Financial Engineering Laboratory is a research group in the department of Industrial and Systems Engineering at KAIST.
Welcome to KAIST Financial Engineering Lab.
Latest Publications
- Hyunglip Bae, Jang Ho Kim, Hwayong Choi, Frank J. Fabozzi, Woo Chang Kim (2026). Deep Financial Planning. Annals of Operations Research.
- Haeun Jeon*, Seunghoon Choi*, Hyunglip Bae, Yongjae Lee, Woo Chang Kim (2026). Decision-Focused Sparse Tangent Portfolio Optimization. International Conference on Machine Learning (ICML).
- Mingyu Yang, Guhyuk Chung, Chanyeong Kim, Woo Chang Kim (2026). Enhancing Limit Order Book Modeling Through Type-Based Representation. Pacific-Asia Conference on Knowledge Discovery and Data Mining.
- Insu Choi, Soyeong Lim, Seoyeon Kim, Yeona Choi, Subin Han, Woo Chang Kim (2026). Metric-based Technical Indicators for Yield Forecasting. Pacific-Basin Finance Journal.
- Insu Choi, Woo Chang Kim (2026). Beyond Linear Insights in the Feldstein–Horioka Puzzle: Delving Into Monotonic and Nonlinear Statistical Dependencies With Moving Windows. International Finance.
- Hyunglip Bae∗, Minsu Park∗, Haeun Jeon, Woo Chang Kim (2025), A Decision-focused Learning Framework for Goal-based Investing, Quantitative Finance.
- Insu Choi, Woo Chang Kim (2026). Navigating the Flow: Unveiling Directional Information Transfer in Commodity Markets With Transfer Entropy and Moving Window Analysis. Complexity.
- Jang Ho Kim, Yongjae Lee, Woo Chang Kim, Jae Wook Song, Frank J. Fabozzi (2025). Random Forests for Feature Selection: Concepts and Applications in Asset Management. Journal of Portfolio Management.
- Junhyeong Lee, Haeun Jeon, Hyunglip Bae, and Yongjae Lee. (2025, November). Return Prediction for Mean-Variance Portfolio Selection: How Decision-Focused Learning Shapes Forecasting Models. In Proceedings of the 6th ACM International Conference on AI in Finance (pp. 114-122).
- Sungho Lee, Sukmin Hwang, Chanyeong Kim, Mingyu Yang, Yongjae Lee, and Woo Chang Kim (2025, November). From Constituents to Index: Interpretable Price Movement Prediction via Cross-Asset Order Flow. In Proceedings of the 6th ACM International Conference on AI in Finance (pp. 665-673).
- Sukmin Hwang, Sungho Lee, Chanyeong Kim, Yongjae Lee, and Woo Chang Kim (2025, November). Shock-Biased Attention: Enhancing Transformer Hawkes Processes with Amplitude-Driven Temporal Kernels. In Proceedings of the 6th ACM International Conference on AI in Finance (pp. 915-923).
- Myounggu Lee, Insu Choi, and Woo Chang Kim (2025), "Predicting Mobile Payment Behavior Through Explainable Machine Learning and Application Usage Analysis" Journal of Theoretical and Applied Electronic Commerce Research, 20(2), 117. [full paper]
- Haeun Jeon*, Hyunglip Bae*, Minsu Park, Chanyeong Kim, and Woo Chang Kim (2025), "Locally Convex Global Loss Network for Decision-Focused Learning" presented at the Association for the Advancement of Artificial Intelligence (AAAI) (Oral Presentation).
- Insu Choi & Woo Chang Kim (2025). "A Multifaceted Graph-wise Network Analysis of Sector-Based Financial Instruments' Price-Based Discrepancies with Diverse Statistical Interdependencies". The North American Journal of Economics and Finance.
- Jang Ho Kim, Yongjae Lee, Woo Chang Kim, Taehyeon Kang, and Frank J. Fabozzi (2024). "An Overview of Optimization Models for Portfolio Management". The Journal of Portfolio Management 51 (1). [full paper]
- Insu Choi & Woo Chang Kim (2024). "Unlocking ETF Price Foreasting: Explring the Interconnections with Statistical Dependence-Based Graphs and xAI Techniques". Knowledge-Based Systems. 305, 112567. [full paper]
- Lee, Yongjae; Kim, Jang Ho; Kim, Woo Chang; Fabozzi, Frank J (2024). “An Overview of Machine Learning for Portfolio Optimization". Journal of Portfolio Management. [full paper]
- Jang Ho Kim*, Seyoung Kim, Yongjae Lee, Woo Chang Kim, and Frank J. Fabozzi (2024). "Enhancing mean-variance portfolio optimization through GANs-based anomaly detection". Annals of Operation Research. [full paper]
- Insu Choi* and Woo Chang Kim* (2024). "A Temporal Information Transfer Network Approach Considering Federal Funds Rate for an Interpretable Asset Fluctuation Prediction Framework". International Review of Economics and Finance. [full paper]
- Sanghyeon Bae*, Yongjae Lee, Woo Chang Kim*, Jang Ho Kim, and Frank J. Fabozzi (2024). "Goal-based investing with goal postponement: Multistage stochastic mixed-integer programming approach", Annals of Operations Research, 1-25. [full paper]
- Insu Choi*, Woosung Koh*, Gimin Kang, Yuntae Jang, & Woo Chang Kim (2024). "Encoding Temporal Statistical-space Priors via Augmented Representation under Data Scarcity", 3rd International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2024) at International Joint Conference on Artificial Intelligence (IJCAI) 2024. CEUR-WS.org.
- Minsu Kim*, Joohwan Ko*, Taeyoung Yun*, Dinghuai Zhang, Ling Pan, Woo Chang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio (2024), “Learning to Scale Logits for Temperature-Conditional GFlowNet”, International Conference on Machine Learning (ICML)
- Joohwan Ko*, Kyurae Kim*, Woo Chang Kim, Jacob R. Gardner (2024). “Provably Scalable Black-Box Variational Inference with Structured Variational Families”, International Conference on Machine Learning (ICML)
- Insu Choi and Woo Chang Kim (2024). Practical Forecasting of Risk Boundaries for Industrial Metals and Critical Minerals via Statistical Machine Learning Techniques. International Review of Financial Analysis. 103252.[full paper]
- Guhyuk Chung, Yongjae Lee+, and Woo Chang Kim+ (2024), "Neural Marked Hawkes Process for Limit Order Book Modeling," Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD).
- Woosung Koh*, Insu Choi*, Yuntae Jang*, Gimin Kang, and Woo Chang Kim (2024), "Curriculum Learning and Imitation Learning for Model-free Control on Financial Time-series," AI4TS: AI for Time Series Analysis: Theory, Algorithms, and Application Workshop at AAAI 2024.
- Insu Choi*, Woosung Koh*, Bonwoo Koo*, and Woo Chang Kim (2024), "Network-based Exploratory Data Analysis and Explainable Clustering for Financial Customer Profiling," Engineering Applications of Artificial Intelligence. [full paper]
- Insu Choi and Woo Chang Kim (2024), "Enhancing Exchange-Traded Fund Price Predictions: Insights from Information-Theoretic Networks and Node Embeddings". Entropy, 26(1), 70. [full paper]
- Insu Choi, Jihye Kim, and Woo Chang Kim (2024), "An Explainable Prediction for Dietary-Related Diseases via Language Models," Nutrients, 16(5), 686. [full paper]
