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Journal of Statistical Theory and Practice

, Volume 8, Issue 3, pp 423–438 | Cite as

Estimation of Optimal Portfolio Weights Under Parameter Uncertainty and User-Specified Constraints: A Perturbation Method

  • Christopher J. Bennett
  • Ričardas Zitikis
Article

Abstract

We propose a novel methodology for constructing optimal portfolios in the presence of (i) model parameter uncertainty and (ii) user-specified constraints on the portfolio weights. This is a challenging problem, in large part because the constraint conditions generally preclude the derivation of closed-form solutions even in the absence of parameter uncertainty. Yet, in this article, we succeed in producing a practical solution, which is based on a herein proposed technique that we call a “perturbation method.” The method relies on a specially devised resampling procedure, whose performance is shown in simulations to compare favorably to other methods from the literature on portfolio optimization.

Keywords

Portfolio selection Optimization Risk Bootstrap Resampling 

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Copyright information

© Grace Scientific Publishing 2014

Authors and Affiliations

  1. 1.Department of EconomicsVanderbilt UniversityNashvilleUSA
  2. 2.Department of Statistical and Actuarial SciencesUniversity of Western OntarioLondonCanada

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