CHAPTER 1: INTRODUCTION

Human decisions are dominated by emotions and not by rationale and they are hard to predict. (Kuzmina, 2010). Similar funds and securities can have different trading values depending on where securities trade and the price difference on the asset is based on investor sentiment (Bodurtha, 2015) ( (Froot, 1999). Modern Finance theory asserts that markets are efficient which is not the true case (Ahmed, 2013).  Each investor is unique in all aspects and hence cannot agree on decisions made by others (Chan-Lau, 2015). When designing, or formulating an investment portfolio, he/she needs to analyze, and take the risk involved in the securities, its goals and constraints. Classical financial theory supports the argument that investor decisions are rationale and bound by wealth maximization. (Windsor, 2010). It completely neglects investor sentiments. Earlier researchers would make investments based on performance in the stock market, market trends, forecasting and various events which would cause a jump in the stock market. Most of these decisions were an impact of the psychological decision making which can lead to various losses and mistakes. Evidence does indicate that negative relationship exists between stock and sentiments (Brown.G.W, 2005). Thus, evolved the concept of behavioral finance and study of investor sentiments. A paradigm suggests that investment decisions are hugely based on psychology or emotional factors. This paper would comprise of the theory aspects of investor sentiments, how Ireland investors make decisions based on such sentiments and whether the change in pricing affects the stock market and if this behavior is consistent. Are Ireland stock markets driven by sentiments or just based on fundamentals is the basic idea behind this research paper.

1.1 Research Structure

Research structure of this research paper is as follow:

Chapter 1: Introduction

The first chapter of the research gives a broad overview of the research background, aims, objectives and questions. At the same time, also discussed is research justification and structure which gives a brief introduction regarding the research topic

Chapter 2: Literature Review

In this chapter, I have discussed about investor sentiment based on critical analysis. For this purpose, references of various existing theories, concept & framework related to the topic have been used which support the study in an effective manner. Also, I have referred to relevant articles, books, journals, periodicals in order to collect relevant data.

Chapter 3: Research Methodology

This chapter, details the research methods which are used for the purpose of collecting the data. While doing so, I have used the secondary data analysis method to analyze in depth the using Irish Stock Exchange, Michigan Consumer Index, S&P 500 Index and Consumer Sentiment Index.

Chapter 4: – Data Analysis

This part of the paper deals with the analysis of the data using the qualitative approach to correlate the research findings with secondary data. I have used the graphical representation in terms of tables, charts and figures to increase the relevancy and effectivity of my findings.

Chapter 5: Conclusion & Recommendations

The last chapter concludes the study by summing up the whole research in contrast to the aims and objectives that were set out at the start. Not only have I articulated the summary of our findings but also provided potential recommendations to aid the relationship between investor sentiments and stock returns.

1.2 Research Background

Sentiments are optimistic as well as pessimistic, which play a vital role towards the decision-making process with regards to the investment in the financial market (Kearney, 2014). It assumes the role of innate urge to actively manage, which empowers the wheels to go around while choosing the options amongst the alternatives at best while calculating various parameters.

In context of Ireland, it is identified that early contribution towards the sentiment is linked with biased expectations and noise. Investor’s sentiment is associated with different attributes while dealing in the financial market. While making decisions regarding the investments, investors give focus to the formation of future cash flows. At the same time, investment risks are focused which are not justified by the existing facts. (Siganos, A., Vagenas-Nanos, E., & Verwijmeren, P., 2014) speculated that in context of Irish markets, irrational investors have a power to move the prices, which reflects their sentiment while evaluating different asset valuations between arbitrageurs and retail investors. Based on this, it has been identified that investors’ sentiment is based on rational as well as irrational evaluation of asset depending on its characteristics.

(Fernandes, C., Gama, P. M., & Vieira, E, 2016) in their paper suggested that researchers make investments while focusing on stock market performance, market trends, forecasting and other events related to rational evaluation. Based on the study, it can be considered that investment decisions are hugely influenced by psychological or emotional factors. It is therefore essential to study this factor in order to get an in-depth knowledge about the investment decisions  (Chan-Lau, J. A., Liu, E. X., & Schmittmann, J. M. , 2015). This research paper has been backed up by a detailed understanding of the research topic with its underlying focus on various theories related to investor opinions and its impact on financial market, particularly with regards to Ireland.

