Comparative Analysis of LSTM, GRU, and Transformer Models for Stock Price Prediction

Jue Xiao, Tingting Deng, Shuochen Bi
10/20/2024
q-fin.STcs.LG

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Abstract

In recent fast-paced financial markets, investors constantly seek ways to gain an edge and make informed decisions. Although achieving perfect accuracy in stock price predictions remains elusive, artificial intelligence (AI) advancements have significantly enhanced our ability to analyze historical data and identify potential trends. This paper takes AI driven stock price trend prediction as the core research, makes a model training data set of famous Tesla cars from 2015 to 2024, and compares LSTM, GRU, and Transformer Models. The analysis is more consistent with the model of stock trend prediction, and the experimental results show that the accuracy of the LSTM model is 94%. These methods ultimately allow investors to make more informed decisions and gain a clearer insight into market behaviors.

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Cite this paper

@article{xiao2024comparative,
  title  = {Comparative Analysis of LSTM, GRU, and Transformer Models for Stock Price Prediction},
  author = {Jue Xiao and Tingting Deng and Shuochen Bi},
  year   = {2024},
  eprint = {2411.05790},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2411.05790v1}
}

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