@inproceedings{42393e0f46f64935a78c2f10c323f27e,
title = "Another Two-Timescale Duplex Neurodynamic Approach to Portfolio Selection",
abstract = "This paper is concerned with portfolio selection based on the Markowitz mean-variance framework using neurodynamic optimization. The portfolio optimization problem is formulated as a biconvex optimization problem. A two-timescale duplex neurodynamic approach is then applied for solving the profolio selection problem. The approach makes use of two recurrent neural networks (RNNs) which operate at different timescales for local search. A particle swarm optimization algorithm is employed to update the neuronal states of the two RNNs for global optima. Experimental results on four stock market datasets show the superior performance of the neurodynamic approach in terms of long-term expected returns.",
keywords = "Two-timescale, local search, neural networks, portfolio optimization",
author = "Leung, {Man Fai} and Jun Wang and Hangjun Che",
note = "Funding Information: This work is supported in part by the Research Grants Council of the Hong Kong Special Administrative Region of China (Grant 11202019), in part by the Laboratory for AI-Powered Financial Technologies, in part by the Fundamental Research Funds for the Central Universities (Grant No.SWU020006), in part by the National Natural Science Foundation of China (Grant No. 62003281), and in part by Hong Kong Metropolitan University Research Grant (No. 2020/1.4). Publisher Copyright: {\textcopyright} 2021 IEEE.; 11th International Conference on Intelligent Control and Information Processing, ICICIP 2021 ; Conference date: 03-12-2021 Through 07-12-2021",
year = "2021",
doi = "10.1109/ICICIP53388.2021.9642204",
language = "English",
series = "11th International Conference on Intelligent Control and Information Processing, ICICIP 2021",
pages = "387--391",
booktitle = "11th International Conference on Intelligent Control and Information Processing, ICICIP 2021",
}