Submitted
- Scalable Pontryagin-Guided Adjoint-to-Control Recovery for Constrained Dynamic Portfolio Choice, Jeonggyu Huh*, Jaegi Jeon*, Hyeng-Keun Koo, Byung-Hwa Lim, under revision in Mathematical Finance [Paper] [Slides]
- MarketGANs: Multivariate Financial Time-Series Data Augmentation Using Generative Adversarial Networks, Jeonggyu Huh*, Seungwon Jeong, Hyeng-Keun Koo, Byung-Hwa Lim, Hyun-Gyoon Kim*, under revision in Financial Innovation [Link]
- Reinforcement Learning and Heterogeneity in Nonlinear Financial Markets, Hyun Soo Doh*, Yunzhi Hu, Jeonggyu Huh, Byung-Hwa Lim, reject & resubmit, Management Science [Link]
- Self-Consistent Adjoint Policy Iteration for Constrained Dynamic Portfolio Choice, Jeonggyu Huh*, Yeoneung Kim, Seungwon Jeong [Link]
- Knowing When Not to Act: Latent No-Action Region Recovery Hidden in Neural Control, Hojin Ko*, Jeonggyu Huh* [Slide]
- Differentiating Through Delay: Stochastic Control Without Full History Hessians, Seungwon Jeong*, Jihun Kim*, Jeonggyu Huh*
- Neural Policy Iteration for Dynamic Portfolio Choice with Control-Dependent Diffusion, Seungwon Jeong*, Jeonggyu Huh*, Yeoneung Kim*
- Computable Welfare Bounds for Constrained Dynamic Portfolio Choice, Seungwon Jeong*, Jeonggyu Huh*, Yeoneung Kim*
- Sobolev-Stable Regime-Conditioned DeepONet for Monthly Implied-Volatility Surface Forecasting, Hojin Ko*, Jeonggyu Huh*, Ho-Jun Lee, Wonwoo Choi
- Forecast Origins and Information Value in Cross-Market Volatility Forecasting, Jaegi Jeon*, Jeonggyu Huh, Seungwon Jeong*
- Barrier killing and wrong-way CVA under fast mean-reverting volatility, Jaegi Jeon*, Jeonggyu Huh* [Link]
2026
- Beyond the Bellman Recursion: A Pontryagin-Guided Framework for Non-Exponential Discounting, Hojin Ko*, Jeonggyu Huh*, International Conference on Machine Learning (ICML), 2026 [Link]
- Learning Distributions for Continuous-Time Financial Models, Jeonggyu Huh*, Seung-Won Jeong*, Computational Economics, 2026 [Link]
- Equity Premium Forecasting with Reliability-Screened Forward-Looking Signals, Jeonggyu Huh*, Jaegi Jeon, Seung-Won Jeong*, PLOS One, 2026 [Link]
- DeepONet-Based Surrogate Modeling for Bond Option Pricing, Sang-Hyun Lee*, Jeonggyu Huh, Seungwon Jeong*, AIMS Mathematics, 2026 [Link]
2025
- LSTM-based Dynamic Correlation Forecasting with Economic Conditions, Jeonggyu Huh*, Seungwoo Ha, Seung-Won Jeong*, Finance Research Letters, 2025 [Link]
- Improved Accuracy of an Analytical Approximation for Option Pricing under Stochastic Volatility Models using Deep Learning Techniques, Donghyun Kim*, Jeonggyu Huh*, Ji-Hun Yoon, Computers and Mathematics with Applications, 2025 [Link]
- Considering Appropriate Input Features of Neural Network to Calibrate Option Pricing Models, Hyun-Gyoon Kim*, Hyeongmi Kim, Jeonggyu Huh*, Computational Economics, 2025 [Link]
- Deep Learning of Optimal Exercise Boundaries for American Options, Hyun-Gyoon Kim*, Jeonggyu Huh*, International Journal of Computer Mathematics, 2025 [Link]
- Pontryagin-Guided Direct Policy Optimization for Continuous-Time Portfolio Problem, Jeonggyu Huh*, Jaegi Jeon*, Seung-Won Jeong, Journal of Industrial and Management Optimization, 2025 [Link]
- Reliable option pricing through deep learning: An anomaly score-based approach, Jihong Park*, Jeonggyu Huh, Jaegi Jeon*, Networks and Heterogeneous Media, 2025 [Link]
- Dual‑Uncertainty Modeling in Financial Time‑Series via VMD‑LSTM with Concrete Dropout and VMD‑WGAN, Jeonggyu Huh*, Dajin Kim, Minseok Jung, Seung-Won Jeong*, Networks and Heterogeneous Media, 2025 [Link]
- [Conference] Bounded Rationality, Reinforcement Learning, and Market Efficiency, Hyun Soo Doh*, Byung Hwa Lim, Jeonggyu Huh, China International Conference in Finance (CICF), 2025 [Link]
