Equal risk bounding is better than risk parity for portfolio selection

DOI10.1007/s10898-016-0477-6zbMath1411.91489OpenAlexW3122345351MaRDI QIDQ1675564

Fabio Tardella, Francesco Cesarone

Publication date: 2 November 2017

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

Full work available at URL: https://doi.org/10.1007/s10898-016-0477-6

zbMATH Keywords

portfolio optimizationrisk diversificationnonlinear 0-1 optimizationnon-convex quadratically constrained optimizationrisk parity

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Portfolio theory (91G10)

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On the exactness of the \(\varepsilon\)-constraint method for biobjective nonlinear integer programming ⋮ Portfolio optimization through a network approach: network assortative mixing and portfolio diversification ⋮ Risk budgeting portfolios from simulations ⋮ Almost exact risk budgeting with return forecasts for portfolio allocation ⋮ Risk parity with expectiles ⋮ Clustering and portfolio selection problems: a unified framework ⋮ A conjugate direction based simplicial decomposition framework for solving a specific class of dense convex quadratic programs ⋮ An optimization-diversification approach to portfolio selection

Cites Work

• Unnamed Item
• Unnamed Item
• Pseudo-Boolean optimization
• A polyhedral branch-and-cut approach to global optimization
• Linear vs. quadratic portfolio selection models with hard real-world constraints
• A new method for mean-variance portfolio optimization with cardinality constraints
• Least-squares approach to risk parity in portfolio selection

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