A Two-Timescale Neurodynamic Approach to Minimax Portfolio Optimization

Man Fai Leung, Jun Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

This paper is concerned with asset allocation based on two-timescale neurodynamic optimization. The portfolio optimization in classical mean-variance framework is reformulated as a minimax portfolio selection problem and a two-timescale neurodynamic approach is developed to solve the problem. The neurodynamic approach incorporates a recurrent neural network (RNN) operating on two different timescales. Computational results show the efficacy and performance of the developed approach to asset allocation.

Original languageEnglish
Title of host publication2021 11th International Conference on Information Science and Technology, ICIST 2021
Pages438-443
Number of pages6
ISBN (Electronic)9781665412667
DOIs
Publication statusPublished - 21 May 2021
Event11th International Conference on Information Science and Technology, ICIST 2021 - Chengdu, China
Duration: 21 May 202123 May 2021

Publication series

Name2021 11th International Conference on Information Science and Technology, ICIST 2021

Conference

Conference11th International Conference on Information Science and Technology, ICIST 2021
Country/TerritoryChina
CityChengdu
Period21/05/2123/05/21

Keywords

  • Asset allocation
  • minimax
  • neurodynamic optimization
  • recurrent neural networks
  • two-timescale

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