Similar funds and securities can have different trading values as it depends on the place where security trading has taken place and the differential pricing of an asset as it is based on investor sentiments. Different investors have different perception and every individual is unique in different aspects due to which they do not agree on similar decisions. This is the main driving force behind market based movements as it is influenced by the investor’s mood through various mediums such as internet, news, financial periodicals, and much more (Chan-Lau, 2015)

1.3 Research Aims & Objectives

Investor sentiments need to analyze sentiment proxies that can remain useful for long. Large number of authors have studied investor sentiments in the stock markets. They were either biased, mispriced or the statistical data used was not strong enough. To understand the investor sentiments better, we need to examine them and understand if investor sentiments have an influence on the market returns and value of the stock returns. Investor sentiments can be a combination of many factors such as, the liquidity indicators (Raissi, 2015). To generate stock performance, the investor sentiment of various markets and investors is critical. By the data published in the markets, such sentiments could be affected. Macro-economic factors could also be a reason for changes in behavior of the investors and we need to analyze the situations and conditions in which changes occur.

Studies have shown that change in equity value and consumers way of thinking are correlated (Otoo, 1999). There have been various studies on investor sentiments related to behavioral finance and stock markets. Much of the literature review looks at classical finance theories, behavioral finance and efficient markets hypothesis (EMH). EMH focuses in brief about investor sentiments in financial markets but has not much been explored or contributed towards in terms of how new policies and changes in financial markets have affected Ireland. Ireland being predominantly an IT and Finance hub, has seen many Foreign Direct Investments due to the large multinational firms. These companies have large clientele dealings globally and it would definitely benefit the research paper to understand the effect of behavioral change on these sentiments and the markets on the whole. With this agenda, the below objectives can be a source of contribution to the study.

1.3.1 Research Objective

The main focus of this study is to identify the relationship between investor sentiments and stock returns while focusing on the sentiment data which is used by the investors in the market. It also tries to evaluate the ways to use sentiment data by the investors especially during important market events. More precisely, to understand the protruding factors that can influence an investor’s sentiments like confidence index, anomalies and how the stock market force can be a deciding factor in evaluating these sentiments. We cannot identify a stocks sensitivity easily even with the seven stock proxies developed by (Baker, M. and Wurgler, J, 2007) as each anomaly varies per different proxies chosen.

1.3.2 Research Justification

Investor sentiments are based on the combination of many factors like the liquidity indicator (Siganos, A., Vagenas-Nanos, E., & Verwijmeren, P., 2014). So, to develop the stock performance, it is imperative to focus on the investor sentiment of the market. Data publishing in the markets and other macro-economic constituents are other factors which brings changes in the behavior of the investors. Due to this reason, we need to analyze and examine the situations as well as conditions in which such changes occur.

Furthermore, this study has been worked upon to evaluate the changes in the equity value and consumers’ way of thinking on the basis of their sentiments while correlating both the factors (Spyrou, S., 2016). While the local and multinational companies in Ireland continue to make progress, it is important for these firms to understand their investor’s sentiments and how these behavioral aspects could affect the markets in the long run.  Post Brexit, the significance of this study has increased and we need to examine how investors in Ireland perceive it (Caporale, G. M., Spagnolo, F., & Spagnolo, N`, 2016)

1.4 Why Investor Sentiment is important?

(Thorp, 2004) recommends constructing a decision tree to identify the investor decisions made on the basis of sentiment index which move in opposite directions as per bullish and bearish sentiments. A bullish sentiment is observed when investors invest heavily in the stock market bringing share prices to an all-time high. On the contrary, bearish sentiment shows the opposite. Market indicators are used to analyze different approaches in the market leading to a contrarian indicator. (Thorp, 2004).

(Amy Chang, 2016)  suggests creating a decision-making process. The first step would be to select a sentiment index with high probability. Second step would be to identify the risk level based on bearish and bullish market sentiment. Thirdly, forecast the movement and form future anticipation. Lastly, Make investment decisions on the basis of buy or sell.

