Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1287/opre.1080.0684 | Operations Research |
Keywords | Field | DocType |
corresponding problem,market data simulation,worst-case conditional value-at-risk,monte carlo simulation example,underlying probability distribution,ellipsoidal uncertainty,robust portfolio management,box uncertainty,mixture distribution uncertainty,worst-case cvar,risk management,linear program,mixture distribution,conditional value at risk,monte carlo simulation,probability distribution,portfolio management,portfolio optimization,robust optimization,correspondence problem | Mixture distribution,Monte Carlo method,Mathematical optimization,Project portfolio management,Portfolio optimization,Probability distribution,Linear programming,Operations management,Mathematics,Expected shortfall,CVAR | Journal |
Volume | Issue | ISSN |
57 | 5 | 0030-364X |
Citations | PageRank | References |
94 | 4.62 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shushang Zhu | 1 | 244 | 13.07 |
| Masao Fukushima | 2 | 2050 | 172.73 |