniques to derive optimal financial plans
- Analyzing and modeling financial markets: use probabilistic models, ML/AI techniques to analyze and model financial assets such as equities, bonds, real estates, commodities, or data.
연구분야
금융공학, 금융인공지능, 재무계획, 가계 및 개인 금융 ／ Financial Engineering, AI for Finance, Financial Planning, Household and Personal Finance
Financial Engineering, AI for Finance, Financial Planning, Household and Personal Finance
연구주제
금융공학, 금융인공지능, 재무계획, 가계 및 개인 금융
Financial Engineering, AI for Finance, Financial Planning, Household and Personal Finance
Financial Engineering, AI for Finance, Financial Planning, Household and Personal Finance
국가연구개발사업 기술 분류체계
국가과학기술표준분류
SC. 경제/경영 > SC13. 재무관리 > SC1303. 투자/위험관리
논문
· Hwang, Yoontae; Park, Junpyo; Kim, Jang Ho*; Lee, Yongjae**; Fabozzi, Frank J. (2024) “Heterogeneous Trading Behaviors of Individual Investors: A Deep Clustering Approach,” Finance Research Letters, 65, 105481
· Kim, Kyeongbin†; Hwang, Yoontae†; Lim, Dongcheol; Kim, Suhyeon; Lee, Junghye*; Lee, Yongjae** (2023) "Household Financial Health: A Machine Learning Approach for Data-Driven Diagnosis and Prescription," Quantitative Finance, 23(11), 1565-1595
· Hwang, Yoontae; Lee, Junhyeong; Kim, Daham; Noh, Seunghwan; Hong, Joohwan*; Lee, Yongjae** (2023) “SimStock: Representation Model for Stock Similarities,” The 4th ACM International Conference on AI in Finance (ICAIF’23), oral presentation (top 27%)
특허
· Collaborative Filtering Recommender System for Stock Recommendation (주식 추천을 위한 협업 필터링 추천 시스템) (No. 10-2022-0100772) / Investors: Kim, Woo Chang; Chung, Munki; Lee, Yongjae; Choi, Hwayong / Contents: Collaborative filtering recommender system for mean-variance investors / Status: Filed
· Method and Apparatus for Asset Management (자산 운용 방법) (No. 10-1951340) / Inventors: Kim, Woo Chang; Kwon, Do-Gyun; Lee, Yongjae; Kim, Jang Ho; Lin, Changle / Country: Korea / Registered: 2019.02.18