Market sentiment can be defined as the overall attitude or feelings of investors towards a particular security or larger financial market. In other words, it is a changing psychology of individual or investors on the basis of price movements of the securities traded in the certain market (Baker, Wurgler and Yuan, 2012). Herein, researcher aim evaluating the fact by making comparative study on the traditional and empirical studies of financial theory in which traditional financial theory claims that, sentiments has no role in financial market while empirical theory illustrates that there is a significant role of investor sentiments in financial market.
Many events have occurred in the past where prices rose very high consequently creating a bubble and eventually the market crashed. The most significant were: the Great Crash (1929), the Tronics Boom (early 1960s), the Nifty fifty bubble (early 1970s), the Black Monday crash (October 1987), the Internet bubble (1990s). Stock prices had a dramatic change. The change could be explained through behavioral finance as the standard model failed to do so. It suggested that investors are subject to sentiment, as backed up by the assumptions of Delong, Shleifer, Summers and Waldmann (1990), and that betting against sentimental investors is costly and risky because of limits to arbitrage (Da, Engelberg and Gao, 2015).
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Traditional Financial Theory
On the basis of traditional financial theory, the world and its participants are considered as the rational wealth maximizers. However, according to this theory, investors know each and every aspect about the stock market and the company in which are they are planning to invest. In this situation, rational is considered more powerful than the sentiments which indeed indicates that, there is no major role of sentiments for the investors in making decisions in the financial market. However, it has been seen often that emotions and psychology influences our decisions which leads individual to behave in unpredictable manner or irrational ways (Stambaugh, Yu and Yuan, 2014).
Furthermore, under traditional financial theory, investors considers efficient market hypothesis which is an investment theory that states it is impossible to beat the market because stock market efficiency causing existing share price to always incorporate and reflect all relevant information or data. As per the theory of efficient market hypothesis, stocks always trade at their fair value on the stock exchange and creating several problems for the investors to buy the undervalued stocks or sell stocks for inflated prices. However, although it becomes almost impossible to outperform the entire market through the views and thoughts of experts on stock selection or market timings (Mian and Sankaraguruswamy, 2012). But the only remaining way to generate higher returns is to buy higher riskier investments. In addition to although considering Efficiency Market Hypothesis as the cornerstone of modern financial theory it is still highly controversial and often disputed. Further, whenever investors are buying or selling the securities they are actually engaging in the game of chance rather than of skills (Kumar, Page and Spalt, 2013).
According to empirical approach, theory and historical anecdote both clearly indicates that sentiment may cause systematic patterns of mispricing. However, although it is very difficult to identify the mispricing still through means of systematic patterns evaluating the mispricing corrections. Furthermore, mispricing is the outcome of both an uninformed demand shock and a limit on arbitrage. Therefore, individual can think of two different channels with the help of which investor’s sentiment might affect the cross section of stock prices. However, in the first source sentimental demand shocks vary in the cross section whereas arbitrage limit are stable. While on the other hand in second channel, the hindrance of arbitrage differentiate from stock to stock by sentiment are generic (Białkowski, Etebari and Wisniewski, 2012).
Role of investor sentiment in the financial market
Investor sentiment is “a belief about future cash flows and investment risks that is not justified by the facts at hand.” Sentiment has cross-sectional effects when sentiment-based demands or arbitrage constraints varies across stocks. Irrational investors, also known as noise traders, affect stock prices by their correlated demand shocks which leads to an instant mispricing. The type of stocks affected by investor sentiment may be new, small, more volatile, unprofitable, non-dividend paying, or distressed stocks (Corredor, Ferrer and Santamaria, 2013).
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Furthermore, sentiment dynamics could be used to explain the cross-sectional variation among different portfolio types, which portfolios are the most sensitive to sentiment. Investor sentiment is described as a ‘contrarian indicator’ for subsequent returns and is less likely to indicate the reason why rational arbitrageurs do not correct mispricing’s that are avoidable.
Furthermore, as per the study made by Chen, Chen and Lee, (2013), indicates that the findings generated by author are aligned with the prediction and clarity that the role of investor’s sentiment in asset pricing is important. On the basis of this study it has been analysed that, empirical outcomes clearly indicates that impact of cumulative sentiment alters as per the returns because they in terms of economic are larger than the impact of sentiment levels although it does not impact on the others.
