Dual Stochastic Dominance and Related Mean-Risk Models
SIAM Journal on Optimization
Robust mixture modelling using the t distribution
Statistics and Computing
Robust portfolio selection problems
Mathematics of Operations Research
Generating Scenario Trees for Multistage Decision Problems
Management Science
Static Mean-Variance Analysis with Uncertain Time Horizon
Management Science
Constructing Risk Measures from Uncertainty Sets
Operations Research
Constructing Risk Measures from Uncertainty Sets
Operations Research
Robust portfolio selection problem for an insurer with exponential utility preference
WSEAS Transactions on Mathematics
Robust optimization framework for cardinality constrained portfolio problem
Applied Soft Computing
Computers and Operations Research
Robust portfolio selection involving options under a " marginal+joint " ellipsoidal uncertainty set
Journal of Computational and Applied Mathematics
Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics
Operations Research
Mean-CVaR portfolio selection: A nonparametric estimation framework
Computers and Operations Research
Worst-Case Value at Risk of Nonlinear Portfolios
Management Science
SDP reformulation for robust optimization problems based on nonconvex QP duality
Computational Optimization and Applications
Journal of Intelligent and Robotic Systems
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This paper considers the worst-case Conditional Value-at-Risk (CVaR) in the situation where only partial information on the underlying probability distribution is available. The minimization of the worst-case CVaR under mixture distribution uncertainty, box uncertainty, and ellipsoidal uncertainty are investigated. The application of the worst-case CVaR to robust portfolio optimization is proposed, and the corresponding problems are cast as linear programs and second-order cone programs that can be solved efficiently. Market data simulation and Monte Carlo simulation examples are presented to illustrate the proposed approach.