Market sentiment
Market sentiment, also known as investor attention, is the general prevailing attitude of investors as to anticipated price development in a market. This attitude is the accumulation of a variety of fundamental and technical factors, including price history, economic reports, seasonal factors, and national and world events. If investors expect upward price movement in the stock market, the sentiment is said to be bullish. On the contrary, if the market sentiment is bearish, most investors expect downward price movement. Market participants who maintain a static sentiment, regardless of market conditions, are described as permabulls and permabears respectively. Market sentiment is usually considered as a contrarian indicator: what most people expect is a good thing to bet against. Market sentiment is used because it is believed to be a good predictor of market moves, especially when it is more extreme. Very bearish sentiment is usually followed by the market going up more than normal, and vice versa. A bull market refers to a sustained period of either realized or expected price rises, whereas a bear market is used to describe when an index or stock has fallen 20% or more from a recent high for a sustained length of time.
Market sentiment is monitored with a variety of technical and statistical methods such as the number of advancing versus declining stocks and new highs versus new lows comparisons. A large share of the overall movement of an individual stock has been attributed to market sentiment. The stock market's demonstration of the situation is often described as all boats float or sink with the tide, in the popular Wall Street phrase "the trend is your friend". In the last decade, investors are also known to measure market sentiment through the use of news analytics, which include sentiment analysis on textual stories about companies and sectors.
Theory of investor attention
A particular thread of scientific literature connects results from behavioural finance, changes of investor attention on financial markets, and fundamental principles of asset pricing: Barberis et al., Barberis & Thaler, and Baker & Wurgler. The authors argue that behavioural patterns of retail investors have a significant impact on market returns. At least five main approaches to measuring investor attention are known today in scientific literature: financial market-based measures, survey-based sentiment indexes, textual sentiment data from specialized on-line resources, Internet search behavior, and non-economic factors.First approach
According to the first approach, investor attention can be approximated with particular financial market-based measures. According to Gervais et al. and Hou et al., trading volume is a good proxy for investor sentiment. High trading volume on a particular stock leads to appreciating of its price. Extreme one-day returns are also reported to draw investors' attention. Noise traders tend to buy stocks with high returns. Whaley and Baker & Wurgler suggest Chicago Board Options Exchange Volatility Index as an alternative market sentiment measure. Credit Suisse Fear Barometer is based on prices of zero-premium collars that expire in three months. This index is sometimes used as an alternative to VIX index. The Acertus Market Sentiment Indicator incorporates five variables : Price/Earnings Ratio ; price momentum ; Realized Volatility ; High Yield Bond Returns ; and the TED spread. Each of these factors provides a measure of market sentiment through a unique lens, and together they may offer a more robust indicator of market sentiment. Closed-end fund discount reported to be possible measure of investor attention and Lee et al. ).The studies suggest that changes in discounts of closed-end funds are highly correlated with fluctuations in investor sentiment. Brown et al. investigate daily mutual fund flow as possible measure of investor attention. According to Da et al., "...individual investors switch from equity funds to bond funds when negative sentiment is high." Dividend premium potentially can be a good predictor for investor sentiment and Vieira ). Retail investor trades data is also reported to be able to represent investor attention. The study shows that retail investor transactions "...are systematically correlated — that is, individuals buy stocks in concert". Initial public offering of a company generates a big amount of information that can potentially be used to proxy investor sentiment. Ljungqvist et al. and Baker & Wurgler report IPO first-day returns and IPO volume the most promising candidates for predicting investor attention to a particular stock. It is not surprising that high investments in advertisement of a particular company results in a higher investor attention to corresponding stock. The authors in Chemmanur & Yan provide an evidence that "...a greater amount of advertising is associated with a larger stock return in the advertising year but a smaller stock return in the year subsequent to the advertising year". Equity issues over total new issues ratio, insider trading data, and other financial indicators are reported in Baker & Wurgler to be useful in investor attention measurement procedure.
The aforementioned market-based measures have one important drawback. In particular, according to Da et al. : "Although market-based measures have the advantage of being readily available at a relatively high frequency, they have the disadvantage of being the equilibrium outcome of many economic forces other than investor sentiment." In other words, one can never be sure that a particular market-based indicator was driven due to investor attention. Moreover, some indicators can work pro-cyclical. For example, a high trading volume can draw an investor attention. As a result, the trading volume grows even higher. This, in turn, leads to even bigger investor attention. Overall, market-based indicators are playing a very important role in measuring investor attention. However, an investor should always try to make sure that no other variables can drive the result.
Second way
The second way to proxy for investor attention can be to use survey-based sentiment indexes. Among most known indexes should be mentioned University of Michigan Consumer Sentiment Index, The Conference Board Consumer Confidence Index, and UBS/Gallup Index of Investor Optimism. The University of Michigan Consumer Sentiment Index is based on at least 500 telephone interviews. The survey contains fifty core questions. The Consumer Confidence Index has ten times more respondents. However, the survey consists of only five main questions concerning business, employment, and income conditions. The questions can be answered with only three options: "positive", "negative" or "neutral". A sample of 1000 households with total investments equal or higher than $10,000 are interviewed to construct UBS/Gallup Index of Investor Optimism. Mentioned above survey-based sentiment indexes were reported to be good predictors for financial market indicators. However, according to Da et al., using such sentiment indexes can have significant restrictions. First, most of the survey-based data sets are available at weekly or monthly frequency. At the same time, most of the alternative sentiment measures are available at a daily frequency. Second, there is a little incentive for respondents to answer question in such surveys carefully and truthfully. To sum up, survey-based sentiment indexes can be helpful in predicting financial indicators. However, the usage of such indexes has specific drawbacks and can be limited in some cases.Third direction
Under the third direction, researchers propose to use text mining and sentiment analysis algorithms to extract information about investors' mood from social networks, media platforms, blogs, newspaper articles, and other relevant sources of textual data. A thread of publications, Dougal et al., and Ahern & Sosyura ) report a significant influence of financial articles and sensational news on behavior of stock prices. It is also not surprising, that such popular sources of news as Wall Street Journal, New York Times or Financial Times have a profound influence on the market. The strength of the impact can vary between different columnists even inside a particular journal. Tetlock suggests a successful measure of investors' mood by counting the number of "negative" words in a popular Wall Street Journal column "Abreast of the market". Zhang et al. and Bollen et al. report Twitter to be an extremely important source of sentiment data, which helps to predict stock prices and volatility. The usual way to analyze the influence of the data from micro-blogging platforms on behavior of stock prices is to construct special mood tracking indexes.The easiest way would be to count the number of "positive" and "negative" words in each relevant tweet and construct a combined indicator based on this data. Nasseri et al. reports the predictive power of StockTwits data with respect to behavior of stock prices. An alternative, but more demanding, way is to engage human experts to annotate a large number of tweets with the expected stock moves, and then construct a machine learning model for prediction. The application of the event study methodology to Twitter mood shows significant correlation to cumulative abnormal returns, Ranco et al. , Gabrovšek et al. ). Karabulut reports Facebook to be a good source of information about investors' mood. Overall, most popular social networks, finance-related media platforms, magazines, and journals can be a valuable source of sentiment data, summarized in Peterson. However, important to notice that it is relatively more difficult to collect such type of data. In addition, analysis of such data can also require deep machine learning and data mining knowledge.