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Variable neighborhood search heuristic for nonconvex portfolio optimization

Author

Listed:
  • Andrijana Bačević
  • Nemanja Vilimonović
  • Igor Dabić
  • Jakov Petrović
  • Darko Damnjanović
  • Dušan Džamić

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.

Suggested Citation

  • Andrijana Bačević & Nemanja Vilimonović & Igor Dabić & Jakov Petrović & Darko Damnjanović & Dušan Džamić, 2019. "Variable neighborhood search heuristic for nonconvex portfolio optimization," The Engineering Economist, Taylor & Francis Journals, vol. 64(3), pages 254-274, July.
    • Handle: RePEc:taf:uteexx:v:64:y:2019:i:3:p:254-274
    DOI: 10.1080/0013791X.2019.1619888
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