3 papers in the archive (2024–2025), average empirical rigor 1.8/10, average math complexity 8.8/10. Quadrant mix: Lab Rats ×3.
Works mostly in Stochastic Control & Optimal Stopping, Portfolio Optimization.
Frequent co-authors: Jingzhen Liu (3), Jiaqin Wei (2), Alain Bensoussan (1), Ka-Fai Cedric Yiu (1), Yusha Chen (1), Zhenyu Cui (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%).
The monotone mean-variance (MMV) preference proposed by Maccheroni, et al. (Math. Finance 19(3): 487-521, 2009) fails to differentiate strictly dominant payoffs, which may cause inconsistency in portfolio decision-making. This paper introduces a broader class of strictly monotone mean-variance (SMMV
In this paper we derive a novel characterization result for time-consistent stochastic control problems with higher-order moments, originally formulated by Wang et al. [SIAM J. Control. Optim., 63 (2025), 1560–1589], and newly explore many solvable instances including a mean-variance-excess kurtosi
In this paper, we focus on a class of time-inconsistent stochastic control problems, where the objective function includes the mean and several higher-order central moments of the terminal value of state. To tackle the time-inconsistency, we seek both the closed-loop and the open-loop Nash equilibri