Name
Title | ||
|---|---|---|
Properties, formulations, and algorithms for portfolio optimization using Mean-Gini criteria. |
Abstract | ||
|---|---|---|
We study an extended set of Mean-Gini portfolio optimization models that encompasses a general version of the mean-risk formulation, the Minimal Gini model (MinG) that minimizes Gini’s Mean Differences, and the new risk-adjusted Mean-Gini Ratio (MGR) model. We analyze the properties of the various models, prove that a performance measure based on a Risk Adjusted version of the Mean Gini Ratio (RAMGR) is coherent, and establish the equivalence between maximizing this performance measure and solving for the maximal Mean-Gini ratio. We propose a linearization approach for the fractional programming formulation of the MGR model. We also conduct a thorough evaluation of the various Mean-Gini models based on four data sets that represent combinations of bullish and bearish scenarios in the in-sample and out-of-sample phases. The performance is (i) analyzed with respect to eight return, risk, and risk-adjusted criteria, (ii) benchmarked with the Su0026P500 index, and (iii) compared with their Mean-Variance counterparts for varying risk aversion levels and with the Minimal CVaR and Minimal Semi-Deviation models. For the data sets used in our study, our results suggest that the various Mean-Gini models almost always result in solutions that outperform the Su0026P500 benchmark index with respect to the out-of-sample cumulative return. Further, particular instances of Mean-Gini models result in solutions that are as good or better (for example, MinG in bullish in-sample scenarios, and MGR in bearish out-of-sample scenarios) than the solutions obtained with their counterparts in Mean-Variance, Minimal CVaR and Minimal Semi-Deviation models. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s10479-016-2230-4 | Annals OR |
Keywords | Field | DocType |
Mean-Gini model, Mean-Gini ratio, Portfolio optimization | Mathematical optimization,Data set,Equivalence (measure theory),Portfolio optimization,Risk aversion,Almost surely,Fractional programming,Mathematics,Linearization,CVAR | Journal |
Volume | Issue | ISSN |
248 | 1-2 | 1572-9338 |
Citations | PageRank | References |
1 | 0.36 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ran Ji | 1 | 1 | 0.36 |
| Miguel A. Lejeune | 2 | 253 | 21.95 |
| Srinivas Y. Prasad | 3 | 12 | 2.12 |