Sparse Markowitz portfolio selection by using stochastic linear complementarity approach
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Publication:1716964
DOI10.3934/jimo.2017059zbMath1412.90098OpenAlexW2667024645MaRDI QIDQ1716964
Publication date: 5 February 2019
Published in: Journal of Industrial and Management Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3934/jimo.2017059
convergence analysisstochastic programmingsample average approximationsparse linear complimentarily problemsparse Markowitz portfolio selection
Applications of mathematical programming (90C90) Stochastic programming (90C15) Portfolio theory (91G10)
Related Items (3)
Lifted stationary points of sparse optimization with complementarity constraints ⋮ Robust multi-period and multi-objective portfolio selection ⋮ On Monte-Carlo methods in convex stochastic optimization
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Cites Work
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- Sparse solutions of linear complementarity problems
- Monte Carlo methods for mean-risk optimization and portfolio selection
- Smoothing methods for nonsmooth, nonconvex minimization
- Algorithm for cardinality-constrained quadratic optimization
- Cardinality constrained portfolio selection problem: a completely positive programming approach
- A new method for mean-variance portfolio optimization with cardinality constraints
- An efficient optimization approach for a cardinality-constrained index tracking problem
- Optimal Cardinality Constrained Portfolio Selection
- Improving the Performance of MIQP Solvers for Quadratic Programs with Cardinality and Minimum Threshold Constraints: A Semidefinite Program Approach
- An Augmented Lagrangian Method for Non-Lipschitz Nonconvex Programming
- Sparse and stable Markowitz portfolios
- An Exact Solution Approach for Portfolio Optimization Problems Under Stochastic and Integer Constraints
- A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms
- A Quadratically Convergent Newton Method for Computing the Nearest Correlation Matrix
- Decoding by Linear Programming
- Constraint Qualifications and Necessary Optimality Conditions for Optimization Problems with Variational Inequality Constraints
- A survey of subdifferential calculus with applications
- Sparse Approximate Solutions to Linear Systems
- Positive-Definite ℓ1-Penalized Estimation of Large Covariance Matrices
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