Are Indian Stock Markets Driven more by Sentiment or Fundamentals? A Case Study Based on Relationship Between Investor Sentiment and Stock Market Volatility in Indian Markets Himanshu Labroo Student ID: 1749671 812013 A Thesis presented to Dublin Business School and Liverpool John Moores University in partial fulfillment of the requirements for the award degree of Masters of Business Administration in Finance under the supervision of Mr. Michael Kealy.
Introduction
Introduction
Investor psychology significantly influences financial markets, a fact well understood by financial professionals The impact of investors' moods on market movements is frequently analyzed in financial publications, on television, and across online and radio platforms.
In his 2000 speech "Psychology and Market" at Northwestern University, Daniel Kahneman emphasized that financial analysts often highlight the psychological aspects of the market, noting that it possesses its own character, thoughts, beliefs, moods, and even tumultuous emotions.
The research investigates whether Indian stock markets are influenced more by investor sentiments than by fundamental factors This inquiry is significant for potential investors and traders in the Indian Stock Market The project analyzes the effects of key events from the past five years on investor sentiment and market volatility, aiming to determine the relationship between these two aspects.
Investor Sentiment and Stock Market Volatility
Investor sentiment, often viewed as a tendency to react to noise rather than information, reflects overall optimism or pessimism in the market Volatility, a key characteristic of a liquid stock market, influences the pricing of securities and represents the fluctuations in asset prices over time Predicting volatility accurately is challenging, creating a paradox for market participants, academics, and policymakers While some level of volatility is necessary to achieve superior returns—since risk-free securities yield lower returns—excessive volatility can lead to significant losses and economic costs An increase in stock market volatility typically results in substantial price changes, prompting investors to reassess their strategies.
11 market volatility as an increase in the risk of equity investment and consequently they shift their funds to less risky assets
Many people equate volatility with risk, perceiving high volatility as undesirable due to its implications for unreliable security values and dysfunctional capital markets Merton Miller, a Nobel Prize-winning economist, notes that the public often associates volatility with significant market movements, particularly sharp declines These widespread price drops are not always linked to specific news events, which is not unusual in markets for assets like common stocks, where value is influenced by subjective judgments regarding future cash flows and resale prices In contrast, the public tends to adopt a more deterministic perspective on stock prices, believing that a market crash must have a clear cause.
Efficient Market Hypothesis
The Efficient Market Hypothesis posits that predicting the stock market is futile, as share prices consistently reflect all available information This theory suggests that stocks are always traded at their fair value, preventing investors from buying undervalued stocks or selling overvalued ones Consequently, outperforming the market through expert stock selection or timing is deemed impossible; the only way to achieve higher returns is by investing in riskier assets.
The Efficient Market Hypothesis posits that market trends are solely driven by fundamentals and assumes complete informational efficiency However, this theory faced significant scrutiny following the Wall Street Crisis of 1987 Critics, including investors and analysts, highlighted the influence of cognitive biases on stock prices, leading to the emergence of "Behavioral Finance." This perspective gained particular relevance in the context of India, where historical events have shown that impactful news often triggers immediate and irrational market reactions.
Twelve key investors significantly influence stock prices through their buying and selling decisions, often leading to unexpected market movements Despite this, there are occasions when market fundamentals prevail, overshadowing emotional or sentimental trends.
The Indian Stock Market
India boasts the world's third-largest investor base, with over 20 million shareholders and more than 10,000 listed companies across its stock exchanges, trailing only the United States and Japan Approximately 9,400 stock brokers facilitate these markets, including 29 foreign brokers This significant growth in the market has created a strong demand for efficient settlement procedures According to the National Securities Depository, an impressive 99.9% of trades in India are settled in dematerialized form under a T+2 rolling settlement system, reflecting the robust nature of the capital market.
In recent years, Indian stock markets have experienced significant growth, driven by improving macroeconomic fundamentals and substantial foreign investment, which has enhanced transparency and liquidity Since entering the International Financial Markets in the late 1970s, coinciding with the Fourth Five Year Plan, Indian stock markets have played a crucial role in fueling the economy by providing essential capital Their dynamics have captured the attention of scholars, analysts, and investors alike, leading to the development of various theories and propositions regarding market behavior.
The US continues to dominate global financial markets, while the euro zone has established itself as a significant financial powerhouse Together, the euro zone, UK, and US represent approximately 80% of all cross-border capital flows In stark contrast, Japan finds itself isolated, with capital flows that are smaller than those of China, despite China's financial assets being only a quarter of Japan's total This integration is largely driven by individuals' desire for economic freedom and diverse financial options.
In India, the stock market is undergoing significant transformation due to liberalization measures, raising concerns about its vulnerability to global and regional crises Understanding the extent of contagion effects on the Indian stock market in an increasingly integrated global environment is crucial Policymakers must address the degree of financial openness to effectively structure their economies and implement successful policies The Indian capital market is evolving to align its operations with international standards, reflecting a shift towards practices seen in developed markets.
The Indian Capital Markets are mainly affected by two E’s –
1 Earnings/Price Ratio – It is an important factor affecting the stock price of a company It gives us a fair idea of company’s share price when it is compared to its earnings The stock becomes undervalued if the price of the share is much lower than the earnings of a company But if this is the case, then it has the potential to rise in the near future The stock becomes overvalued if the price is much higher than the actual earning of the company
2 Emotions/ Sentiments - They are a huge part of investing Was it the case that only earnings drove the Indian Sensex to a high of 21,000 points in January 2008 and a low of 8700 points in October 2008? Not really Emotions played a big part in both the rise and fall of the Sensex When we get positive news about a company, it increases the buying interest in the market On the other hand, when there is a negative press release, it ruins the prospect of a stock to increase in value.
Figure 1.1 2 Factors Influencing Stock Prices
Investors often exhibit sensitivity to reference points, particularly when stock prices decline due to negative news Many are reluctant to sell at a loss, clinging to their original purchase price as a benchmark This tendency to hold onto losing investments stems from a psychological aversion to loss, leading some investors to wait for prices to recover to their initial levels before making a decision, often without a rational assessment of the situation In essence, investors generally "hate to lose."
