Risk-return trade-off with the scenario approach in practice: a case study in portfolio selection
From MaRDI portal
Publication:1935293
DOI10.1007/s10957-012-0074-xzbMath1257.90089OpenAlexW2020274275MaRDI QIDQ1935293
Publication date: 14 February 2013
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10957-012-0074-x
Related Items (11)
Chance-constrained problems and rare events: an importance sampling approach ⋮ Scenario Min-Max Optimization and the Risk of Empirical Costs ⋮ FAST—Fast Algorithm for the Scenario Technique ⋮ On Conditional Risk Assessments in Scenario Optimization ⋮ Recovery strategies from major supply disruptions in single and multiple sourcing networks ⋮ Wait-and-judge scenario optimization ⋮ Expected shortfall: heuristics and certificates ⋮ New safe approximation of ambiguous probabilistic constraints for financial optimization problem ⋮ Partial sample average approximation method for chance constrained problems ⋮ A linear programming approach for linear programs with probabilistic constraints ⋮ Risk and complexity in scenario optimization
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A sampling-and-discarding approach to chance-constrained optimization: feasibility and Optimality
- An integer programming approach for linear programs with probabilistic constraints
- IIS branch-and-cut for joint chance-constrained stochastic programs and application to optimal vaccine allocation
- Sample average approximation method for chance constrained programming: Theory and applications
- Robust solutions of uncertain linear programs
- Uncertain convex programs: randomized solutions and confidence levels
- On mixing sets arising in chance-constrained programming
- The Exact Feasibility of Randomized Solutions of Uncertain Convex Programs
- A CHANCE-CONSTRAINED PORTFOLIO SELECTION PROBLEM UNDER t-DISTRIBUTION
- A Sample Approximation Approach for Optimization with Probabilistic Constraints
- Lectures on Stochastic Programming
- Pattern-Based Modeling and Solution of Probabilistically Constrained Optimization Problems
- A VaR Black–Litterman model for the construction of absolute return fund-of-funds
- Dual method for the solution of a one-stage stochastic programming problem with random RHS obeying a discrete probability distribution
- Convex Approximations of Chance Constrained Programs
- Concavity and efficient points of discrete distributions in probabilistic programming.
This page was built for publication: Risk-return trade-off with the scenario approach in practice: a case study in portfolio selection
