Market Confidence Predicts Stock Price: Beyond Supply and Demand
Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using...
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Published in | PloS one Vol. 11; no. 7; p. e0158742 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
Public Library of Science
08.07.2016
Public Library of Science (PLoS) |
Subjects | |
Online Access | Get full text |
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Summary: | Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using transaction record of stocks with identifier of traders, we introduce an index to characterize market confidence, i.e., the ratio of the number of traders who is active in two successive trading days to the number of active traders in a certain trading day. Strong Granger causality is found between the index of market confidence and stock price. We further predict stock price by incorporating the index of market confidence into a neural network based on time series of stock price. Experimental results on 50 stocks in two Chinese Stock Exchanges demonstrate that the accuracy of stock price prediction is significantly improved by the inclusion of the market confidence index. This study sheds light on using cross-day trading behavior to characterize market confidence and to predict stock price. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Conceived and designed the experiments: XQS HWS XQC. Performed the experiments: XQS HWS. Analyzed the data: XQS. Contributed reagents/materials/analysis tools: YZ. Wrote the paper: XQS HWS. |
ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0158742 |