A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems

In this paper, we investigate a multi-period portfolio selection problem with a comprehensive set of real-world trading constraints as well as market random uncertainty in terms of asset prices. We formulate the problem into a two-stage stochastic mixed-integer program (SMIP) with recourse. The set...

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Main Authors: He, Fang, Qu, Rong
Format: Article
Published: Elsevier 2014
Subjects:
Online Access:https://eprints.nottingham.ac.uk/28273/
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author He, Fang
Qu, Rong
author_facet He, Fang
Qu, Rong
author_sort He, Fang
building Nottingham Research Data Repository
collection Online Access
description In this paper, we investigate a multi-period portfolio selection problem with a comprehensive set of real-world trading constraints as well as market random uncertainty in terms of asset prices. We formulate the problem into a two-stage stochastic mixed-integer program (SMIP) with recourse. The set of constraints is modelled as mixed-integer program, while a set of decision variables to rebalance the portfolio in multiple periods is explicitly introduced as the recourse variables in the second stage of stochastic program. Although the combination of stochastic program and mixed-integer program leads to computational challenges in finding solutions to the problem, the proposed SMIP model provides an insightful and flexible description of the problem. The model also enables the investors to make decisions subject to real-world trading constraints and market uncertainty. To deal with the computational difficulty of the proposed model, a simplification and hybrid solution method is applied in the paper. The simplification method aims to eliminate the difficult constraints in the model, resulting into easier sub-problems compared to the original one. The hybrid method is developed to integrate local search with Branch-and-Bound (B&B) to solve the problem heuristically. We present computational results of the hybrid approach to analyse the performance of the proposed method. The results illustrate that the hybrid method can generate good solutions in a reasonable amount of computational time. We also compare the obtained portfolio values against an index value to illustrate the performance and strengths of the proposed SMIP model. Implications of the model and future work are also discussed.
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spelling nottingham-282732020-05-04T16:58:23Z https://eprints.nottingham.ac.uk/28273/ A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems He, Fang Qu, Rong In this paper, we investigate a multi-period portfolio selection problem with a comprehensive set of real-world trading constraints as well as market random uncertainty in terms of asset prices. We formulate the problem into a two-stage stochastic mixed-integer program (SMIP) with recourse. The set of constraints is modelled as mixed-integer program, while a set of decision variables to rebalance the portfolio in multiple periods is explicitly introduced as the recourse variables in the second stage of stochastic program. Although the combination of stochastic program and mixed-integer program leads to computational challenges in finding solutions to the problem, the proposed SMIP model provides an insightful and flexible description of the problem. The model also enables the investors to make decisions subject to real-world trading constraints and market uncertainty. To deal with the computational difficulty of the proposed model, a simplification and hybrid solution method is applied in the paper. The simplification method aims to eliminate the difficult constraints in the model, resulting into easier sub-problems compared to the original one. The hybrid method is developed to integrate local search with Branch-and-Bound (B&B) to solve the problem heuristically. We present computational results of the hybrid approach to analyse the performance of the proposed method. The results illustrate that the hybrid method can generate good solutions in a reasonable amount of computational time. We also compare the obtained portfolio values against an index value to illustrate the performance and strengths of the proposed SMIP model. Implications of the model and future work are also discussed. Elsevier 2014-12-24 Article PeerReviewed He, Fang and Qu, Rong (2014) A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems. Information Sciences, 289 . pp. 190-205. ISSN 1872-6291 Stochastic programming; Hybrid algorithm; Branch-and-Bound; Local search; Portfolio selection problems http://www.sciencedirect.com/science/article/pii/S0020025514008251 doi:10.1016/j.ins.2014.08.028 doi:10.1016/j.ins.2014.08.028
spellingShingle Stochastic programming; Hybrid algorithm; Branch-and-Bound; Local search; Portfolio selection problems
He, Fang
Qu, Rong
A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems
title A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems
title_full A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems
title_fullStr A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems
title_full_unstemmed A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems
title_short A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems
title_sort two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems
topic Stochastic programming; Hybrid algorithm; Branch-and-Bound; Local search; Portfolio selection problems
url https://eprints.nottingham.ac.uk/28273/
https://eprints.nottingham.ac.uk/28273/
https://eprints.nottingham.ac.uk/28273/