Objectives of This Research
In order to understand the main research question, the researcher will conduct fundamental research which will address the following objectives
1 To ascertain the attitudes and sentiments of the investors in India in the current scenario as well as in the recent past
2 To examine if there is any relationship between the important events and investor sentiments
3 To examine and ascertain the relationship between various important events and stock market volatility
4 To examine the relationship between investor sentiment and the stock market volatility in India taking the important events into consideration.
Research Structure
The dissertation commences with an introductory chapter that presents the research background, outlines the approach to the research question, defines the research objectives, and provides an overview of the dissertation's structure.
Chapter two explores the academic literature on investor sentiment and stock market volatility, highlighting key insights from Behavioral Finance The review encompasses seven main headings, addressing topics such as the global implications of investor sentiment, the significance of Behavioral Finance, the influence of terrorism on investor emotions, and various studies examining investor proxies and moods.
Chapter three outlines the research methodology, detailing the approach taken, the data collection methods employed, the analysis conducted, and the population studied.
Chapter four, this is the section where the data analysis is done and the findings of this research are highlighted and discussed
Chapter five serves as the conclusion, synthesizing the findings from chapter four and summarizing key insights from the literature review This section also presents recommendations based on the conclusions drawn.
Chapter six focuses on self-reflective learning, highlighting the insights gained throughout the research process This section will reference specific events that facilitated learning derived from this dissertation.
Resources such as the questionnaire used and various other sources are included in the Appendix.
Recipients of the research
Despite numerous studies on investor sentiment in various countries, there is a lack of comprehensive research specifically focused on India It is essential to conduct such studies periodically, as investors' attitudes and sentiments can fluctuate over time.
There is a lack of research examining the effects of significant political events, such as terrorist attacks, on the Indian stock markets While numerous studies have explored the influence of macroeconomic events on stock market performance, the specific impact of political turmoil remains underexplored.
Recent studies have not thoroughly examined the effects of significant economic events, such as global oil price fluctuations and domestic financial scandals, on the stock market.
This research targets Indian investors, including both institutional and retail, as well as Foreign Institutional Investors (FIIs) interested in the Indian market, and stock broker companies globally It is also relevant for professionals and students aspiring to build careers in Behavioral Finance, a dynamic and growing field in today's financial landscape.
Scope and Limitations to the research
A survey conducted by the researcher in collaboration with two investment banks in India aims to assess investors' sentiments regarding socio-economic events The study explores how various factors, including terrorism and economic fluctuations, influence their overall mood and investment decisions.
17 oil price to the global recession which took place in 2008 and had engulfed major European countries out of which a few of are still struggling to come out
Before starting the research, several practical issues needed to be addressed The primary quantitative research faced challenges due to confidentiality procedures at two investment banks in India, which hindered access to investors' contact information Additionally, some investors did not provide their names, resulting in a population size of only 90 While a larger sample size would have been preferable, confidentiality restrictions and access limitations made this unfeasible.
Literature Review
Literature Review
Research indicates a potential connection between stock market news content and investor psychology and sociology The role of financial news media remains ambiguous, as it may either influence, exacerbate, or merely mirror investors' perceptions of market performance (Tetlock, 2007).
Investor sentiment and the World
Investor sentiment refers to the overall feeling or tone of a market, often influenced by crowd psychology, as reflected in the activity and price movements of securities It encompasses the tendency to trade based on noise rather than information and is commonly associated with investor optimism or pessimism The term also conveys emotional aspects, leading the media to describe it in terms of investor fear or risk aversion For instance, rising prices signify a bullish market sentiment, while falling prices indicate a bearish sentiment Despite some studies, such as those by Antweiler and Frank, finding no significant impact of "bullish" messages on returns, the concept of investor sentiment remains crucial in understanding market dynamics.
Research indicates a correlation between message activity and trading volume, as well as between message activity and return volatility (2004) Additionally, Coval and Shumway (2001) demonstrate that the ambient noise level in a futures trading pit is associated with volume, volatility, and depth, though it does not affect returns.
Malcolm Baker (2007) highlights that the focus has shifted from questioning whether investor sentiment influences stock prices to measuring and quantifying its effects Specifically, stocks of low-capitalization, younger, unprofitable, high-volatility, non-dividend paying growth companies, or those in financial distress, tend to be more sensitive to fluctuations in investor sentiment Understanding the impact of investor sentiment on stock prices is crucial, as it can significantly affect market movements.
20 to market bubbles followed by massive devaluations, Brown and Cliff (2004) explained
Finter, Niessen-Ruenzi, Ruenzi, in 2011, proposed that the real estate bubble crash in
The 2008 financial crisis highlighted the significant impact of investor sentiment on asset prices globally, particularly in the U.S stock market Most studies focus on retail investors, suggesting they are more influenced by sentiment fluctuations, which lead to stock prices deviating from their fundamental values (Kumar and Lee, 2006) These studies often assume that institutional investors exhibit more rational trading behaviors Therefore, it is crucial to examine whether these findings hold true in other markets with different demographics and investor compositions, addressing a notable gap in existing research on this topic.
Research on the relationship between investor sentiment and volatility in the Indian stock market is limited, with few studies examining the impact of various events on both factors The unique composition and demographics of the Indian market may significantly alter this relationship, highlighting the need for further investigation This project aims to address the existing gap in research, providing a foundation for future analysis and a deeper understanding of how investor sentiment influences stock market volatility in India.
The Impact of investor sentiment
Numerous empirical studies have demonstrated that investor sentiment significantly affects equity returns, with research by Lee, Shleifer, and Thaler (1991), Lee et al (2002), Brown and Cliff (2005), and Baker and Wurgler (2007) highlighting the influence of sentiment on asset prices.
