Variable neighborhood search heuristic for nonconvex portfolio optimization
Само за регистроване кориснике
2019
Аутори
Bačević, AndrijanaVilimonović, Nemanja
Dabić, Igor
Petrović, Jakov
Damnjanović, Darko
Džamić, Dušan
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Чланак у часопису (Објављена верзија)
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Метаподаци
Приказ свих података о документуАпстракт
In this article we consider a portfolio optimization problem under multiple real-world constraints, such as: cardinality constraints, tracking error, active share, and turnover. We propose a heuristic based on variable neighborhood search (VNS) that effectively addresses additional constraints that introduce non-convexities. In the VNS-based heuristic, several neighborhood structures are introduced and fast local search is implemented. We develop a VNS portfolio rebalancing framework (VNS-PRF) with two rebalance strategies. Data sets provided by a financial investment firm are used to evaluate the validity and reliability of the proposed VNS-PRF. Computational experiments and different portfolio performance measures indicate that our approach is able to obtain solutions with competitive quality and can be applied on large-scale data sets.
Извор:
Engineering Economist, 2019, 64, 3, 254-274Издавач:
- Taylor & Francis Inc, Philadelphia
Финансирање / пројекти:
- Математички Модели и Методе Оптимизације Великих Система (RS-MESTD-Basic Research (BR or ON)-174010)
DOI: 10.1080/0013791X.2019.1619888
ISSN: 0013-791X
WoS: 000475248200001
Scopus: 2-s2.0-85067507558
Институција/група
Fakultet organizacionih naukaTY - JOUR AU - Bačević, Andrijana AU - Vilimonović, Nemanja AU - Dabić, Igor AU - Petrović, Jakov AU - Damnjanović, Darko AU - Džamić, Dušan PY - 2019 UR - https://rfos.fon.bg.ac.rs/handle/123456789/1950 AB - In this article we consider a portfolio optimization problem under multiple real-world constraints, such as: cardinality constraints, tracking error, active share, and turnover. We propose a heuristic based on variable neighborhood search (VNS) that effectively addresses additional constraints that introduce non-convexities. In the VNS-based heuristic, several neighborhood structures are introduced and fast local search is implemented. We develop a VNS portfolio rebalancing framework (VNS-PRF) with two rebalance strategies. Data sets provided by a financial investment firm are used to evaluate the validity and reliability of the proposed VNS-PRF. Computational experiments and different portfolio performance measures indicate that our approach is able to obtain solutions with competitive quality and can be applied on large-scale data sets. PB - Taylor & Francis Inc, Philadelphia T2 - Engineering Economist T1 - Variable neighborhood search heuristic for nonconvex portfolio optimization EP - 274 IS - 3 SP - 254 VL - 64 DO - 10.1080/0013791X.2019.1619888 UR - conv_2200 ER -
@article{ author = "Bačević, Andrijana and Vilimonović, Nemanja and Dabić, Igor and Petrović, Jakov and Damnjanović, Darko and Džamić, Dušan", year = "2019", abstract = "In this article we consider a portfolio optimization problem under multiple real-world constraints, such as: cardinality constraints, tracking error, active share, and turnover. We propose a heuristic based on variable neighborhood search (VNS) that effectively addresses additional constraints that introduce non-convexities. In the VNS-based heuristic, several neighborhood structures are introduced and fast local search is implemented. We develop a VNS portfolio rebalancing framework (VNS-PRF) with two rebalance strategies. Data sets provided by a financial investment firm are used to evaluate the validity and reliability of the proposed VNS-PRF. Computational experiments and different portfolio performance measures indicate that our approach is able to obtain solutions with competitive quality and can be applied on large-scale data sets.", publisher = "Taylor & Francis Inc, Philadelphia", journal = "Engineering Economist", title = "Variable neighborhood search heuristic for nonconvex portfolio optimization", pages = "274-254", number = "3", volume = "64", doi = "10.1080/0013791X.2019.1619888", url = "conv_2200" }
Bačević, A., Vilimonović, N., Dabić, I., Petrović, J., Damnjanović, D.,& Džamić, D.. (2019). Variable neighborhood search heuristic for nonconvex portfolio optimization. in Engineering Economist Taylor & Francis Inc, Philadelphia., 64(3), 254-274. https://doi.org/10.1080/0013791X.2019.1619888 conv_2200
Bačević A, Vilimonović N, Dabić I, Petrović J, Damnjanović D, Džamić D. Variable neighborhood search heuristic for nonconvex portfolio optimization. in Engineering Economist. 2019;64(3):254-274. doi:10.1080/0013791X.2019.1619888 conv_2200 .
Bačević, Andrijana, Vilimonović, Nemanja, Dabić, Igor, Petrović, Jakov, Damnjanović, Darko, Džamić, Dušan, "Variable neighborhood search heuristic for nonconvex portfolio optimization" in Engineering Economist, 64, no. 3 (2019):254-274, https://doi.org/10.1080/0013791X.2019.1619888 ., conv_2200 .