Solving realistic portfolio optimization problems via metaheuristics: a survey and an example

Jana Doering; Angel A. Juan; Renatas Kizys; Angels Fito; Laura Calvet

doi:10.1007/978-3-319-40506-3_3

Solving realistic portfolio optimization problems via metaheuristics: a survey and an example

Jana Doering, Angel A. Juan, Renatas Kizys, Angels Fito, Laura Calvet

Open University of Catalonia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

639 Downloads (Pure)

Abstract

Computational finance has become one of the emerging application fields of metaheuristic algorithms. In particular, these optimization methods are quickly becoming the solving approach alternative when dealing with realistic versions of financial problems, such as the popular portfolio optimization problem (POP). This paper reviews the scientific literature on the use of metaheuristics for solving rich versions of the POP and illustrates, with a numerical example, the capacity of these methods to provide high-quality solutions to complex POPs in short computing times, which might be a desirable property of solving methods that support real-time decision making.

Original language	English
Title of host publication	Modeling and Simulation in Engineering, Economics and Management
Subtitle of host publication	International Conference, MS 2016, Teruel, Spain, July 4-5, 2016, Proceedings
Publisher	Springer International Publishing
Pages	22-30
Volume	254
ISBN (Electronic)	978-3-319-40506-3
ISBN (Print)	978-3-319-40505-6
DOIs	https://doi.org/10.1007/978-3-319-40506-3_3
Publication status	Published - 26 Jun 2016
Event	International Conference on Modeling and Simulation in Engineering, Economics and Management: MS 2016 - Teruel, Spain Duration: 4 Jul 2016 → 5 Jul 2016 http://amsemodelling.com/conferences/teruel2016.html

Publication series

Name	Lecture Notes in Business Information Processing
Volume	254
ISSN (Print)	1865-1348

Conference

Conference	International Conference on Modeling and Simulation in Engineering, Economics and Management
Country/Territory	Spain
City	Teruel
Period	4/07/16 → 5/07/16
Internet address	http://amsemodelling.com/conferences/teruel2016.html

Keywords

Portfolio optimization
SimILS
Metaheuristics
Simulation

Access to Document

10.1007/978-3-319-40506-3_3

KIZYS_2016_cright_MSEEM_Solving Realistic Portfolio Optimization Problems via Metaheuristics
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-40506-3_3.
Accepted author manuscript (Post-print), 377 KB

Cite this

Doering, J., Juan, A. A., Kizys, R., Fito, A., & Calvet, L. (2016). Solving realistic portfolio optimization problems via metaheuristics: a survey and an example. In Modeling and Simulation in Engineering, Economics and Management: International Conference, MS 2016, Teruel, Spain, July 4-5, 2016, Proceedings (Vol. 254, pp. 22-30). (Lecture Notes in Business Information Processing; Vol. 254). Springer International Publishing. https://doi.org/10.1007/978-3-319-40506-3_3

Doering, Jana ; Juan, Angel A. ; Kizys, Renatas et al. / Solving realistic portfolio optimization problems via metaheuristics : a survey and an example. Modeling and Simulation in Engineering, Economics and Management: International Conference, MS 2016, Teruel, Spain, July 4-5, 2016, Proceedings. Vol. 254 Springer International Publishing, 2016. pp. 22-30 (Lecture Notes in Business Information Processing).

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abstract = "Computational finance has become one of the emerging application fields of metaheuristic algorithms. In particular, these optimization methods are quickly becoming the solving approach alternative when dealing with realistic versions of financial problems, such as the popular portfolio optimization problem (POP). This paper reviews the scientific literature on the use of metaheuristics for solving rich versions of the POP and illustrates, with a numerical example, the capacity of these methods to provide high-quality solutions to complex POPs in short computing times, which might be a desirable property of solving methods that support real-time decision making.",

keywords = "Portfolio optimization, SimILS, Metaheuristics, Simulation",

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Doering, J, Juan, AA, Kizys, R, Fito, A & Calvet, L 2016, Solving realistic portfolio optimization problems via metaheuristics: a survey and an example. in Modeling and Simulation in Engineering, Economics and Management: International Conference, MS 2016, Teruel, Spain, July 4-5, 2016, Proceedings. vol. 254, Lecture Notes in Business Information Processing, vol. 254, Springer International Publishing, pp. 22-30, International Conference on Modeling and Simulation in Engineering, Economics and Management, Teruel, Spain, 4/07/16. https://doi.org/10.1007/978-3-319-40506-3_3

Solving realistic portfolio optimization problems via metaheuristics: a survey and an example. / Doering, Jana; Juan, Angel A.; Kizys, Renatas et al.
Modeling and Simulation in Engineering, Economics and Management: International Conference, MS 2016, Teruel, Spain, July 4-5, 2016, Proceedings. Vol. 254 Springer International Publishing, 2016. p. 22-30 (Lecture Notes in Business Information Processing; Vol. 254).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Solving realistic portfolio optimization problems via metaheuristics

T2 - International Conference on Modeling and Simulation in Engineering, Economics and Management

AU - Doering, Jana

AU - Juan, Angel A.

AU - Kizys, Renatas

AU - Fito, Angels

AU - Calvet, Laura

PY - 2016/6/26

Y1 - 2016/6/26

N2 - Computational finance has become one of the emerging application fields of metaheuristic algorithms. In particular, these optimization methods are quickly becoming the solving approach alternative when dealing with realistic versions of financial problems, such as the popular portfolio optimization problem (POP). This paper reviews the scientific literature on the use of metaheuristics for solving rich versions of the POP and illustrates, with a numerical example, the capacity of these methods to provide high-quality solutions to complex POPs in short computing times, which might be a desirable property of solving methods that support real-time decision making.

AB - Computational finance has become one of the emerging application fields of metaheuristic algorithms. In particular, these optimization methods are quickly becoming the solving approach alternative when dealing with realistic versions of financial problems, such as the popular portfolio optimization problem (POP). This paper reviews the scientific literature on the use of metaheuristics for solving rich versions of the POP and illustrates, with a numerical example, the capacity of these methods to provide high-quality solutions to complex POPs in short computing times, which might be a desirable property of solving methods that support real-time decision making.

KW - Portfolio optimization

KW - SimILS

KW - Metaheuristics

KW - Simulation

U2 - 10.1007/978-3-319-40506-3_3

DO - 10.1007/978-3-319-40506-3_3

M3 - Conference contribution

SN - 978-3-319-40505-6

VL - 254

T3 - Lecture Notes in Business Information Processing

SP - 22

EP - 30

BT - Modeling and Simulation in Engineering, Economics and Management

PB - Springer International Publishing

Y2 - 4 July 2016 through 5 July 2016

ER -

Doering J, Juan AA, Kizys R, Fito A, Calvet L. Solving realistic portfolio optimization problems via metaheuristics: a survey and an example. In Modeling and Simulation in Engineering, Economics and Management: International Conference, MS 2016, Teruel, Spain, July 4-5, 2016, Proceedings. Vol. 254. Springer International Publishing. 2016. p. 22-30. (Lecture Notes in Business Information Processing). doi: 10.1007/978-3-319-40506-3_3

Solving realistic portfolio optimization problems via metaheuristics: a survey and an example

Abstract

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Keywords

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