Ho and Hung, 2009; Baker, Wurgler, and Yuan, 2009) These studies find a positive contemporaneous relationship between investor sentiment and stock market returns
Research indicates a correlation between investor sentiment and stock market volatility, highlighting how fluctuations in investor emotions can significantly impact market dynamics (Brown, 1999; Lee et al., 2002).
An exogenous shock in investor sentiment can initiate a sequence of events, potentially observable at various stages of this process This shock manifests in investor beliefs, which can be assessed through surveys These beliefs subsequently influence discernible trading patterns in securities, which are systematically recorded.
Classical Finance and Investor Sentiment
Classical finance theories often overlook investor sentiment, positing that in a competitive financial market, irrational trading behaviors—such as focusing on non-fundamental signals—will be swiftly corrected.
In short, classical finance revolves around two basic premises, that when taken together implies the lack of prolonged arbitrage opportunities a) Financial markets are information efficient b) Market participants are rational
The Efficient Markets Hypothesis, a fundamental principle of modern financial economics, asserts that asset prices accurately reflect all available information regarding the intrinsic value of the underlying security In an ideal market without frictions, the price of a security aligns with its fundamental value, which is determined by the present value of anticipated future cash flows Consequently, the price \( P_t \) of a specific stock or portfolio is equivalent to its expected forecast.
(P*t+1) times of subsequent cash flows and investment risks, conditional on all information available at the current time period This can be stated concisely as:
The Efficient Markets Hypothesis posits that market prices reflect the optimal forecast of future values, indicating that unexpected stock market movements stem from new information regarding fundamental value (P*t+1) Consequently, fundamental value consists of both a predictable component and an unpredictable component.
In the context of forecasting, the error term ut must be uncorrelated with any information available at time t to ensure that all relevant data is considered (Shiller 2003) Additionally, since the price Pt serves as information, it is essential that both Pt and ut remain uncorrelated to maintain the integrity of the forecasting process.
Arguments against Classical Finance Theory
According to the market efficiency paradigm, individuals are presumed to behave rationally, fully considering all available information when making decisions Consequently, when new information about a security arises, rational investors respond swiftly, eliminating excess risk-adjusted returns associated with that information Traditional finance theories suggest that self-interest and arbitrage forces will quickly remove irrational investors from the market, along with any opportunities for risk-free profits.
In real financial markets, arbitrage opportunities are limited due to various trading costs, such as transaction, information, and financing expenses, which can hinder rational arbitrageurs from capitalizing on market mispricings The imperfections of actual financial markets create frictions that complicate the identification and exploitation of perfectly substitutable assets (Shleifer 2000).
Standard financial theories struggle to account for persistent mispricing and unexploited arbitrage opportunities, even when considering fundamental risks and transaction costs Notable financial anomalies, such as the closed-end fund discount and IPO underpricing, serve as empirical evidence that markets may not always operate with informational efficiency.
23 anomalies, one approach has been to appeal to behavioral explanations that relax the strict rationality requirement of standard theories
Baker and Wurgler (2007) emphasize the growing challenge of explaining certain financial events through traditional finance theories, particularly as investors often let emotions influence their asset valuations instead of relying solely on the net present value of future cash flows In this framework, sentiment refers to beliefs about future cash flows and investment risks that lack rational justification based on available information Stock price volatility during market crashes contradicts the assumptions of traditional financial models, which suggest that emotionless investors align capital market prices with the rational present value of expected future cash flows As a result, researchers have sought to enhance these models to account for market crashes Shiller (1987) found that many investors perceived crashes as driven by psychological factors rather than fundamental financial indicators like earnings or interest rates.
Behavioral finance has challenged the notion of market efficiency, which posits that market prices accurately reflect fundamental characteristics and that excess returns are neutralized over time Numerous studies have identified market anomalies—such as unusual price movements related to IPOs, mergers, stock splits, and spin-offs—that standard financial theories fail to explain Throughout the 1980s and 1990s, persistent statistical anomalies indicated that existing finance models might be incomplete Research has shown that investors often do not respond rationally to new information, exhibiting overconfidence and altering their decisions based on superficial changes in how investment information is presented (Olsen, 1998).
In recent years, media interest in technology stocks has surged, often accompanied by a positive bias in assessments This bias may have misled investors, resulting in poor investment decisions These anomalies indicate that the principles of rational behavior, as outlined by the efficient market hypothesis, are not fully applicable in this context.
24 correct and it is needed to be looked at including other models of human behaviour as have been studied in other forms of social sciences (Shiller, 1998).
Behavioral Finance
Behavioral finance is a rapidly growing field that examines how deviations from perfect rationality influence market outcomes, asset prices, and investor behavior This discipline provides more adaptable models for understanding investor sentiment and its effects on financial markets.
In their 2003 paper "A Survey of Behavioral Finance," Barberis and Thaler critique the traditional finance paradigm, which assumes that agents operate under rationality This rationality encompasses two key aspects: first, agents accurately update their beliefs upon receiving new information according to Bayes' law; second, their choices align with Savage's concept of Subjective Expected Utility (SEU), ensuring normatively acceptable decision-making.
The traditional framework for predicting stock returns is attractive due to its simplicity, and it would be gratifying if its forecasts aligned with actual data However, after extensive research, it has become evident that fundamental truths about overall stock performance do not support its predictions.
Bayes' Theorem, introduced by Reverend Thomas Bayes in the 18th century, utilizes conditional probability to enable reverse predictions This mathematical principle establishes the connection between the probabilities of two events, A and B, through their respective conditional probabilities, P(A|B) and P(B|A).
Subjective expected utility, introduced by L J Savage in 1954, is a decision-making framework that addresses risk by integrating two key subjective elements: a personal utility function and a personal probability distribution grounded in Bayesian probability theory This approach builds on earlier contributions from Ramsey and von Neumann, emphasizing the importance of individual preferences and beliefs in decision-making under uncertainty.
