Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/178257 
Year of Publication: 
2015
Citation: 
[Journal:] Operations Research Perspectives [ISSN:] 2214-7160 [Volume:] 2 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2015 [Pages:] 133-136
Publisher: 
Elsevier, Amsterdam
Abstract: 
The Markowitz mean–variance portfolio optimization problem is a quadratic programming problem whose first-order conditions require the solution of a linear system. It is well known that the optimal portfolio weights are sensitive to parameter estimates, particularly the mean return vector. This has generally been attributed to the interaction of estimation error and optimization. In this paper we present some examples that suggest the linear system produced by the first-order conditions is ill-conditioned and it is this property that gives rise to the sensitivity of the optimal weights.
Subjects: 
Portfolio optimization
Sensitivity
Matrix condition
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.