Investment Strategy Based on LSTM Network and PSO Model

作者：Kunqi Han, Wei Zhang, Yuzi Zhang · 发表于：Atlantis Highlights in Intelligent Systems/Atlantis highlights in intelligent systems · 年份：2022 · DOI：10.2991/978-94-6463-010-7_34 · 研究领域：Advanced Decision-Making Techniques

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.