A Closer Look at the Minimum-Variance Portfolio Optimization Model

Recently, by imposing the regularization term to objective function or additional norm constraint to portfolio weights, a number of alternative portfolio strategies have been proposed to improve the empirical performance of the minimum-variance portfolio. In this paper, we firstly examine the relati...

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Main Author:	Zhifeng Dai
Format:	Article
Language:	English
Published:	Hindawi Limited 2019-01-01
Series:	Mathematical Problems in Engineering
Online Access:	http://dx.doi.org/10.1155/2019/1452762

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spelling	doaj-6a69610aad6e43f7aadfea267a56c93e2020-11-24T20:51:53ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472019-01-01201910.1155/2019/14527621452762A Closer Look at the Minimum-Variance Portfolio Optimization ModelZhifeng Dai0College of Mathematics and Statistics, Changsha University of Science and Technology, Changsha 410114, ChinaRecently, by imposing the regularization term to objective function or additional norm constraint to portfolio weights, a number of alternative portfolio strategies have been proposed to improve the empirical performance of the minimum-variance portfolio. In this paper, we firstly examine the relation between the weight norm-constrained method and the objective function regularization method in minimum-variance problems by analyzing the Karush–Kuhn–Tucker conditions of their Lagrangian functions. We give the range of parameters for the two models and the corresponding relationship of parameters. Given the range and manner of parameter selection, it will help researchers and practitioners better understand and apply the relevant portfolio models. We apply these models to construct optimal portfolios and test the proposed propositions by employing real market data.http://dx.doi.org/10.1155/2019/1452762
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Zhifeng Dai
spellingShingle	Zhifeng Dai A Closer Look at the Minimum-Variance Portfolio Optimization Model Mathematical Problems in Engineering
author_facet	Zhifeng Dai
author_sort	Zhifeng Dai
title	A Closer Look at the Minimum-Variance Portfolio Optimization Model
title_short	A Closer Look at the Minimum-Variance Portfolio Optimization Model
title_full	A Closer Look at the Minimum-Variance Portfolio Optimization Model
title_fullStr	A Closer Look at the Minimum-Variance Portfolio Optimization Model
title_full_unstemmed	A Closer Look at the Minimum-Variance Portfolio Optimization Model
title_sort	closer look at the minimum-variance portfolio optimization model
publisher	Hindawi Limited
series	Mathematical Problems in Engineering
issn	1024-123X 1563-5147
publishDate	2019-01-01
description	Recently, by imposing the regularization term to objective function or additional norm constraint to portfolio weights, a number of alternative portfolio strategies have been proposed to improve the empirical performance of the minimum-variance portfolio. In this paper, we firstly examine the relation between the weight norm-constrained method and the objective function regularization method in minimum-variance problems by analyzing the Karush–Kuhn–Tucker conditions of their Lagrangian functions. We give the range of parameters for the two models and the corresponding relationship of parameters. Given the range and manner of parameter selection, it will help researchers and practitioners better understand and apply the relevant portfolio models. We apply these models to construct optimal portfolios and test the proposed propositions by employing real market data.
url	http://dx.doi.org/10.1155/2019/1452762
work_keys_str_mv	AT zhifengdai acloserlookattheminimumvarianceportfoliooptimizationmodel AT zhifengdai closerlookattheminimumvarianceportfoliooptimizationmodel
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A Closer Look at the Minimum-Variance Portfolio Optimization Model

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