STLGOct 20, 2024

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

arXiv:2411.05790v134 citationsh-index: 8Proceedings of the International Conference on Digital Economy, Blockchain and Artificial Intelligence
Originality Synthesis-oriented
AI Analysis

This is an incremental study for investors seeking improved decision-making in financial markets.

The paper tackled stock price prediction by comparing LSTM, GRU, and Transformer models on Tesla data from 2015 to 2024, finding that the LSTM model achieved 94% accuracy.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes