Applying Three Deep Learning Techniques to Predicting Stock Price

This study uses three deep learning techniques to predict stock prices, and takes Taiwan Semiconductor Manufacturing Company as the target. The results show that the prediction effect of support vector machine regression is the best, followed by the prediction of regression analysis, and then by the prediction of neural network analysis.The experimental results show that the model proposed in this study can outperform the traditional SVM regression model by producing, especially in lower prediction error and higher prediction accuracy. It can be concluded that the use of support vector machine regression can effectively discover the hidden information of the original data to improve the prediction results. Future research could expand the scope of the study to analyze multiple stocks or options.