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Machine Learning and Artificial Intelligence Applied in the Research of the Emotions Impact on Forecasting
| Content Provider | Scilit |
|---|---|
| Author | Jiang, Yaokui Zuo, Yi Yang, Yudong |
| Copyright Year | 2021 |
| Description | Journal: Journal of Physics: Conference Series According to the behavioral finance theory, the psychology and behavior of investors in capital market have an important impact on the fluctuation of stock index. Therefore, this paper assumes that there is a certain internal mechanism between investor sentiment and stock index, which can predict the overall price change of the stock market. The text mining technology and sentiment analysis method can be used to generate a total of six categorypositive and negativeinvestor sentiment time series data, with three orders; The methods such as unit root test, Granger causality test and factor analysis are used to construct the composite index of SSE investor sentiment, and then the support vector machine and neural network are adopted to predict the stock market price changes and conduct the hypothesis verification. The results indicate that the SSE investor sentiment composite index constructed by using the text data of online stock market forum and stock transaction data can improve the accuracy of stock index trend prediction, which is conducive to better decision-making of the government, online platforms, listed companies, and investment entities. |
| Related Links | https://iopscience.iop.org/article/10.1088/1742-6596/1982/1/012052/pdf |
| ISSN | 17426588 |
| e-ISSN | 17426596 |
| DOI | 10.1088/1742-6596/1982/1/012052 |
| Journal | Journal of Physics: Conference Series |
| Issue Number | 1 |
| Volume Number | 1982 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2021-07-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Journal of Physics: Conference Series Decision Making Stock Index |
| Content Type | Text |
| Resource Type | Article |
| Subject | Physics and Astronomy |
