Yujiao Liu and Lin He and Duohui Li and Xiaozhao Luo and Guo Peng and Xiaoping Fan and Guang Sun (2020) Correlation Analysis of Chinese Pork Concept Stocks Based on Big Data. Artificial Intelligence and Security. pp. 475-486.
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Abstract
This article conducts an empirical study on the correlation between Chinese pork price and the fluctuation of the pork concept index. The first is to use Tushare financial data interface, crawler tools and other technologies to obtain initial data, then use machine learning SVM sentiment analysis to convert text data into structured data to pre-process and standardize the data, which is beneficial to SPSS.24 for correlation and multiple linear regression analysis. Finally came to the following conclusions: Firstly, the Chinese pork price has a significant positive correlation at the level of 0.01 with the pork concept index, and upstream and midstream companies in the pork industry chain are more affected by changes in pork prices. Therefore, investors can focus on pork price changes to guide investment decisions. Secondly, from the long-term analysis, investor sentiment has little effect on the stock price of pork stocks. Thirdly, weak correlation between Chinese macroeconomic factors and Chinese pork stock price.
| Item Type: | Article |
|---|---|
| Keyword: | Big data technology, Correlation analysis, SVM sentiment analysis, Pork sector index |
| Subjects: | Q Science > Q Science (General) T Technology > T Technology (General) |
| Depositing User: | SITI AZIZAH BINTI IDRIS - |
| Date Deposited: | 09 Nov 2020 16:09 |
| Last Modified: | 09 Nov 2020 16:09 |
| URI: | https://eprints.ums.edu.my/id/eprint/26273 |
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