Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022)

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Investment Strategy Based on LSTM Network and PSO Model

Authors
Kunqi Han1, Wei Zhang2, *, Yuzi Zhang3
1College of Energy and Electrical Engineering, Hohai University, 8th Focheng West Road, Nanjing, People’s Republic of China
2Business School of Hohai University, 8th Focheng West Road, Nanjing, People’s Republic of China
3School of Public, Administration of Hohai University, 8th Focheng West Road, Nanjing, People’s Republic of China
*Corresponding author. Email: 1907020220@hhu.edu.cn
Corresponding Author
Wei Zhang
Available Online 2 December 2022.
DOI
10.2991/978-94-6463-010-7_34How to use a DOI?
Keywords
Investment Strategy; LSTM Network; Sharpe Rate; Particle Swarm Optimization
Abstract

With the rapid development of economy, many people are keen to buy and sell unstable financial products to maximize their interests. This paper proposes an investment strategy based on Sharp ratio and neural network particle swarm optimization, which is able to predict the best time to buy, hold and sell various financial products through artificial intelligence based on the price flow data of the products over the past period of time. Taking cash, gold and bitcoin as examples, this paper conducts empirical research on the algorithm and obtains the final profit of the optimal investment scheme. Then, through the sensitivity analysis, we found that as the transaction fee increases, the number of transactions of gold and Bitcoin decreases significantly, and the value decreases. On the contrary, there is the same theory, which proves that our model is very good. However, the model proposed in this paper still has some shortcomings. In summary, although the model proposed in this paper has some shortcomings, its accuracy and stability are enough to solve this problem, so it can be explained again the accuracy of the model proposed in this paper.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
2 December 2022
ISBN
978-94-6463-010-7
ISSN
2589-4919
DOI
10.2991/978-94-6463-010-7_34How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Kunqi Han
AU  - Wei Zhang
AU  - Yuzi Zhang
PY  - 2022
DA  - 2022/12/02
TI  - Investment Strategy Based on LSTM Network and PSO Model
BT  - Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022)
PB  - Atlantis Press
SP  - 330
EP  - 339
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-010-7_34
DO  - 10.2991/978-94-6463-010-7_34
ID  - Han2022
ER  -