- [Insight Report] AI Bringing Dynamic Portfolio Choice into Reality, The Korean Journal of Financial Studies, 2025 [Link]
2024
- Tighter 'Uniform Bounds for Black-Scholes Implied Volatility' and the Applications to Root-Finding, Jaehyuk Choi*, Jeonggyu Huh, Su Nan, Operations Research Letters, 2024 [Link]
- Accelerating SDE Simulation through Learning of Stochastic Dynamics, Seung-Won Jeong*, Ji-Hun Kim, Jitae Jung, Jeonggyu Huh*, Journal of Korean Society for Industrial and Applied Mathematics, 2024 [Link]
- [Conference] Continuous-Time Portfolio Optimization via Model-based Reinforcement Learning, Jeonggyu Huh, Hyeng-Keun Koo, Byung Hwa Lim*, Financial Management Association (FMA) Asia/Pacific, 2024 [Link]
2023
- Variable Annuity with a Surrender Option under Multi-Scale Stochastic Volatility, Jeonggyu Huh*, Junkee Jeon, Kyunghyun Park*, Japan Journal of Industrial and Applied Mathematics, 2023 [Link]
- Analytical Pricing of Exchange Option with Default Risk under a Stochastic Volatility Model, Jaegi Jeon*, Jeonggyu Huh, Geonwoo Kim*, Advances in Continuous and Discrete Models, 2023 [Link]
- Random Augmentation Technique for Mitigating Overfitting in Neural Networks for Financial Time Series Forecasting, Yeonglong Kwak*, Jeonggyu Huh*, Journal of The Korean Data Analysis Society, 2023 [Link]
2022
- Extensive Networks Would Eliminate the Demand for Pricing Formulas, Jaegi Jeon*, Kyunghyun Park, Jeonggyu Huh*, Knowledge-Based Systems, 2022 [Link]
- Pricing Path-Dependent Exotic Options with Flow-Based Generative Networks, Hyun-Gyoon Kim*, Se-Jin Kwon, Jeong-Hoon Kim, Jeonggyu Huh*, Applied Soft Computing, 2022 [Link]
- Large Scale Online Learning of Implied Volatilities, Tae-Kyoung Kim*, Hyun-Gyoon Kim, Jeonggyu Huh*, Expert Systems with Applications, 2022 [Link]
- Newton–Raphson Emulation Network for Highly Efficient Computation of Numerous Implied Volatilities, Geon Lee*, Tae-Kyoung Kim, Hyun-Gyoon Kim, Jeonggyu Huh*, Journal of Risk and Financial Management, 2022 [Link]
2021
- Consistent and Efficient Pricing of SPX Options and VIX Options under Multi-Scale Stochastic Volatilities, Jaegi Jeon*, Geonwoo Kim, Jeonggyu Huh*, Journal of Futures Markets, 2021 [Link]
- Asymptotic Expansion Approach to the Valuation of Vulnerable Option under a Multiscale Stochastic Volatility Model, Jaegi Jeon*, Geonwoo Kim, Jeonggyu Huh*, Chaos, Solitons & Fractals, 2021 [Link]
- Pricing of Vulnerable Power Exchange Option under the Hybrid Model, Jaegi Jeon*, Jeonggyu Huh, Geonwoo Kim*, East Asian Mathematical Journal, 2021
- Simplified Approach to Valuation of Vulnerable Exchange Option under a Reduced-Form Model, Jeonggyu Huh*, Jaegi Jeon, Geonwoo Kim*, East Asian Mathematical Journal, 2021
2020
- Measuring Systematic Risk with Neural Network Factor Model, Jeonggyu Huh*, Physica A: Statistical Mechanics and its Applications, 2020 [Link]
- Static Hedges of Barrier Options under Fast Mean-Reverting Stochastic Volatility, Jeonggyu Huh*, Jaegi Jeon, Yong-Ki Ma*, Computational Economics, 2020 [Link]
- An Analytic Approximation for the Valuation of American Option in Two Regimes, Junkee Jeon*, Jeonggyu Huh, Kyunghyun Park*, Computational Economics, 2020 [Link]
2019
- Pricing Options with Exponential Levy Neural Network, Jeonggyu Huh*, Expert Systems with Applications, 2019 [Link]
- A Reduced PDE Method for European Option Pricing under Multi-Scale, Multi-Factor stochastic volatility, Jeonggyu Huh*, Jaegi Jeon, Jeong-Hoon Kim*, Hyejin Park, Quantitative Finance, 2019 [Link]
- Barrier Option Pricing with Heavy-Tailed Distribution, Geonwoo Kim*, Jeonggyu Huh*, Economic Computation and Economic Cybernetics Studies and Research, 2019
2018
- A Scaled Version of the Double-Mean-Reverting Model for VIX Derivatives, Jeonggyu Huh*, Jaegi Jeon, Jeong-Hoon Kim*, Mathematics and Financial Economics, 2018 [Link]