Linear statistical inference for global and local minimum variance portfolios

DOI10.1007/s00362-008-0170-zzbMath1247.91171OpenAlexW2058398795MaRDI QIDQ451456

Gabriel Frahm

Publication date: 23 September 2012

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10419/26739

zbMATH Keywords

portfolio optimizationestimation risklinear regression theoryMarkowitz portfoliominimum variance portfoliotop down investment

Mathematics Subject Classification ID

Statistical methods; risk measures (91G70) Parametric hypothesis testing (62F03) Exact distribution theory in statistics (62E15) Portfolio theory (91G10)

Related Items (7)

A test on the location of the tangency portfolio on the set of feasible portfolios ⋮ Statistical Inference for High-Dimensional Global Minimum Variance Portfolios ⋮ Another look at portfolio optimization with mental accounts ⋮ On the market price of risk ⋮ Replica approach to mean-variance portfolio optimization ⋮ Analytic solution to variance optimization with no short positions ⋮ Portfolio selection: shrinking the time-varying inverse conditional covariance matrix

Cites Work

• Distributional properties of portfolio weights
• Portfolio Choice and Estimation Risk. A Comparison of Bayesian to Heuristic Approaches
• An Exact Test for Multiple Inequality and Equality Constraints in the Linear Regression Model
• Likelihood Ratio Test, Wald Test, and Kuhn-Tucker Test in Linear Models with Inequality Constraints on the Regression Parameters
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