3 papers in the archive (2023–2024), average empirical rigor 1.8/10, average math complexity 9.3/10. Quadrant mix: Lab Rats ×3.
Works mostly in Portfolio Optimization, Stochastic Control & Optimal Stopping, Volatility Modeling & Forecasting, Options & Derivatives Pricing.
Frequent co-authors: Chi Seng Pun (3), Jingxiang Tang (1).
Scores are our LLM-assisted heuristics (methodology), not peer review or citation counts. Author pages are generated from paper metadata; name variants may split one person across pages. arXiv author page →
Ordered by a blend of empirical rigor (60%) and math complexity (40%).
This paper studies dynamic mean-variance (MV) asset allocation problems in general incomplete markets. Besides of the conventional MV objective on portfolio’s terminal wealth, our framework can accommodate running MV objectives with general (non-exponential) discounting factors while in general, any
This paper studies the well-posedness of a class of nonlocal parabolic partial differential equations (PDEs), or equivalently equilibrium Hamilton-Jacobi-Bellman equations, which has a strong tie with the characterization of the equilibrium strategies and the associated value functions for time-inco
In this paper, we establish existence, uniqueness, and regularity properties of the solutions to multi-dimensional backward stochastic Volterra integral equations (BSVIEs), whose (possibly random) generator reflects nonlinear dependence on both the solution process and the martingale integrand compo