25 market, the cross-section of average returns and individual trading behavior are not easily understood in this framework
Behavioral Finance represents an innovative approach to financial markets that has arisen partly due to the limitations of traditional financial theories It posits that certain financial phenomena are more effectively explained through models that account for the irrational behaviors of some market participants.
This article examines the implications of relaxing the two foundational principles of individual rationality in behavioral finance It highlights that some models depict agents who fail to accurately update their beliefs, while others show agents applying Bayes’ law correctly yet making choices that contradict subjective expected utility (SEU) Most asset pricing models rely on the Rational Expectations Equilibrium (REE) framework, which presumes not only individual rationality but also consistent beliefs, as noted by Sargent (1993) Consistent beliefs imply that agents possess accurate forecasts of future unknown variables based on the correct subjective distribution This accuracy necessitates not only the proper processing of new information but also sufficient knowledge about the economic structure to determine the appropriate distribution of relevant variables.
Behavioral finance diverges from the traditional Rational Expectations Equilibrium (REE) model by relaxing the assumption of individual rationality, while another approach maintains rationality but questions the consistency of beliefs In this framework, investors correctly apply Bayes' law but lack the necessary information to understand the actual distribution of variables This area of research is often referred to as bounded rationality or structural uncertainty For instance, a model where investors are uncertain about the growth rate of an asset’s cash flows and learn from available data exemplifies this concept.
Behavioral finance is a rapidly growing field of research that examines how deviations from perfect rationality influence market outcomes, asset prices, and investor behavior.
3 Rational expectations (RE) is a collection of assumptions regarding the manner in which economic agents exploit available information to form their expectations In its stronger forms,
RE operates as a coordination device that permits the construction of a “representative agent" having “representative expectations”
Behavioral finance provides flexible models that enhance our understanding of investor sentiment, effectively explaining financial anomalies like limited arbitrage.
Studies taken up on the Subject of Behavioral Finance
Behavioral finance validation began with studies exploring the correlation between macroeconomic variables and stock prices, revealing that stock prices reflect more than just fundamental factors Niederhoffer (1971) noted the weak stock market reactions to significant events, such as elections and wars, while substantial asset price fluctuations remained unexplained More recently, Cutler, Poterba, and Simmons (1991) found that macroeconomic variables accounted for about a third of stock return variance, with changes in government and financial policies explaining some, but not all, of this variation Shiller (2000) also highlighted that stock price volatility exceeded predictions based on economic indicators Niederhoffer further connected world events to movements in the S&P 500, using significant headlines from the New York Times to demonstrate that these events have a noticeable impact on stock market trends.
500 More specifically, returns following world events tend to be larger in absolute value than returns on other days
Kim and Mei (1994) analyze the Hong Kong stock market's fluctuations in relation to political events, demonstrating through an event-study approach that political developments significantly influence stock prices.
Diamonte, Liew, and Stevens (1996) and Erb, Harvey, and Viskanta (1996) examine the long-term relationship between political risk and stock market returns, revealing that changes in the political environment significantly impact emerging markets like India more than developed markets The studies indicate that macroeconomic factors also influence global markets, while Erb et al (1996) establish a correlation between country-risk measures—encompassing both political and economic risks—and future equity returns Collectively, these studies highlight the importance of understanding the political landscape's effect on stock market performance over time.
Finance experts acknowledge that market fluctuations often reflect investor sentiment, leading to the exploration of behavioral finance as a viable alternative The relationship between asset valuation and the emotions of investors has sparked significant discussion among professionals in the field.
Figure 2.1 2: The Sentiment Seesaw by M Baker & J Wurgler (2006)
The sentiment seesaw by M Baker summarizes this perspective into a simple, unified view of the effects of sentiment on stocks
The x-axis categorizes stocks based on their valuation and arbitrage complexity, with bond-like stocks, such as regulated utilities, positioned on the left side In contrast, stocks from newer, smaller, more volatile, distressed, or high-growth companies are found on the right side.
The y-axis represents prices, with P* indicating fundamental values that can fluctuate over time The accompanying lines demonstrate the core assumptions regarding the impact of sentiment shifts on stock valuations.
High investor sentiment typically correlates with elevated stock valuations, especially for stocks that are difficult to value and arbitrage Conversely, low sentiment tends to drive down valuations When sentiment is neutral, stocks are generally perceived to be fairly valued on average.
29 priced at P* An empirical question that arises in the drawing of Figure is where to locate the crossing point of this seesaw
In a scenario where no crossing point is present, the high-sentiment line remains entirely above the no sentiment P* line, which is also above the low sentiment line This indicates that as sentiment rises, stock prices increase across the board, albeit at varying rates Consequently, the overall impact of sentiment on the market is significant, as stock indexes reflect the average performance of the underlying stocks.
The data illustrates a scenario where the prices of highly secure, easily arbitraged stocks are inversely correlated with market sentiment This phenomenon may arise when shifts in sentiment lead to significant variations in the demand for speculative securities, potentially causing investors to seek safer investments, often referred to as "flights to quality" in the stock market.
Market episodes can lead to a decline in speculative stock prices while simultaneously boosting bond-like stock prices, even when fundamental factors remain unchanged As a result, the impact of investor sentiment on overall market returns may be diminished, as stocks are not uniformly reacting in the same direction.
Behavioral theory offers distinct cross-sectional predictions regarding the impact of sentiment; however, the overall predictions are less definitive, which may clarify the inconsistent statistical outcomes observed in studies from the 1980s.
The stocks become underpriced or overpriced at periods of high or low sentiment, which leads to predictable subsequent returns (Baker and Wurgler, 2006: Qiu and Welch, 2006)
There was a study carried out by Peter (1970) to identify those factors which motivate or guide the investment decisions of the retail stock investors The study identified
30 factors such as income from dividends, rapid growth, purposeful investment as a protective outlet of savings and investment management
In a study conducted by Shanmugam (1990) involving 90 investors, the research aimed to identify the factors influencing investment decisions, particularly focusing on investment objectives and awareness levels The findings revealed that these investors were high-risk takers, demonstrating a strong understanding of government regulations as well as monetary and fiscal policies.
