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Sejong University, 03/2026–
- Associate Professor, Department of Economics
Korea Institute for International Economic Policy (KIEP), 08/2023–02/2026
- Research Fellow, International Finance Team, 01/2025–02/2026
- Associate Research Fellow, International Finance Team, 08/2023–12/2024
City University of Hong Kong, 05/2016–06/2023
- Assistant Professor (Finance), Department of Economics and Finance
Korean Air Force, 09/2012–11/2015
- 1st Lieutenant/Assistant Professor (Mandatory Military Service)
Ph.D. in Economics, University of Pennsylvania, 2012
M.A. in Economics, University of Pennsylvania, 2011
B.Sc. in Physics and B.A. in Economics, Summa cum Laude, Seoul National University, 2006
Working Papers
Revise and Resubmit at the Journal of Economic Theory
This paper extends the Kalman–Bucy–Liptser–Shiryaev filter (Kalman and Bucy, 1961; Liptser and Shiryaev, 1974) to a case of ambiguous state dynamics. The extension shows that ambiguity about the drift of the state process translates, through learning, into additional volatility for the process. This helps rationalize the seemingly excessive long-run risk (LRR) implied by stock returns. The generalized filter is embedded in recursive maxmin expected utility and applied to asset pricing to demonstrate that the endogenous LRR indeed improves the performance of the LRR model: With learning under ambiguity, the predictability of consumption growth decreases while that of stock returns increases; and the estimated elasticity of intertemporal substitution decreases.
How Much Do Investors Follow AI Advice? Recommendation Pass-Through in a Pension Portfolio Experiment, with Jeongbin Kim, Matthew Kovach, Kyu-Min Lee, Euncheol Shin, and Hector Tzavellas
We identify how recommendation content passes through to pension portfolios. In an experiment, 400 South Korean defined contribution plan participants choose portfolios before and after random assignment to two AI-generated recommendations. Along the axis connecting them, 36.8 percent of the induced gap passes through to portfolios. Content shifts return, volatility, risk allocations, and breadth, with no detectable effects on Sharpe ratios or concentration. Eighty-one percent revise. Among revisers, 95 percent move toward the recommendation but implement half of the suggested adjustment. Rationales have no statistically reliable effect on pass-through. Content thus shifts risk exposure despite incomplete implementation.
Publications
Learning about Ambiguous Long-Term Prospects, 2026, Journal of Economic Theory
On the Timing Premium Puzzle, 2025, Economics Letters
Work in Progress
Can Learning Reduce the Dark Matter in the Long-Run Risk Model?
General Research Fund, Hong Kong Research Grants Council, 01/2022–12/2023
Research Interests
Finance (Theoretical Asset Pricing, Portfolio Choice), Microeconomics (Decision Making under Ambiguity)
Teaching
Sejong University, 2026–
Principles of Economics
Mathematics for Social Sciences
City University of Hong Kong, 2016–2023
Derivatives and Risk Management
Fixed Income Securities
Stochastic Calculus for Finance
Theoretical Asset Pricing (Part 2/4)
Financial Management
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