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https://nccur.lib.nccu.edu.tw/handle/140.119/98565
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| Title: | PTT股票板討論對股市之影響
The Influence of Discussion in Stock Section of PTT on Stock Market |
| Authors: | 林彥丞 |
| Contributors: | 周冠男
林彥丞 |
| Keywords: | 社群網路
PTT |
| Date: | 2016 |
| Issue Date: | 2016-07-01 14:59:28 (UTC+8) |
| Abstract: | 過去總認為市場是有效率的，投資人是理性的，但近年來，行為財務學的興起，開始證明投資人經常做出不理性的行為，導致投資市場只有少數人為贏家，能長期獲得超額報酬。散戶的投資行為也是學術上時常探討的，而在過去幾年，國外開始有學者利用社群網站twitter，並用情緒辨識軟體將發文者的文章做情緒的歸類，來看能不能提升對大盤或個股的預測能力。結論是其中幾類情緒的確能提升預測大盤或個股的機率。而在台灣，比較有名的股票社群為PTT的股票板，該板通常會同時有1000人以上在線上。本文做了兩項研究，其一為藉由本週看多及看空文章的總數來看是否能預測未來幾週的大盤報酬，其二為藉由個股看多或看空文章的回文數，來看是否看多或看空文章的回文數愈多，是否能預測個股未來幾天的報酬，而以上兩項的結果，即使有些部分在統計上為顯著，但並沒有一致性，舉例來說，有些個股可能在第三天顯著，並與回文數呈負相關，但另一些個股可能在第5天顯著，並與回文數呈正相關，因此並無法得到一致性，很難有合理的解釋，因此可說明，PTT裡的發文及回文對整個投資市場來說，並無資訊內涵，並無法預測股市的報酬。
The efficient market was popular before and most of the investors are seen as rationality. However, behavioral finance emerged in recent years. This theory tells us investors usually invest irrationally that there are only a few people in the market are winner in the long run. Retail investors’ behaviors are usually discussed in theses in recent years. In foreign country, there were some people studying the social network- twitter and use some software to judge the different emotions in an article in twitter. Finally, they found some types of emotions could predict the movement of stock prices or stock index like Dow Jones. In Taiwan, the stock section in PTT is famous. Many people express their opinions in stock section of PTT. In this paper, author use the bullish or bearish article to forecast the stock index a few weeks later and use the number of responses of an article for a specific stock to predict the return of the stock a few days later. The results are that some of the responses of stocks can predict stocks returns five days later and there are negative relation between the numbers of responses and the returns. However, other responses of stocks can predict stocks returns three days later and there are positive relation between the numbers of responses and the returns. The author can’t find the consistent results. There are more than1000 people stay in the stock section of PTT at the same time, but these people are only a small group in the stock market. Consequently, we can use PTT to predict the stock market. |
| Reference: | 1. Eugene Fama, 1970, Efficient capital markets: A review of theory and empirical work, The Journal of Finance 25, 383-417.
2. Kahneman and Tversky, 1979, Prospect Theory-Division of the Humanities and Social Science, Econometrica 47, 263-292.
3. Wesley S. Chan, 2002, Stock Price Reaction to News and No-News: Drift and Reversal After Headlines, Journal of Financial Economics 70, 223–236.
4. Werner Antweiler and Murray Z. Frank, 2004, Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards, The Journal of Finance 3, 1259-1294.
5. Malcolm Baker and Jeffrey Wurgler, 2006, Investor Sentiment and the Cross-Section of Stock Returns, The Journal of Finance 4, 1645-1680.
6. Z. Da, J. Engelberand, and P. Gao, 2010, The sum of all fears: investor sentiment and asset prices, http://ssrn.com/abstract=1509162
7. Johan Bollen, Huina Mao and Xiao-Jun Zeng, 2010, Twitter mood predicts the stock market, Indiana University, Computer 1010, 1–8.
8. Huina Mao, Scott Counts and Johan Bollen, 2011, Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data, arXiv.org, Quantitative Finance Papers, 1051-1112
9. Tushar Rao and Saket Srivastava, 2012, Analyzing Stock Market Movements Using Twitter Sentiment Analysis, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.
10. Eric D. Brown, 2012, Will Twitter Make You a Better Investor? A Look at sentiment, User Reputation and Their Effect on the Stock Market, Dakota State University |
| Description: | 碩士
國立政治大學
財務管理研究所
103357035 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0103357035 |
| Data Type: | thesis |
| Appears in Collections: | [財務管理學系] 學位論文
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| 703501.pdf | | 1140Kb | Adobe PDF2 | 96 | View/Open | | 703502.pdf | | 1140Kb | Adobe PDF2 | 90 | View/Open |
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