Investor Sentiment in Financial Markets

This assignment delves into the concept of investor sentiment within financial markets. It requires a critical analysis of provided academic research papers, exploring how investor emotions and perceptions impact stock market behavior. The analysis should focus on the key findings, methodologies, and contributions of the cited works.

Investor Sentiment and Stock Returns

TABLE OF CONTENTS
Introduction..........................................................................................................................................
Traditional Financial Theory.......................................................................................................2
Empirical Approach.....................................................................................................................2
Role of investor sentiment in the financial market......................................................................3
Measuring Sentiments..................................................................................................................5
Sentiment affects stock returns....................................................................................................7
Using sentiment to predict stock Returns....................................................................................9
Conclusion..........................................................................................................................................
References..........................................................................................................................................

INTRODUCTION
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).
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
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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).
Empirical Approach
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).
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,
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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).
Measuring Sentiments
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
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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
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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.
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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
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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).
Aggregate predictability:
However, on the basis of above analysis it has been evaluated that when sentiments are
high the market returns are relatively low.
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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.
CONCLUSION
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.
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REFERENCES
Journals and Books
Baker, M., Wurgler, J. and Yuan, Y., 2012. Global, local, and contagious investor
sentiment. Journal of Financial Economics. 104(2). pp.272-287.
Berger, D. and Turtle, H.J., 2012. Cross-sectional performance and investor sentiment in a
multiple risk factor model. Journal of Banking & Finance. 36(4). pp.1107-1121.
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. 36(3). pp.835-845.
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. 14. pp.35-54.
Corredor, P., Ferrer, E. and Santamaria, R., 2013. Investor sentiment effect in stock markets:
Stock characteristics or country-specific factors?.International Review of Economics &
Finance, 27. pp.572-591.
Corredor, P., Ferrer, E. and Santamaria, R., 2014. Is cognitive bias really present in analyst
forecasts? The role of investor sentiment. International Business Review. 23(4). pp.824-
837.
Da, Z., Engelberg, J. and Gao, P., 2015. The sum of all fears investor sentiment and asset
prices. Review of Financial Studies. 28(1). pp.1-32.
Dash, P. A., 2009. Security Analysis And Portfolio Management. 2nd Ed. I. K. International Pvt
Ltd.
Hong, G. And Sarkar, S., 2007. Equity Systematic Risk (Beta) And Its Determinants.
Contemporary Accounting Research. 24(2). Pp. 423-66.
Kim, J.S., Ryu, D. and Seo, S.W., 2014. Investor sentiment and return predictability of
disagreement. Journal of Banking & Finance. 42. pp.166-178.
Kumar, A., Page, J.K. and Spalt, O.G., 2013. Investor sentiment and return comovements:
Evidence from stock splits and headquarters changes. Review of Finance. 17(3). pp.921-
953.
Mian, G.M. and Sankaraguruswamy, S., 2012. Investor sentiment and stock market response to
earnings news. The Accounting Review. 87(4). pp.1357-1384.
Stambaugh, R.F., Yu, J. and Yuan, Y., 2012. The short of it: Investor sentiment and
anomalies. Journal of Financial Economics. 104(2). pp.288-302.
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Stambaugh, R.F., Yu, J. and Yuan, Y., 2014. The long of it: Odds that investor sentiment
spuriously predicts anomaly returns. Journal of Financial Economics. 114(3). pp.613-
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