2. Literature Review
2.4 Text Mining and Sentiment Analysis
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立 政 治 大 學
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N a tio na
l C h engchi U ni ve rs it y
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2.4 Text Mining and Sentiment Analysis
Text announcement and media content would affect investors’ sentiment, investors’
sentiment would induce investors’ decision. News provide investors with information related to the financial market and future market trend, therefore, it is important to analyze information generated by the mass media and the impulse raised by the media content.
Tetlock (2007) measured the interaction between stock market activity and daily media contents. Scholar analyzed news pieces available on Wall Street Journal (WSJ) column. Research studied on the linkage between measure of media pessimism and the stock market using basic vector autoregressions (VAR). Result suggested that high level of pessimistic and uncertainty quotes predict downward movement on stock price.
Extremely high or low level of pessimism anticipate rise in trading volume. We can conclude that daily media content and stock market return and volume are highly correlated.
Kaplanski and Levy (2010) suggested that investors’ mood and anxiety would negatively affect their investment decision and hence affect the entire stock market. The study investigated the impulse caused by aviation disaster on investors’ sentiment, scholar believed that aviation disaster would increase investors’ anxiety and reduce the market demand on risky investments and affect stock prices. Result suggested that aviation disaster are followed by negative rates of return in the stock market accompanied by a reversal effect two days later. VIX and VXO would increase after aviation disasters.
Akhtar et al. (2011) examined the impact of monthly released Australian consumer sentiment news on the equity market. Scholar believed that announcement of negative (positive) consumer sentiment news will induce a negative (zero) stock market reaction.
Result reflected that consumer sentiment contain valuable information content and it is useful in predicting variation in stock market activities. Scholars suggested that the monthly Australian Consumer Sentiment Index (CSI) is a good proxy of for investors’
sentiment in the Australian equity market. If the recently released CSI is lower than that of the previous CSI, the Australian market will suffer from a significant announcement negative day effect. However, there is no significant impact if CSI is higher than that of the previous month.
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立 政 治 大 學
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N a tio na
l C h engchi U ni ve rs it y
Carretta et al. (2011) investigated on how news communication affect the stock market, they extracted information available between 2003 and 2007 in a major Italian financial newspaper. From the result of the analysis, scholars concluded that the mass media have significant impact on the financial markets since news reports contribute to the formation of investor expectations. The paper first proved the possibility that investor behavior is influenced by the content of the news and by the tone of communication.
Zhang and Skiena (2011) used the natural language processing techniques to analyze the text content of blogs and news. They studied the anticipating power of text appeared in blogs and the mass media on market trade volume and future returns. Based on the sentiment data available from blogs and news, scholars developed a market-neural strategy to generate information from text data. Result suggested that news and blogs polarity are correlated with market volume and return. The sentiment conveyed by blogs will last longer than that of news, as content of blogs include more personal feelings if investors.
Baker et al. (2012) constructed the investor sentiment indices for six major equity market and investigated the impact of investor sentiment on both local and global markets. Result shown that relative sentiment is correlated with the stock prices of dual-listed companies. Global investors’ sentiment is a useful contrarian predictor of country-level stock returns and both global and local sentiment are contrarian predictors of future returns. Investors’ sentiment play a significant role in international market volatility and generates market predictability. From the study, we learn that both local and global investors’ sentiment are related to future stocks returns.
Liu (2012) provided an overview of sentiment analysis and opinion mining.
Scholar defined sentiment analysis as a field of study that investigate people’s opinions, emotions and attitudes. Liu (2012) believed that opinion words are powerful indicators of sentiment, these opinion words reflect positive or negative feelings. We could use the number of positive and negative wordings appeared in news article as variables of study.
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立 政 治 大 學
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N a tio na
l C h engchi U ni ve rs it y
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Ferguson et al. (2013) suggested that news media provide valuable information for market participants. Both private and public information shape investors’ expectation on firm’s future performance. Scholars used the information from UK market and gather international evidence for the predictive power of news content on future stock returns, there is significant interaction between positive and negative content and stock returns. Market participants react more significantly for news with higher level of visibility.