Figure 1: Investment Decision Making Tree

CHAPTER 2: LITERATURE REVIEW

2.1 Introduction

In this chapter, I have critically analyzed the research topic theoretically while focusing towards the past studies. Normal observations have suggested that news content can be linked to psychology of investors, but it’s unclear if this news induce or just plainly reflect interpretations of an investor’s performance (Tetlock, 2007).

2.2 Theoretical Concept

2.2.1 Investor Sentiments

A typical finance theory does not give much importance to investor sentiments. It can be perceived simply as a view of an investor about the market. There is no single definition which can define Investor Sentiment. Existing literature review can be biased or vague depending on the research done. It can be seen as an investor’s optimistic or pessimistic outlook.  Investor sentiment is how beliefs are cultivated by the investors. The theory is based on the empirical observation of both overreaction and lack of reaction of investors inconsistent with the weak-form and the semi-strong form of the EMH (Aziegbemhin, C. A, 1998). The concept of investor sentiment is still abstract. (Baker, M. and Wurgler, J, 2007) define investor sentiment as investors’ misevaluation of an asset. (Black, 1986) refers to investor sentiment as the noise in financial markets. Investors use technical analysis and indicators to measure price changes and profit from the investor’s attitude towards its portfolio and securities. It basically determines the difference between asset price and what it should be.. The research also studies how stock market volatility is impacted by investor sentiment (Portniaguina, Lee., 2002) Investor sentiment is the overall attitude of the investors towards particular security as well as financial market. Investor sentiment is the psychology of the investor which is revealed through the activity and price movement of the securities when traded in the market. In this context, (Danbolt, J., Siganos, A., & Vagenas-Nanos, E, 2015) depicted that rising prices indicate towards bullish market sentiment. However, on the contrary, falling prices indicate bearish market sentiment. Investor sentiments play crucial role in different economic issues, such as bank crisis, poverty traps, currency attacks and much more. (Gödl, M., & Kleinert, J, 2016) portrayed that investor sentiment consists market-wide component while focusing towards price influence with regards to various securities in a direction. At the same time, during the bubble period, investors’ enthusiasm pushes the price above the levels while justifying the standard measures of value.

According to (Bathia, D., & Bredin, D., 2013), investor sentiment is not always based on fundamentals and it plays a key role in decision making for the day traders and technical analysts as they use technical indicators for measuring the profit while showing concern towards short-term price changes which is measurably caused due to investors’ attitudes towards the security factor. Investor sentiment also remains helpful for contrarian investors to trade in the opposite direction for instance if everyone is buying then a contrarian investor would sell (Zhao, Z., & Ahmad, K. , 2015).

2.2.2 Financial Market in Ireland

Financial markets are controlled highly as compared to the other markets. Ireland had experienced one of the most awful financial crisis during the global financial recession in 2008. Following which it saw an increase in credit extensions, bank lending and borrowing from international markets. Since the collapse of the banking sector the Irish government guaranteed all investors in the financial markets which the then Ministry of Finance termed as the cheapest form of bank rescue (Carswell, 2008). Ireland was considered a prosperous economy until the financial crisis hit them hard and they have recovered largely proving to be a good example to other economies.  As rightly said by (O’Mahony, 2016) “Market numerology feeds investor illusions”. Investors believe in different illusions like not trading in rounding numbers in a stock exchange or giving significance to multiples. When conducting surveys using consumer confidence index, the European markets, include questions on economic and financial situation and gage consumers reactions and any change in the index correlates to high or low stock price in the markets (Zouaoui, 2011).

2.3 Relationship between Investor Sentiments and Stock Returns

Investor sentiment is a very wide-ranging aspect and can be used in diverse ways by stock traders, the media, investors, individuals etc.  Three market ratios – Discount of closed end fund, Price-earnings ratio and Turnover rate used by (Robert Neal and Simon M. Wheatley, 1998) were the first to be used as investment indicators. In the many behavioral models of securities markets inspired by  (Delong, 2007) Investors are of two types: rational arbitrageurs who are sentiment-free and irrational traders prone to exogenous sentiment. Rational arbitrageurs are restricted in different ways from risk trading and short selling while irrational traders determine prices and expect returns. We can say that falling price indicate a bearish market while rise in prices relate to bullish markets. There is no data to statistically prove this significant effect. Since the asset bubble burst in the US, retail investors were the worst affected and media focused on their sentiments saying that they caused the stock prices to move away from its value (Kumar, 2006).

