Portfolio optimization by using MeanSharp-βVaR and Multi Objective MeanSharp-βVaR models
DOI10.2298/FIL1803815BOpenAlexW2884328516MaRDI QIDQ5023453
Sarah Navidi, Shokoofeh Banihashemi
Publication date: 21 January 2022
Published in: Filomat (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.2298/fil1803815b
data envelopment analysisportfolio optimizationvalue at risknegative datamulti objective decision makingMeanSharp-\(\beta\)VaRmulti objective MeanSharp-\(\beta\)VaR
Multi-objective and goal programming (90C29) Management decision making, including multiple objectives (90B50) Special problems of linear programming (transportation, multi-index, data envelopment analysis, etc.) (90C08) Portfolio theory (91G10)
Cites Work
- Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis
- Measuring the efficiency of decision making units
- Computation of mean-semivariance efficient sets by the critical line algorithm
- Predicting extreme value at risk: nonparametric quantile regression with refinements from extreme value theory
- A semi-oriented radial measure for measuring the efficiency of decision making units with negative data, using DEA
- Large returns, conditional correlation and portfolio diversification: a value-at-risk approach
- Negative data in DEA: a directional distance approach applied to bank branches
- Portfolio Value-at-Risk with Heavy-Tailed Risk Factors
- Nonparametric estimation of value-at-risk
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