Name
Title | ||
|---|---|---|
Robust Semi-Variance Downside Risk Portfolio Problems: A Convex Optimization Approach |
Abstract | ||
|---|---|---|
Consider a robust portfolio optimization problem which minimizes the worst-case expected disutility (the negative utility) function to account for both the uncertain nonnegative probability distributions and the uncertain returns. In particular, the disutility function is adopted as a semi-variance which is a wellknowndownside risk measure, and the problem therefore is also termed as a robust semi-variance downside risk portfolio problem. When the uncertainty sets are a class of intersections of the nonnegative orthants and ellipsoidal sets, the robust downside risk portfolio problem can be equivalently transformed into a finite optimization problem in an explicit form, namely a second-order cone program, via the strong duality of convex optimization theory. Therefore the new robust portfolio problem is tractable computationally and can be solved efficiently by an convex optimization solver. To validate our results, simulation examples are presented to demonstrate the performance gains of the proposed method over an existing conservative robust design. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/SSP.2018.8450686 | 2018 IEEE Statistical Signal Processing Workshop (SSP) |
Keywords | Field | DocType |
Portfolio selection,semi-variance disutility,no short selling,robust optimization counterparts,second-order cone programs | Mathematical optimization,Downside risk,Computer science,Portfolio,Portfolio optimization,Strong duality,Solver,Risk measure,Convex optimization,Optimization problem | Conference |
ISBN | Citations | PageRank |
978-1-5386-1572-0 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maobiao Yang | 1 | 0 | 0.34 |
| Yongwei Huang | 2 | 814 | 50.83 |