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Incorporating Research Reports and Market Sentiment for Stock Excess Return Prediction: A Case of Mainland China
Joint Authors
Huang, Xin
Song, Huilin
Peng, Diyun
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-31
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
The prediction of stock excess returns is an important research topic for quantitative trading, and stock price prediction based on machine learning is receiving more and more attention.
This article takes the data of Chinese A-shares from July 2014 to September 2017 as the research object, and proposes a method of stock excess return forecasting that combines research reports and investor sentiment.
The proposed method measures individual stocks released by analysts, separates the two indicators of research report attention and rating sentiment, calculates investor sentiment based on external market factors, and uses the LSTM model to represent the time series characteristics of stocks.
The results show that (1) the accuracy and F1 evaluation indicators are used, and the proposed algorithm is better than the benchmark algorithm.
(2) The performance of deep learning LSTM algorithm is better than traditional machine learning algorithm SVM.
(3) Investor sentiment as the initial hidden state of the model can improve the accuracy of the algorithm.
(4) The attention of the split research report takes the two indicators of investor sentiment and price as the input of the model, which can effectively improve the performance of the model.
American Psychological Association (APA)
Song, Huilin& Peng, Diyun& Huang, Xin. 2020. Incorporating Research Reports and Market Sentiment for Stock Excess Return Prediction: A Case of Mainland China. Scientific Programming،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1209322
Modern Language Association (MLA)
Song, Huilin…[et al.]. Incorporating Research Reports and Market Sentiment for Stock Excess Return Prediction: A Case of Mainland China. Scientific Programming No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1209322
American Medical Association (AMA)
Song, Huilin& Peng, Diyun& Huang, Xin. Incorporating Research Reports and Market Sentiment for Stock Excess Return Prediction: A Case of Mainland China. Scientific Programming. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1209322
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1209322