Although the stock market is complex and fluctuates, making prediction challenging, accurately forecasting stock prices is crucial for investors to make informed decisions based on past performance. Hence, a suitable prediction model can significantly help investors take action in a prudent manner. In this paper, we design a stock price prediction model using LSTM (Long Short-Term Memory) and compare its performance on Maotai stock with other models based on the RMSE value. In comparison, the LSTM model outperforms other models with an RMSE value. Therefore, this model can help investors forecast stock prices more accurately to some extent.

Jiahui Teng, Jun Feng, Yukun Huang, Xinyi Li, Yiyang Tao, Jinming Xu. Stock Price Prediction Using LSTM: A Case Study of Maotai. Academic Journal of Business & Management(2025), Vol. 7, Issue 4: 39-43. https://doi.org/10.25236/AJBM.2025.070405.

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