A new global algorithm for factor-risk-constrained mean-variance portfolio selection

DOI10.1007/s10898-022-01218-zMaRDI QIDQ6064034

Jianzhen Liu, Xianye Zhang, Huixian Wu, Hezhi Luo

Publication date: 8 November 2023

Published in: Journal of Global Optimization (Search for Journal in Brave)

global optimization branch-and-bound semi-definite relaxation successive convex optimization factor-risk-constrained mean-variance portfolio selection

Mathematics Subject Classification ID

Polyhedral combinatorics, branch-and-bound, branch-and-cut (90C57) Nonconvex programming, global optimization (90C26) Quadratic programming (90C20)

Cites Work

Unnamed Item
Unnamed Item
Convex relaxations of non-convex mixed integer quadratically constrained programs: projected formulations
A new branch-and-cut algorithm for non-convex quadratic programming via alternative direction method and semidefinite relaxation
Globally solving box-constrained nonconvex quadratic programs with semidefinite-based finite branch-and-bound
Shortfall as a risk measure: properties, optimization and applications
Solving a class of linearly constrained indefinite quadratic problems by DC algorithms
On the complexity of approximating a KKT point of quadratic programming
New global algorithms for quadratic programming with a few negative eigenvalues based on alternative direction method and convex relaxation
Globally solving nonconvex quadratic programming problems via completely positive programming
A simplicial branch-and-bound algorithm for solving quadratically constrained quadratic programs
A branch and cut algorithm for nonconvex quadratically constrained quadratic programming
An efficient global algorithm for worst-case linear optimization under uncertainties based on nonlinear semidefinite relaxation
Active allocation of systematic risk and control of risk sensitivity in portfolio optimization
Variations and extension of the convex-concave procedure
A finite branch-and-bound algorithm for nonconvex quadratic programming via semidefinite relaxations
On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
A sensitive-eigenvector based global algorithm for quadratically constrained quadratic programming
Optimal Dynamic Portfolio Selection: Multiperiod Mean-Variance Formulation
Optimal trade-off portfolio selection between total risk and maximum relative marginal risk^†
Sequential Convex Approximations to Joint Chance Constrained Programs: A Monte Carlo Approach
DC Programming and DCA for General DC Programs
Necessary conditions for ε-optimality
Variational Analysis
Using SeDuMi 1.02, A Matlab toolbox for optimization over symmetric cones
An Efficient Global Algorithm for Single-Group Multicast Beamforming
Portfolio selection with the effect of systematic risk diversification: formulation and accelerated gradient algorithm
Nonlinear Optimization by Successive Linear Programming
Complexity Results and Effective Algorithms for Worst-Case Linear Optimization Under Uncertainties
Risk Control Over Bankruptcy in Dynamic Portfolio Selection: A Generalized Mean-Variance Formulation
Line Search Filter Methods for Nonlinear Programming: Motivation and Global Convergence
Line Search Filter Methods for Nonlinear Programming: Local Convergence
Portfolio selection with marginal risk control
Common risk factors in the returns on stocks and bonds
On the Sequential Quadratically Constrained Quadratic Programming Methods

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