In 1996, researchers developed comprehensive lifestyle and demographic profiles of investors, focusing on the value and types of their investment holdings Subsequently, Krishnan and Booker (2002) examined the key factors that influence investor decisions, particularly highlighting the reliance on analysts' recommendations for making short-term choices regarding whether to hold or sell stocks.
Sachithanantham et al (2007) examined the impact of capital market reforms on investor investment levels in the Indian Capital Market Their findings revealed that while educational and attractive reforms were statistically significant, they negatively affected the amount of money invested by investors.
A study by Bennet et al (2011) revealed that investors generally anticipate stock prices to rise beyond their initial investments They believe that if the market declines, it will recover, and if it is already performing well, it will continue to rise Consequently, their investment decisions are based on the expectation of achieving superior returns from the stock market.
Terrorist activities and Investor Sentiments
The question of whether terrorist activity can be considered a mood proxy is explored by Edmans et al (2007), who assert that effective mood indicators must meet three key criteria to establish a connection with stock returns Firstly, the chosen variable should significantly and clearly influence mood, creating a strong impact that can be observed in asset prices Secondly, it must affect a large segment of the population, thereby likely influencing investor sentiment Lastly, the mood's impact must be consistent across the majority of individuals within a country.
Terrorist events, which are inherently unpredictable and external to stock market fluctuations, serve as a strong proxy for investor sentiment These events uniquely fulfill key criteria, as they are among the few social occurrences that can induce significant and closely correlated mood shifts within a nation's populace.
Under the null hypothesis of Market Efficiency, terrorist activity should not influence stock returns; however, the alternative hypothesis suggests that such incidents do significantly impact returns, aligning with investor sentiment models If investor sentiment is swayed by terrorism, we can predict that on trading days when terrorist events occur, risk-adjusted returns will be notably lower Furthermore, the impact on stock returns is expected to increase with the severity of the event, as terrorist activities are believed to lead to a decline in investor sentiment.
The relationship between the severity of a terrorist attack and its impact on the population is significant; as the severity increases, so does the likelihood of affecting a larger proportion of individuals This correlation highlights how more severe attacks tend to influence a greater number of people.
Impact of Oil Prices
Fluctuations in crude oil prices play a crucial role in understanding stock price movements Over the long term, the impact of oil prices on stock markets is significant, as changes in oil prices affect macroeconomic indicators that ultimately influence market liquidity.
Changes in oil prices significantly influence key macroeconomic indicators, which subsequently impact the long-term equilibrium relationships among various markets These changes are driven by observable economic factors, while also being affected by speculative elements that operate within the market over shorter timeframes.
Market conditions can interact in complex ways, leading to scenarios where a market may exhibit speculative strength while remaining fundamentally weak Theoretical frameworks suggest that oil-price shocks influence stock market returns and prices primarily by impacting expected earnings (Jones et al., 2004).
Using oil price changes as a measure for shifts in key macroeconomic indicators is rational because stock prices theoretically reflect the discounted expectations of future cash flows, such as dividends, which are influenced by macroeconomic events potentially triggered by oil shocks An increase in oil prices raises production costs in industrialized oil-consuming countries and is expected to elevate the cost of imported capital goods, negatively impacting the profit outlook for firms listed on Indian stock markets.
Rising oil prices lead to an overall increase in prices, reducing real disposable income and subsequently lowering demand Additionally, the direct effects on price levels can influence wage levels, contributing to heightened inflation Central banks often respond to inflationary pressures by raising interest rates, making bond investments more appealing than stocks, which in turn can lead to a decline in stock prices.
Rising import prices lead to a decline in terms of trade, resulting in welfare losses for importing countries Conversely, oil-exporting nations experience increased export revenues, although these gains may be threatened by a potential decrease in global oil demand.
Liberalization and integration of international markets economies (Chittedi 2010,
The surge in capital flows and international investments in emerging markets since 2011 has heightened global investors' vulnerability to the effects of oil price fluctuations on stock markets Understanding how susceptible stock prices in these economies are to global oil price movements is crucial However, research by Huang, Masulis, and Stoll (1996) revealed no negative correlation between stock returns and changes in oil futures prices Most studies have focused on the relationship between oil prices and stock prices in developed countries, leaving a gap in the analysis of developing nations.
Volatility
Stock prices fluctuate daily based on market dynamics, influenced by the perceptions of buyers and sellers regarding the value of each stock The financial markets often display significant volatility, which can seem disproportionate to fundamental changes This phenomenon has been the subject of extensive research and analysis over the years.
Share prices fluctuate due to the forces of supply and demand; when more investors seek to buy a stock than sell it, prices rise, while an excess of sellers leads to falling prices This volatility is a fundamental characteristic of the stock market, characterized by alternating bull and bear phases In a bullish market, share prices experience significant increases, whereas in a bearish market, they decline.
34 downs determine the return and volatility of the stock market Volatility is a symptom of a highly liquid stock market
Increased stock market volatility leads to significant fluctuations in stock prices, prompting investors to perceive higher risks associated with equity investments As a result, many choose to reallocate their funds to safer assets Additionally, shifts in the local or global economic and political landscape impact share price movements, reflecting the overall condition of the stock market to the public.
In their 2009 article, Pandian and Jeyanthi highlighted the adverse effects of the 2001 Gujarat earthquake, rising interest rates, and inflation on the corporate sector They noted the proposal to increase the tax on dividend distributions by companies and mutual funds from 10% to 20% as a negative indicator Additionally, they pointed out that recurring financial scams have consistently exposed the vulnerabilities within the regulatory framework and the finance and capital markets.
One can see below some of the important sentiment proxies, and previous work done on few of them, such as-:
Research by Kamstra, Kramer, and Levi (2003) highlights a connection between investor mood and stock prices, revealing that market returns tend to be lower during the fall and winter months This decline is attributed to seasonal affective disorder, a type of depression linked to reduced daylight Their findings, which show consistent patterns across various latitudes and both hemispheres, support the idea that emotional changes can significantly influence market performance.
