The Influence and Prediction of Industry Asset Price Fluctuation Based on The LSTM Model and Investor Sentiment. (21st March 2022)
- Record Type:
- Journal Article
- Title:
- The Influence and Prediction of Industry Asset Price Fluctuation Based on The LSTM Model and Investor Sentiment. (21st March 2022)
- Main Title:
- The Influence and Prediction of Industry Asset Price Fluctuation Based on The LSTM Model and Investor Sentiment
- Authors:
- Hu, Wenxiu
Liu, Huan
Ma, Xiaoqiang
Bai, Xiong - Other Names:
- Che Hangjun Academic Editor.
- Abstract:
- Abstract : In a real-world environment, not only can different levels of market expectations be triggered by factors such as macroeconomic policies, market operating trends, and current company developments have an impact on sector assets, but sector asset rises and falls are also influenced by a factor that cannot be ignored: market sentiment. Therefore, this paper uses LSTM to construct a forecasting model for industrial assets based on investor sentiment and public historical trading data of industry asset markets to determine future trends and obtains two conclusions: first, forecasting models incorporating investor sentiment have better forecasting effects than those without the incorporation of sentiment characteristics, indicating that the factor of investor sentiment should not be ignored when studying the problem of industry asset forecasting; secondly, investor sentiment quantified by different methods.
- Is Part Of:
- Mathematical problems in engineering. Volume 2022(2022)
- Journal:
- Mathematical problems in engineering
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-03-21
- Subjects:
- Engineering mathematics -- Periodicals
510.2462 - Journal URLs:
- https://www.hindawi.com/journals/mpe/ ↗
http://www.gbhap-us.com/journals/238/238-top.htm ↗ - DOI:
- 10.1155/2022/1113023 ↗
- Languages:
- English
- ISSNs:
- 1024-123X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 21326.xml