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 language | English |
|---|---|
| Title of host publication | 11th International Conference on Information Science and Technology (ICIST) |
| Publisher | IEEE |
| Pages | 438-443 |
| ISBN (Electronic) | 978-1-6654-1266-7 |
| ISBN (Print) | 978-1-6654-2941-2 |
| DOIs | |
| Publication status | Published - May 2021 |
| Event | 11th International Conference on Information Science and Technology, ICIST 2021 - Chengdu, China Duration: 21 May 2021 → 23 May 2021 https://conference.cs.cityu.edu.hk/icist/ |
Publication series
| Name | International Conference on Information Science and Technology, ICIST |
|---|---|
| ISSN (Print) | 2164-4357 |
| ISSN (Electronic) | 2573-3311 |
Conference
| Conference | 11th International Conference on Information Science and Technology, ICIST 2021 |
|---|---|
| Place | China |
| City | Chengdu |
| Period | 21/05/21 → 23/05/21 |
| Internet address |
Research Keywords
- Asset allocation
- minimax
- neurodynamic optimization
- recurrent neural networks
- two-timescale
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