Retail investors, often less experienced than professionals, tend to be influenced by market sentiment Research by Greenwood and Nagel (2006) indicates that younger investors are more prone to purchasing stocks at market peaks, such as during the Internet bubble Additionally, Barber, Odean, and Zhu (2006) demonstrate through micro-level trading data that retail investors frequently buy and sell stocks in unison, reflecting a pattern of systematic sentiment Kumar and Lee propose the development of sentiment measures for retail investors, focusing on their buying and selling behaviors.
Trading Volume Trading volume, or more generally liquidity, can be viewed as an investor sentiment index For instance, Baker and Stein (2004) note that if short-
Selling incurs higher costs compared to opening and closing long positions, which influences trading behavior Irrational investors tend to engage in more trading when they are optimistic about rising stocks, contributing to market liquidity In contrast, they are less active when pessimistic about falling stocks Market turnover, defined as the ratio of trading volume to the number of shares listed, serves as a straightforward indicator of this phenomenon.
Implied volatility in options pricing increases when the underlying asset is expected to experience greater volatility Models like the Black-Scholes formula can be inverted to derive implied volatility from options prices The Market Volatility Index (VIX), which tracks the implied volatility of options on the S&P 100 index, is commonly referred to as the "investor fear gauge" by market professionals.
Insider trading occurs when corporate executives use their superior knowledge of their firm's true value to inform personal investment decisions This practice, while legally questionable, can indicate executives' perceptions of their firm's mispricing Additionally, if market sentiment causes widespread mispricing among firms, the patterns of insider trading may reflect a broader systematic sentiment influence.
IPO volume is highly influenced by investor sentiment, leading to significant fluctuations in the number of initial public offerings Investment bankers refer to "windows of opportunity" that unpredictably open and close, which contributes to these erratic changes in IPO activity.
100 issues per month in some periods and zero issues per month in others
High trading volume often indicates market liquidity and can signal overvaluation, as suggested by Baker and Stein (2004) In markets where short-sale constraints exist, retail investors tend to engage more actively when they are optimistic, leading to increased trading volume Consequently, liquidity tends to rise during periods of trader optimism.
A financial model for price variation over time, particularly for stocks, is essential for determining the price of European call options This model is based on the assumption that heavily traded assets exhibit geometric Brownian motion with consistent drift and volatility When utilized for stock options, it factors in the stock's constant price fluctuations, the time value of money, the option's strike price, and the time remaining until the option's expiration.
The Volatility Index (VIX) serves as a crucial indicator of market expectations regarding short-term volatility Essentially, volatility reflects the potential for significant price fluctuations When market conditions are highly volatile, the VIX typically increases, indicating sharp upward or downward movements Conversely, the VIX decreases as market volatility subsides.
36 and betting on rising stocks rather than when they are pessimistic and betting on falling stocks
Dividend premium: In general, dividend-paying stocks have a predictable income stream which investors perceive as a salient characteristic for safety (Baker, Wurgler
In times of high dividend premiums, companies are more inclined to distribute dividends, while they tend to withhold them during periods of low premiums This behavior suggests that firms respond to market sentiment regarding financial "safety" when making dividend payment decisions.
Terrorism has already been discussed above as a proxy Other than this, the macro- economic events also have been discussed above in detail are optimal candidates as proxies.
Conclusion on Literature Review
Previous studies have explored various sentiment proxies and their impact on aggregate market returns and future predictions Currently, multiple methods exist to gauge market sentiment, including investor surveys conducted in several countries In the U.S., organizations such as the American Association of Individual Investors (AAII) and the University of Michigan’s Consumer Confidence Index regularly survey investors about their economic outlook Research by Fisher and Statman (2003) indicates that a rise in consumer confidence correlates with increased bullishness among individual investors, while Qui and Welch (2006) highlight the consumer confidence index as a useful predictor of excess returns on small stocks However, research on emerging markets like India remains limited, with notable studies by Bennet et al (2011, 2012), Loomba (2012), and Kaur (2004) This research aims to provide a comprehensive analysis of Indian investor sentiment and its relationship with stock market volatility, synthesizing existing literature in the field.
Research Methods and Methodology
Introduction
The first crucial step in undertaking a Master's level dissertation is to establish a clear and robust research methodology, ensuring that the gathered data effectively addresses the primary research objectives According to Blumberg et al (2009), there are nine criteria that collectively define "desirable, decision-oriented research."
1 The purpose of the research should be clearly defined and common concepts
2 The research procedure used should be described in sufficient detail to permit another researcher to repeat the research for further advancement, keeping the continuity of what has already been attained
3 The procedural design of the research should be carefully planned to yield results that are as objective as possible
4 The researcher should report with complete frankness, flaws in procedural design and estimate their effects upon the findings
5 The analysis of data should be sufficiently adequate to reveal its significance and the methods of analysis used should be appropriate The validity and reliability of the data should be checked carefully
6 Findings should be clear and unambiguous
7 Conclusions should be confined to those justified by the data of the research and limited to those for which the data provide an adequate basis
8 Research design clearly described and carefully planned
9 Greater confidence in research is warranted if the researcher is experienced, has a good reputation in research and is a person of integrity
The research will follow Blumberg’s methodology in order to ensure that a suitable standard of research is attained
Kothari (2009) stated that the qualities of a good research can be obtained by
A systematic approach in research ensures a coherent and logical flow, emphasizing the importance of empirical evidence that connects to real-world situations Additionally, effective research should encompass various aspects of these real situations to enhance its relevance and applicability.
“replicable” so that the results are verified by replacing the study and thereby building a sound basis for decisions
Blumberg’s methodology will be employed to ensure a systematic approach and intellectual rigor in the design, while the suitable research methodology will be determined by examining each layer of the Saunders et al (2009) 'research onion.'
