Certified High-Dimensional Wasserstein Robust Portfolio Optimization

Battle Count: 74

Directly addresses high-dimensional portfolio optimization with robust guarantees. Demonstrates monthly rebalancing of 476-asset portfolios and scalability to 1000 assets. The certified approximation framework provides explicit error bounds on portfolio performance, making it highly relevant for practical quantitative trading systems requiring robust allocation under distributional uncertainty.

The final formulation (Corollary 3.7) is a standard linear program solvable with any LP solver (MOSEK, Gurobi, etc.). The main complexity lies in: (1) constructing the supporting hyperplane partition for the utility function, (2) understanding the Wasserstein duality framework, and (3) choosing appropriate parameters (eta, epsilon). The LP itself has O(n*N*eta^{-1/2}) variables and constraints, which is tractable for practical portfolio sizes.

The paper provides complete mathematical formulations, specifies solver (MOSEK via CVXPY), uses publicly available data (Yahoo Finance, FRED), and details experimental parameters (tolerance eta, radius grid, sample sizes). The box-specialized LP in Corollary 3.7 is fully specified. However, no code repository is explicitly linked.