l1-Regularization for multi-period portfolio selection

In this work we present a model for the solution of the multi-period portfolio selection problem. The model is based on a time consistent dynamic risk measure. We apply l 1 -regularization to stabilize the solution process and to obtain sparse solutions, which allow one to reduce holding costs. The...

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Bibliographic Details
Published inAnnals of operations research Vol. 294; no. 1-2; pp. 75 - 86
Main Authors Corsaro, Stefania, De Simone, Valentina, Marino, Zelda, Perla, Francesca
Format Journal Article
LanguageEnglish
Published New York Springer US 01.11.2020
Springer Nature B.V
Subjects
Business and Management
Combinatorics
Equality
Iterative methods
Operations research
Operations Research/Decision Theory
Optimization
Portfolio management
Regularization
S.i.: Balcor-2017
Sparsity
Theory of Computation
Portfolio optimization
Time consistency
90C30
65K05
91G10
norm
Constrained optimization
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Summary:In this work we present a model for the solution of the multi-period portfolio selection problem. The model is based on a time consistent dynamic risk measure. We apply l 1 -regularization to stabilize the solution process and to obtain sparse solutions, which allow one to reduce holding costs. The core problem is a nonsmooth optimization one, with equality constraints. We present an iterative procedure based on a modified Bregman iteration, that adaptively sets the value of the regularization parameter in order to produce solutions with desired financial properties. We validate the approach showing results of tests performed on real data.
ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-019-03308-w