Stock Price Prediction using LSTM Model

Yifei Zhang

doi:10.54097/hset.v44i.7352

Authors

Yifei Zhang

DOI:

https://doi.org/10.54097/hset.v44i.7352

Keywords:

algorithms, predictions, forecasts, LSTM model.

Abstract

Stock prices represent the development prospects of a company and play an important role in predicting future economic trends. With the development of deep learning, in this paper, our goal is to predict stock prices through deep learning algorithms. The author uses the Long-Short Term Memory (LSTM) network to make predictions by predicting the real stock prices of Google, Amazon, and Apple, and gives the visualization results of the training and testing stages. The results validate the effectiveness of the LSTM model.

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