3.1 3 The Research Onion, Mark Saunders, Philip Lewis and Adrian Thornhill,
The Research Philosophy
Research philosophy, as outlined by Saunders et al (2009), encompasses the fundamental assumptions that shape how a researcher perceives the world These assumptions significantly impact the chosen research strategy and methods, highlighting the critical role of research philosophy in guiding the entire research process Ultimately, the selected philosophy reflects the researcher’s unique perspective on the relationship between knowledge and its development.
To determine the most appropriate research philosophy for explaining research objectives, one must consider the two primary philosophies: Positivism and Interpretivism Positivism advocates for applying natural science methods to study social realities, focusing on manipulating a single independent variable to identify patterns and relationships within the social world (Bryman and Bell, 2011) In this approach, existing theories guide hypothesis development, which are then tested to refine or create new theories Positivism emphasizes that only confirmed knowledge qualifies as valid, prioritizing factual data over subjective impressions The researcher maintains an objective stance, remaining independent from the data collection process, which allows for minimal influence on the findings (Saunders et al., 2009).
Interpretivism contrasts with positivism by emphasizing that the subject matter of social sciences—people and institutions—differs fundamentally from that of natural sciences This philosophical approach highlights the unique complexities of human behavior and social interactions, advocating for a deeper understanding of the social world.
Interpretivism emphasizes the subjective exploration of social phenomena to achieve a deeper interpretive understanding Blumberg et al (2008) argue that simple laws cannot capture the complexity of social realities, asserting that only through subjective interpretation and intervention can we truly comprehend these realities This perspective stands in stark contrast to positivism, highlighting the need for a more nuanced approach to understanding social dynamics.
The researcher must adopt a sympathetic stance, acknowledging that they are "value bound" and inherently part of the research process, which introduces subjectivity into their findings (Saunders et al., 2009).
Given that neither the objectivity of positivism nor the subjectivity of interpretivism aligned with the research objectives, the researcher opted for realism as a suitable philosophical approach Realism occupies a middle ground between positivism and interpretivism, offering a balanced perspective for the study.
Realism is a research philosophy that integrates principles from both positivism and interpretivism, acknowledging an independent reality while recognizing the subjectivity of human behavior There are two types of realism: direct realism, which asserts that sensory experiences accurately reflect the world, and critical realism, which emphasizes the need to understand the social structures influencing phenomena The research on investor sentiment aligns with direct realism, focusing solely on explaining the phenomena without suggesting any changes.
The researcher has selected Direct Realism as the most appropriate research philosophy due to its ability to facilitate the examination of scientific data and assess its validity effectively.
The Approach Layer
To identify the most suitable research approach, it is essential to understand the distinctions between deduction and induction.
An inductive approach, as outlined by Cooper and Schindler (2008), lacks a strong relationship between theory and research, with conclusions drawn from specific facts or evidence While these conclusions aim to explain the observed facts, they remain hypotheses, representing an "inferential jump beyond the evidence." Lincoln and Dengin (2006) note that this method focuses on significant observations or single case studies to inform broader theories and generalizations, commonly referred to as a bottom-up approach.
This approach focuses on the subjective aspects of human psychology, aiming to explore deeper insights While it draws from behavioral finance, it is not appropriate for this research, which relies on scientific principles and logical conclusions that can be empirically validated Additionally, the observations in this study are conducted quantitatively.
Deductive theory is a prevalent perspective on the relationship between theory and research, as noted by Fisher (2004), who describes deduction as drawing logical conclusions from stated premises without relying on observations Saunders et al (2009) further emphasize that the deductive approach is rooted in scientific research, beginning with hypothesis development from theory, followed by data collection to confirm or reject the hypothesis This top-down approach, as termed by Fisher (2004), seeks to explain causal relationships between variables while maintaining the researcher's independence from the observations Additionally, it requires that concepts be operationalized for quantitative measurement, ensuring scientific rigor.
Robson (2002) as cited by Saunders et al (2009) lists five sequential stages through which deductive research will progress:
1 deducing a hypothesis from the theory;
2 expressing the hypothesis in operational terms which propose a relationship between two specific concepts or variables;
4 examining the specific outcome of the inquiry;
5 if necessary, modifying the theory in the light of the findings
The research employs a deductive approach, which is suitable due to its rigorous and scientific nature This method allows the researcher to formulate and test hypotheses while elucidating the causal relationship between investor sentiment and stock market volatility.
Research Strategy
Research strategy is defined as the overarching plan for addressing research questions (Saunders et al., 2009) and serves as a general orientation for conducting research (Bryman, 2008) It outlines the overall direction and methodology of the research process (Remenyi et al., 2003) Selecting an appropriate research strategy is crucial and should be based on the research questions and objectives, existing knowledge in the field, available time and resources, and the researcher’s philosophical stance (Saunders et al., 2009).
Selecting a research strategy requires careful consideration of three key factors: the type of research question, the investigator's control over behavioral events, and the focus on either contemporary or historical events Various strategies, including experiments, surveys, case studies, action research, and grounded theory, each possess unique characteristics based on these criteria Notably, researchers like Yin (2003) and Saunders et al (2009) recognize significant overlaps among different strategies, emphasizing the importance of choosing the most suitable approach for a specific study in business and management.
Certain methods like Action Research and Experimentation may not be suitable for addressing the research question However, Case Study and Survey require further evaluation due to their similarities, particularly in utilizing multiple data sources to validate scientific statements and form opinions in specific research areas.
The researcher came to the conclusion that a case study strategy would be the most suitable strategy to adopt for the research Robson (2002) as cited by Saunders et al
A case study, as defined by Yin (2009), is a research strategy that entails an empirical investigation of a specific contemporary phenomenon within its real-life context, utilizing multiple sources of evidence.