Li et al. (2014) proposed a media-aware quantitative model to quantify how investors’ sentiment predict future stock market movements. Scholars used the percentage of positive and negative words in news articles to measure the optimistic and pessimistic mood of investors. Result showed that new article sentiment would fluctuate investors’ sentiment and interfere with their decision making. However, news article from different sources would affect the market differently. Moreover, news concerning executive personnel change and new product release are more influential comparing with other types of news.
Benhabib et al. (2016) investigated the impact of financial information on investors’ sentiment fluctuations in equity market. Small investor sentiment shock would be amplified in the financial market and affect the economic situations. The paper illustrated the possibility of sentiment driven fluctuations in stock prices and real-time output.
Yang et al. (2017) applied the text mining approach to evaluate firms’ risks using unstructured textual disclosure from firm’s financial reports. Scholars suggested there are many hidden information hided between the lines in corporate public documents.
The study used the Natural Language Processing techniques to extract firms’ self-identified risks including financial, strategic, operational, and hazard risks and evaluate the relationship between firm’s overall risks and its audit fee.
From research discussed above, we learn that publicly available information such as news and annual reports content would affect investors’ sentiment and decision.
These findings suggested the importance of sentiment mining based on news content.
In this study, we would analyze the interaction between of the external environment news and VIXTWN.
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Table 2-3 Summary of Key Text and Sentiment Analysis Literatures
Author Research
Period
Algorithm Hypothesis Variables Conclusion
Tetlock (2007) 1984 - 1999 Regression Pessimism factor serve as proxies for investor sentiment, return and daily trading volume.
Pessimism Media Factor, Daily Volume
High values of media pessimism induce downward pressure on market price. High or low values of pessimism lead to temporarily high trading volume.
Regression Increased anxiety after aviation disasters will lead to a short-term reduction in demand for risky assets and affects stock prices
Stock Returns Aviation disasters are followed by negative rates of return in the stock market accompanied by a reversal effect two days later.
Akhtar et al.
(2011)
June 1992 – December 2009
Regression The announcement of negative (positive) consumer sentiment news will induce a negative (zero) stock market reaction.
Stock Return, Consumer Sentiment Index
CSI has valuable information content. When a lower (higher) than previous month CSI is announced, the stock market suffers a (no) significant negative announcement day effect.
Carretta et al.
(2011)
2003 – 2007 Regression Corporate governance news would impact the stock market and investor expectations.
Abnormal Return, News Tone
Investors are influenced by the content (positive or negative) and tone of communication (strong or weak) of the news publications.
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Table 2-3 Summary of Key Text and Sentiment Analysis Literatures (cont.)
Author Research
Period
Algorithm Hypothesis Variables Conclusion
Zhang and Skiena (2011)
2005 - 2009 Regression Company related news variables can anticipates the company’s stock trading volumes and financial returns.
News volume, Media Polarity, Stock Return, Trade Volume
News and blogs sentiment can predict volume and return. The sentiment conveyed by blogs can last longer than news.
Baker et al.
(2012)
1980 – 2005 Regression Investors’ sentiment play a significant role in international market volatility and generates market predictability.
Stock Return, Sentiment Indices
Relative sentiment is correlated with the relative prices of dual-listed companies. Global sentiment is a contrarian predictor of
country-level returns.
Ferguson et al.
(2013)
1981 – 2010 Regression Semantic measures of news media content can predict future stock returns
Positive Content, Negative Content, News Volume, Stock Return
Visibility and tone are key factors in determining how investors respond to news.
Li et al. (2014) January 2011 – December 2011
Regression News article and public mood would influence stock market movements.
Optimistic Mood, Pessimistic Mood, Stock Return
Media influence of financial news on stocks exists and can be
quantified using natural language processing techniques.
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立 政 治 大 學
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N a tio na
l C h engchi U ni ve rs it y
3. Research Method