Hojin Ko (고호진)

M.S. student (Semester 0)

Hojin Ko

Non-exponential discounting frameworks · paper accepted to ICML 2026

Papers

  • Beyond the Bellman Recursion: A Pontryagin-Guided Framework for Non-Exponential Discounting, Hojin Ko*, Jeonggyu Huh*, accepted in International Conference on Machine Learning (ICML), 2026
  • Rec-ve-ing No-Tr-de Re-i-ns: Pont--a-in-Gui--d Po--cy Proj--tion f-r Tr--action-C-st -ont-ol, submitted
  • Decision-Focused Conditional Beta Learning for Cost-Aware Portfolio Optimization, submitted

Papers in Progress

  • Finite-Horizon Stochastic Income and Optimal Policies via Pontryagin-Guided Direct Policy Optimization
  • Breaking the Dimensional Barrier for Dynamic Portfolio Choice with Optimal Stopping
  • Macro-Based Forecasting of Implied Volatility Surface Dynamics

Project in Progress

  • ELS Hedging Decision-Making System Using Neural Optimal Control, Jul. 2026–Jun. 2027, RiskX-led project, 2026 Seoul FinTech Technology Commercialization Support Program

Talks

  • Beyond the Bellman Recursion: A Pontryagin-Guided Framework for Non-Exponential Discounting, The 2nd Sookmyung-TMU Mathematical Finance Workshop with Young Researchers, 2026
  • Breaking the Dimensional Barrier in Dynamic Portfolio Choice with Transaction Costs, The Korean Operations Research and Management Science Society (KORMS), Oral Presentation, Spring 2026
  • Beyond the Bellman Recursion: A Pontryagin-Guided Framework for Non-Exponential Discounting, International Conference on Machine Learning (ICML), Poster, 2026 scheduled

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