Actuarial Risk Matrices: The Nearest Positive Semidefinite Matrix Problem

DOI10.1080/10920277.2017.1317273zbMath1414.91177OpenAlexW2756689669MaRDI QIDQ5379243

Helena Šmigoc, Adrian O'Hagan, Stefan Cutajar

Publication date: 28 May 2019

Published in: North American Actuarial Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10920277.2017.1317273

zbMATH Keywords

semidefinite programmingalternating projections methodshrinking methodactuarial risk correlation matricesnearest positive semidefinite matrix problem

Mathematics Subject Classification ID

Uses Software

• Matlab
• SeDuMi
• Mosek

Cites Work

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• Computing the nearest correlation matrix--a problem from finance
• A successive projection method
• On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds
• An interior-point method for approximate positive semidefinite completions
• Restoring Definiteness via Shrinking, with an Application to Correlation Matrices with a Fixed Block
• Computing a Nearest Correlation Matrix with Factor Structure
• An Algorithm for Restricted Least Squares Regression
• Semidefinite optimization
• Matrix Analysis
• A Bisection Method for Measuring the Distance of a Stable Matrix to the Unstable Matrices
• Geometric Programming: Methods, Computations and Applications
• The rate of convergence of dykstra's cyclic projections algorithm: The polyhedral case
• Using SeDuMi 1.02, A Matlab toolbox for optimization over symmetric cones
• Functional Operators (AM-21), Volume 1

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