Abstract | ||
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We investigate in this paper dynamic mean-downside risk portfolio optimization problems in continuous-time, where the downside risk measures can be either the lower-partial moments (LPM) or the conditional value-at-risk (CVaR). Our contributions are twofold, both building up tractable formulations and deriving corresponding analytical solutions. By imposing a limit funding level on the terminal wealth, we conquer the ill-posedness exhibited in a class of mean-downside risk portfolio models. For a general market setting, we prove the existence and uniqueness of the Lagrangian multiplies, which is a key step in applying the martingale approach, and establish a theoretical foundation for developing efficient numerical solution approaches. Moreover, for situations where the opportunity set of the market setting is deterministic, we derive analytical portfolio policies for both dynamic mean-LPM and mean-CVaR formulations. |
Year | DOI | Venue |
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2017 | 10.1137/140955264 | SIAM JOURNAL ON CONTROL AND OPTIMIZATION |
Keywords | Field | DocType |
dynamic mean-downside risk portfolio optimization,lower-partial moments,LPM,conditional value-at-risk portfolio,CVaR,stochastic control,martingale approach | Mathematical optimization,Martingale (probability theory),Downside risk,Replicating portfolio,Portfolio,Post-modern portfolio theory,Portfolio optimization,Mathematics,Stochastic control,CVAR | Journal |
Volume | Issue | ISSN |
55 | 3 | 0363-0129 |
Citations | PageRank | References |
1 | 0.48 | 7 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jianjun Gao | 1 | 51 | 11.33 |
ke zhou | 2 | 1 | 0.48 |
Duan Li | 3 | 56 | 12.31 |
Xi-Ren Cao | 4 | 930 | 123.58 |