PREDICTING STOCK PRICES IN THE STOCK MARKET USING LONG-SHORT TERM MEMORY MODELS, CONVOLUTIONAL NEURAL NETWORK AND SUPPORT VECTOR MACHINE
Abstract
The stock market is always fluctuating and does not follow a specific rule. Predicting stock prices on the stock market is a difficult task and attracts the attention of many investors, experts, and scientists. In this article, we deploy three machine learning models Long-Short Term Memory, Convolutional Neural Network and Support Vector Machine to predict the closing and opening prices of three different companies over about 10 years (from July 2013 to July 2023). The results show that the Long-Short Term Memory model gives better prediction results and competes with the prediction results of the Convolutional Neural Network and Support Vector Machine models.
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