Portfolio Research Based on Neural Network and Multi-Objective Programming

DOI

10.2991/aebmr.k.191225.011How to use a DOI?

Keywords

portfolio, BP neural network, ROE (return on equity), multi-objective programming, benefit-risk ratio

Abstract

In financial investment, risk and benefit coexist. How to balance the benefits and risks and find the optimal investment portfolio is a key issue to be considered by investors. In this research, BP neural network is used to predict the future return on equity (ROE) of asset; a multi-objective programming model of investment portfolio is established on the basis of Markowitz’s portfolio investment theory; to select the optimal investment portfolio, a comparison is made on the benefit-risk ratio of the investment portfolio with the smallest risk and at different income levels; in addition, an empirical analysis is made on the basis of the quarterly ROE data of 5 stocks during 2002-2017.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Rongjie Jian
AU  - Tingting Ni
PY  - 2020
DA  - 2020/01/07
TI  - Portfolio Research Based on Neural Network and Multi-Objective Programming
BT  - Proceedings of the 5th International Conference on Economics, Management, Law and Education (EMLE 2019)
PB  - Atlantis Press
SP  - 56
EP  - 62
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.191225.011
DO  - 10.2991/aebmr.k.191225.011
ID  - Jian2020
ER  -