A deep learning approach for financial market prediction: utilization of Google trends and keywords

Min Hsuan Fan, Mu Yen Chen, En Chih Liao

研究成果: Article同行評審

3 引文 斯高帕斯(Scopus)

摘要

This study used the amount of Internet search on Google Trend and analyzed the correlation between the search volume on Google Trend and Taiwan Weighted Stock Index. The keyword search volume provided by Google Trend was used in the correlation test and the unit root test. Then, the keywords obtained were analyzed in two experiments—first, machine learning, and second, search trend. After empirical analysis, it was found that neural network in experiment one performed better than support vector machine and decision trees. Therefore, neural network was selected to compare with the search trend in the second experiment. Through comparative analysis of calculation of return values, it was found that the return value in search trend is higher than that of the neural network. Therefore, this paper revealed that there was a correlation between using company names of Taiwan 50 Index as search keywords and the rise and fall of TAIEX index.

原文English
頁(從 - 到)207-216
頁數10
期刊Granular Computing
6
發行號1
DOIs
出版狀態Published - 2021 一月

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦科學應用
  • 資訊系統

指紋

深入研究「A deep learning approach for financial market prediction: utilization of Google trends and keywords」主題。共同形成了獨特的指紋。

引用此