(2003) definition included; a case study deals with technically distinctive situation, relies on multiple sources of evidence, and benefits from prior development of theoretical prepositions to guide data collection and analysis
Experiment How, why Yes Yes
Archival analysis Who , What, Where,
History How, Why No No
Case study How, Why No Yes
3.1 4 The Table for Research Strategy, Yin 2003
According to Saunders et al (2009), a case study strategy serves as an effective explanatory research method that employs a variety of data collection techniques in combination While questionnaires are typically associated with survey strategies, they can also be utilized within case study frameworks In this research, the investigator plans to integrate multiple data collection methods, specifically using questionnaires alongside previously recorded historical data.
The Choices Layer
The research design which would be followed for the research is the ‘Multiple- methods’ approach as after considering all the methods available (i.e mono method
The researcher has opted for a multi-method quantitative study, employing various data collection techniques to ensure a detailed and comprehensive interpretation of the primary data gathered and analyzed This approach emphasizes the exclusive use of quantitative methods to enhance the depth of the research findings.
The researcher has opted for a multi-method quantitative study, utilizing various data collection techniques solely within the quantitative realm This approach involves gathering data from stock markets and employing a quantitative survey questionnaire to gauge investor sentiment, thereby enhancing the robustness of the research findings.
The researcher recognizes both the benefits and limitations of the quantitative technique employed, particularly when using questionnaires as part of a case study survey strategy While the simplicity of administering fixed-response questions can enhance data analysis by reducing response variation, there is a concern that overly rigid options may dominate the questions, leading to potentially inaccurate results Additionally, the researcher notes the risk of participants misinterpreting questions or the survey's intent due to the absence of guidance during completion.
The researcher was cautious of the drawbacks of the methods throughout the process and felt that the positive aspects of the process outweighed the negative aspects throughout the research
Time Horizons Layer
When selecting a research methodology, one crucial factor to consider is the time horizon, which can be categorized into cross-sectional and longitudinal approaches According to Saunders et al (2009), cross-sectional research provides a "snapshot of one point in time," while longitudinal research spans an extended period, enabling researchers to observe developments and changes over time.
This dissertation will adopt a cross-sectional time horizon to analyze the sentiments of Indian investors at specific historical moments, correlating these sentiments with stock market volatilities during those events.
Data Collection and Data Analysis
Data can be classified into two main types: primary data and secondary data Primary data refers to original information collected firsthand by the researcher, while secondary data consists of existing information gathered from publications or electronic media According to Kothari (2009), primary data is unique and collected for the first time, whereas secondary data has been previously collected and processed statistically, often through literature studies In this dissertation, the researcher will utilize both primary and secondary data to effectively meet the research objectives.
This research utilizes secondary data obtained from various academic journals available on EBESCO and college library databases, focusing on key searches such as "Stock Market Volatility," "Behavioral Finance," and "Investor Sentiments." Data for the SENSEX during the specified period was acquired from the official Bombay Stock Exchange (BSE) website, while stock market volatility, average daily returns, and investor sentiment data were primarily sourced from Securities Exchange Board of India (SEBI) bulletins and BSE announcements Additionally, sentiment data was gathered from the Boston Analytics Consumer Sentiment Index of India.
The primary quantitative data for this research was collected through a survey questionnaire, a widely utilized data collection technique in survey strategies, as noted by Saunders et al (2009) This method allows each participant to answer the same set of questions, facilitating efficient data collection from a large sample The researcher personally administered the questionnaire, ensuring that respondents—primarily stock-market investors from two investment banks in India—completed it independently.
The survey aimed to gather background information on the current sentiments of investors in India, as well as their feelings during significant events Additionally, it sought to understand investors' future outlook based on their perceptions of the present situation.
The validity and reliability of collected data, as well as the response rate, are significantly influenced by the design of the questions and the overall structure of the questionnaire (Saunders et al., 2009).
When designing a questionnaire, the researcher must first identify the research objectives and the specific goals of the questionnaire A thorough review of relevant academic literature aids in formulating essential questions The resulting questionnaire was straightforward, focusing solely on the investor's mindset It included inquiries about respondents' perceptions of the current, past, and future investment landscape in India, along with the influence of significant events on their investment choices All questions were structured as forced-choice, avoiding open-ended formats to minimize response variance and facilitate comparison Various types of forced questions were employed to ensure respondents had a range of alternatives and considered all possible options.
Data Analysis
The researcher employed the SPSS tool to analyze the findings and data, which were collected from various sources and subsequently processed using this statistical software.
To gauge investor sentiments effectively, the researcher focused on a specific demographic comprising both retail and institutional investors in the stock market The quantitative analysis was conducted among clients of two prominent investment banks in India, with a total of 90 respondents participating in the survey.
This population was chosen in order to provide a basis for this case study and to get a better understanding of the current and previous sentiment of the investors relating to
Both banks offer identical services to customers with DEMAT Accounts, leading to a uniform investor population across both institutions This consistency ensures that the investment decisions made at various events are not biased toward any specific group, resulting in reliable and comparable outcomes.
The sampling frame used is as follows;
Unit: Stock market investors who have been investing in shares and securities since 2008
Extent: Investors in two leading investment banks in India
3.8.2 Ethical issues in data collection
According to Udo Schüklenk (2005), the primary goals of ethics are to guide our actions in specific situations and to offer compelling justifications for those actions.
Research ethics encompass the entire research process, from the relationship between the researcher and the research objective to the writing and publishing of the report, as highlighted by Eriksson et al (2008) It is crucial to uphold ethical behavior consistently throughout this process to ensure integrity and credibility in research.
A DEMAT account is an electronically maintained account offered by banks or broker agencies in India, allowing you to hold funds for transactions involving shares, mutual funds, and gold purchases It must be linked to your savings account, which facilitates payments for share purchases and receives funds from share sales.
Ethics play a crucial role in the research process, particularly in the context of a dissertation They encompass the practices that ensure study participants are treated with respect, while also safeguarding their privacy and maintaining the confidentiality of their data.
The research questionnaire was designed without requesting personal data, and respondents were only asked to optionally provide their names, aligning with ethical research practices as noted by Eriksson et al (2008) Additionally, the researcher avoided sensitive topics, refraining from inquiries about investors' income, investment amounts, or shareholdings.