Cross sectional variation in sentiment:
In general, investor sentiment can be defined as the propensity to speculate. However, as per this definition sentiment drives the relative demand for speculative investments which indeed causes the cross section effects even if arbitrage forces are the same across the available stocks. Considering the bubble period when the propensity to speculate is relatively high then the profile such as canonical young, unprofitable, extreme growth stock etc. allows investment bankers to further argues for the high end of valuations (Corredor, Ferrer and Santamaria, 2014).
Further, there are several other channels that clearly indicates that there are variations in propensity to speculate for the investors which may generally affect the cross section which does not take any stand on the fact that how sentimental investors actually selects the stocks. Therefore, investors which have low tendency to speculate may demand profitable, as it not that profitability and dividends are correlated to each other but if company generates profit it is the position of safety for the investors in which he/she can assure that they will attain returns on the invested stocks or securities (Berger and Turtle, 2012).
Cross sectional variation in Arbitrage:
There are several authors and experts who defines investor’s sentiments as the optimism or pessimism about the stocks (Kim, Ryu and Seo, 2014). Considering the findings of a body related to theoretical and empirical research it can be evaluated that arbitrage tends to be risky and costly particularly for the young investors, small ventures etc. Further including the high characteristic risk for arbitrage makes it more risky for the investors to make any decision regarding the investments (Berk and Demarzo, 2007).
According to Baker 2007 one approach that could be used to measure and quantify the effects of investment sentiment is the ‘bottom up’ method. This method could explain whether investors underreact or overreact to past returns or fundamentals using biases in individual investor psychology such as overconfidence and cognitive biases. Some investors may feel overconfident in their abilities and judgement which may in some cases lead them to wrong investment decisions as a result of underestimating risks (Dash, 2009). Other investors may base their decisions on a small sample of observation and decide upon that at the time, this can be measured using representativeness bias. Other measures of sentiment include, investor surveys such as AAII Sentiment Survey and the European Commission surveys both of which indicate the attitudes of investors whether being bullish, bearish or neutral on the stock market. Other mediums that could be referred to extract additional information on investor mood/attitudes are from social media platforms, Television, weather forecasts (Hong and Sarkar, 2007).
Furthermore, it is not easy to measure the sentiment of an investor. But there is no such fundamental causes on the basis of which investor cannot identify the imperfect substitutions that remains of great use over the time (Brustbauer and Bank, 2014).
Issue in forming the index:
To determine the relative timing of the variables which may be due to lead-lag relationships. Some variables may exhibit a given shift in sentiment before others for e.g. IPO volume lags the first-day returns on IPOs; sentiment may play a role in high first-day returns which attracts additional IPO volume with a lag (Bloomfield, 2010).
There are several potential sentimental substitutions through the means of which investor’s sentiments can be measured in effective and efficient manner which are as follows:
Investors surveys is one of the suitable manner of measuring the sentiments of investors because with the help of this, one can easily identify how optimistic they are as well as gain the insight about the marginal irrational investors. As per the survey conducted by Robert Shiller it has been identified that, there are different attitude of investors which can be seen in different situations that may directly or indirectly affects the decision making. Investor’s mood is another major tool of measuring the sentiments of investors. However, there are some paper that have creatively focused on interlinking the stock prices to the constantly changing human emotions.
Retail investor trade are the inexperienced retail investors that are more likely to subject to the sentiment as compared to the professionals. In this regard, study of Corredor, Ferrer and Santamaria, (2013) illustrates that, younger investors were highly interested in buying the stocks of company in comparison to the older investors. Further, author recommends that constructing sentiment measures for retail investors is based on the fact that whether such investors are buying or selling the securities or commodities.
Trading volume or in general terms can be defined as liquidity can be viewed as the investor sentiment index. In this context, Berger and Turtle, (2012) states that, short selling is more expensive as compared to the opening and closing long position than in such situations irrational investors are more likely to trade or invest. Therefore, it is important for the individual to add liquidity when they are optimistic and betting on rising stock as compared to situation when they are pessimistic.
IPO Volume is the underlying demand for the initial public offerings which is often said to be highly sensitive in context to the investor’s sentiments. There are several investment bankers that states that, IPO is windows of opportunity for open and close. In this, investor can issue 100 shares on one month and zero on the other to manage the risks and uncertainties (Berger and Turtle, 2012).
