3 papers
q-fin.PM2026
Yau's Affine-Normal Descent for Large-Scale Unrestricted Higher-Moment Portfolio Optimization
Ya-Juan Wang, Yi-Shuai Niu, Artan Sheshmani +1
Unrestricted mean-variance-skewness-kurtosis portfolio optimization can capture asymmetry and tail risk, but sample-moment formulations become computationally impractical when the…
math.OC2026
Scalable Mean-Variance Portfolio Optimization via Subspace Embeddings and GPU-Friendly Nesterov-Accelerated Projected Gradient
Yi-Shuai Niu, Yajuan Wang
We develop a sketch-based factor reduction and a Nesterov-accelerated projected gradient algorithm (NPGA) with GPU acceleration, yielding a doubly accelerated solver for large-scal…
math.OC2019
High-order Moment Portfolio Optimization via An Accelerated Difference-of-Convex Programming Approach and Sums-of-Squares
Yi-Shuai Niu, Ya-Juan Wang, Hoai An Le Thi +1
The Mean-Variance-Skewness-Kurtosis (MVSK) portfolio optimization model is a quartic nonconvex polynomial minimization problem over a polytope, which can be formulated as a Differe…