Sensitivity analysis for mean-variance portfolio problems
Management Science
Mathematics of Operations Research
Robust portfolio selection problems
Mathematics of Operations Research
Adjustable robust solutions of uncertain linear programs
Mathematical Programming: Series A and B
Robust Mean-Covariance Solutions for Stochastic Optimization
Operations Research
Robust portfolio selection involving options under a " marginal+joint " ellipsoidal uncertainty set
Journal of Computational and Applied Mathematics
Robust solutions of uncertain linear programs
Operations Research Letters
Direct data-driven portfolio optimization with guaranteed shortfall probability
Automatica (Journal of IFAC)
Hi-index | 7.29 |
We consider the problem of optimal portfolio choice using the lower partial moments risk measure for a market consisting of n risky assets and a riskless asset. For when the mean return vector and variance/covariance matrix of the risky assets are specified without specifying a return distribution, we derive distributionally robust portfolio rules. We then address potential uncertainty (ambiguity) in the mean return vector as well, in addition to distribution ambiguity, and derive a closed-form portfolio rule for when the uncertainty in the return vector is modelled via an ellipsoidal uncertainty set. Our result also indicates a choice criterion for the radius of ambiguity of the ellipsoid. Using the adjustable robustness paradigm we extend the single-period results to multiple periods, and derive closed-form dynamic portfolio policies which mimic closely the single-period policy.