Sentiment affects stock returns
Several studies were conducted to examine sentiment sensitivities in the cross-section in aggregate domestic portfolios and in international markets. Most reported that negative returns are associated within periods of high investor sentiment. Bubble models can be used to examine the impact of cumulative sentiment changes on equity returns. However, in the buying pressure from rationale and noise traders involving the bubbles worsen deviations in price (Baker, Wurgler and Yuan, 2012). Therefore, it can be said increasing prices above the fundamental values can affect the course of decisions made by investors. The relation between sentiment and returns is path dependent short-term increases in sentiment precede strong positive returns, while prolonged periods of increasing sentiment precede negative returns.
Through the help of above defined figure, it can be summarized that, unified view of the effects of sentiments on stocks. On the basis of x axis it can be said that how difficult are the stocks to be valued and arbitrage. Further, the bond type stock are considered as the regulated utilities which are posted towards left and stocks of the companies that are newer, smaller, more volatile, distressed or have tremendous growth are towards right (Da, Engelberg and Gao, 2015).
Furthermore, y axis assist in measuring the prices of stocks which are denoted as P* which can vary on the basis of time and situations. Therefore, the presented line then clearly indicates the stock valuation that is affected by sentiments of investors. However, high sentiments are linked with the high stock valuation and especially to those stocks which are very difficult to either value or arbitrage. While on the other hand, low sentiments operates in the reverse direction. In the absence of sentiments, stock are on average and assumed to be at the accurate price value of P*. But during this analysis question that created several issues for the author is where to locate the crossing point of this seesaw. However, in once case there is no crossing point exists that is related to the upward sloping high sentiment line lies entirely above the no sentiment P* line (Kumar, Page and Spalt, 2013).
Therefore, in order to mitigate such influences it is important for the investors to evaluate each and every substitutions on the basis of macroeconomic indicators that consist of growth in industrial production, real growth in durable, nondurable and services consumption, growth in employment etc (Corredor, Ferrer and Santamaria, 2014). Furthermore, these varied sentiments substitutions will have a common sentiment component so that investors can easily evaluate the macroeconomics influences so that desired results and outcomes can be generated.
Using sentiment to predict stock Returns
Sentiments can be one of the major tools with the help of which investors can predict the stock returns. However, high sentiment indeed causes overvaluation which may be recorded as the low future returns on the sentiment prone stocks. However, predictability is not a nature implications that clearly indicates that correlation between returns and sentiment indices which arises because of the latter contaminated by fundamentals.
Cross sectional predictability:
In order to test the idea further, it is important for the investor to create an empirical version on the sentiment seesaw and compare it to the prediction identified in the above defined figure. However, the unconditional average return are slightly lower for speculative stocks, consistent with behavioural models of disagreement among the investors combined with short sales constraints (Berk and Demarzo, 2007).
However, on the basis of above analysis it has been evaluated that when sentiments are high the market returns are relatively low.
On the basis of above figure it can be seen that, sentiment level is more than one standard deviation above its historical average, monthly returns of - 0.41% for equal weighted market index return. Along with this, -0.34% of points for value weighted returns (Białkowski, Etebari and Wisniewski, 2012). Henceforth, correlation between sentiment changes and returns is higher for an equal weighted index of returns.
In conclusion to the above report it has been analysed that, price bubbles and ‘irrational exuberance’ do not exist in this theory. However, although rationality can suggest future expectations of stock prices to the investors, empirical evidence affirms that investors are actually irrational and greedy. Rational behavior is not predominated in the market, investors with such a characteristic do not necessarily correct the market through arbitrage when prices deviate from their fundamental values; reason being is that arbitrage becomes risky as irrational investors push prices as high or as low as they can in the short term, and it is also costly in terms of having to pay transaction costs. Other investors may base their decisions on a small sample of observation and decide upon that at the time, this can be measured using representativeness bias. There are other biases that can describe investor’s sentiment such as anchoring, confirmation, ostrich effect, disposition effect etc.
- Baker, M., Wurgler, J. and Yuan, Y., 2012. Global, local, and contagious investor sentiment.Journal of Financial Economics.
- Berger, D. and Turtle, H.J., 2012. Cross-sectional performance and investor sentiment in a multiple risk factor model.Journal of Banking & Finance.
- Berk, B. J. And Demarzo, M. P., 2007. Corporate Finance. Pearson Addison Wesley.
- Białkowski, J., Etebari, A. and Wisniewski, T.P., 2012. Fast profits: Investor sentiment and stock returns during Ramadan.Journal of Banking & Finance.
- Chen, M.P., Chen, P.F. and Lee, C.C., 2013. Asymmetric effects of investor sentiment on industry stock returns: Panel data evidence.Emerging Markets Review.