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A Study On The Relationship Between Public Emotion And Stock Market

Posted on:2017-05-03Degree:MasterType:Thesis
Country:ChinaCandidate:S M WangFull Text:PDF
GTID:2209330485450741Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
With the development of Internet technology, the Internet platform has become the main platform of people and spread information, including social media such as post bar, micro blogging, blog, BBS, has become the main platform to access information, express emotion. Now the Internet is controlled by a simple information publishing platform, to develop into an information sharing, communication, social network platform, followed by a geometric series increase of network information. Great amount of information contains important value, foreign scholars have used the network information to make decision analysis, when we want to know customers’ preferences, to know others’ views and opinions and understand the ideas of the people so that we can more targeted to make decisions, the huge network information will play an important role.The purpose of this thesis study is to use large financial stock website, please review the information reflects each investor emotion, to get all investors reflects the mood of the public information, analyzes the relations between public sentiment and the stock market, forecasts the future trend of the stock, so as to help investors avoid disadvantages.This paper to analyze the stock reviews financial BBS, in-depth excavation of the stock comments contained in the information such as investor sentiment and investment behavior, on behalf of all investors emotional mood of the public value, analysis of the stock’s closing price, yield, volume and other information and corresponding shares of public sentiment, the relationship between the public interest, to explore the public emotion and the relationship between the stock market.This article mainly from the perspective of qualitative and quantitative research, using empirical analysis method, analysis of the public feelings is worth points and public attention with the stock’s closing price, yield, volume, etc. There is a correlation between stock information. Spearman rank correlation test was used to study the emotional value of the day if there is a correlation and the stock’s closing price of the day, the emotional value of the study respectively after a few days ago and after a few days of emotional value and whether there is a relationship between the stock’s closing price of the day. Then, using the Granger, Granger causality test, test whether the mood of the public can explain the changes of the stock market. Finally establish a nonlinear model of SVM(support vector machine, support vector machine) model to forecast time series of Shanghai stock index, set up the control inspection public sentiment time sequence can improve the accuracy to predict the price of the stock market.Finally the conclusion is 1, the closing price of the stock market and the yields are with the public emotion has a positive correlation, namely the investor sentiment, the higher the stock’s closing price and yield, on the other hand was not; Public attention is negatively related to the stock market closing price, yield, etc have relations, namely when public attention to increase the stock of yields and the closing price into a downward trend. 2, whether the stock market in the period of increase or decrease in father-in-law emotions are positive correlation with the stock market closing price and yield, and the public in the stock market volatility is relatively strong, expressing the emotion and the public interest and the stock’s closing price and yield are negative correlation, and more negative correlation in decline period, it can be seen in the stock market volatile stock investors behavior converged to a certain extent. 3, public sentiment the stock’s closing price has certain prediction effect.
Keywords/Search Tags:public sentiment, text mining and sentiment analysis, the stock market
PDF Full Text Request
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