In the context of investor sentiments, it is identified that an economic program may succeed in a country but fail in another country however, it has similar economic fundamentals. Economic agents can invest in a mutually beneficial project in an environment but do not prefer to invest in another environment with same economic fundamentals. In this context, economists have argued that difference in outcomes take place due to difference in investor sentiments. (Deeney, 2015) stated that good outcomes are a result of positive outlooks coordination on a good equilibrium. However bad outcomes are due to the agents with negative outlooks coordination on a bad equilibrium. In the views of (Spyrou, 2013) small amounts of information or incomplete information about fundamentals inversely impacts the decision and shows a negative investment decision. Likewise, investors’ sentiments play major role for taking effective decisions.

From correlation and regression, it is evaluated that long-term historical phenomena in securities market need efficient market hypothesis which cannot be captured only on the basis of rational parameter. (Demirer, R, Kutan, A. M, Zhang, H., 2014) determined that behavioral finance attempts to fill the gap by offering psychology-based theories which explain the market anomalies. However, on the contrary, (Galariotis, E. C., Makrichoriti, P., & Spyrou, S, 2016) depicted that focusing towards investor sentiment is the tendency of focusing towards noise and emotions rather than facts. Sentiment can be said to be the strong intuition of the investors regarding the beliefs about the future cash flows where investment risks are not justified. In the views of (Chan-Lau, J. A., Liu, E. X., & Schmittmann, J. M. , 2015) taking the decisions of investment only on the behalf of investor sentiment can create a risky situation for the investor. So, there is a need of focusing towards stock market while giving concern towards sentiments as well as figures, facts, past status.

(Chiarella, C., ter Ellen, S., He, X. Z., & Wu, E, 2015) determined that investor sentiment index based is on the six measures, i.e. number of IPOs, first-day returns on IPOs, equity share in new issues, closed-end fund discount, trading volume as measured by New York Stock Exchange turnover and dividend premium. There is basically a high and low sentiment indicator which enables to compare the number of stocks. Trading stock prices at their low across the board, indicates the traders towards bearish market. On the contrary high trades reflects traders with a bullish market sentiment. Consumer Confidence Index uses features of financial market not included in macroeconomic indicators (Zouaoui, 2011).

It is identified that intense level of change in stock prices reflects the standard finance model which indicate towards unresponsive investors who always enforce capital market prices on the basis of the present value while focusing towards the expected future cash flows. However, in the context of behavioral finance, investors focus on working towards augmenting standard model based on two assumptions (Kleinnijenhuis, J., Schultz, F., & Oegema, D, 2015). The first assumption is based on the concept of investors’ sentiment which can be defined as a belief about future cash flows and investment risks and it is not justified through the facts. However, the second assumption emphasizes towards betting against sentimental investors regarding cost and risk (Kleinnijenhuis, J., Schultz, F., & Oegema, D, 2015).

There is no proper method which can be evaluated to measure investor sentiment. There are several proxies that researchers utilize to capture sentiment, but there is no unison as to which will be the best proxy (Baker, M. and Wurgler, J, 2007).  Market based surveys and survey indices can be a way of measuring the proxies. Close end fund discount is one measure of market based sentiment. IPOs also quantify as measurement of sentiment through corporate decision making. Also, using sentiment based index by Malcom Baker and Wurgler (Baker, M. and Wurgler, J, 2007) on financial proxies, we can examine that not necessarily these proxies may capture the sentiment in the right context. Michigan Consumer Confidence Index was used as a proxy for investor sentiment study by (Portniaguina, 2002). Use of this index is very rational as no one research uses the same method to evaluate investor sentiment. Since relationship between stock market and investor sentiments is complex, use of Consume Confidence Index uses surveys which are similar across most countries making comparison and analysis of data for different countries possible (Welch, 1988).

2.4 Evaluating the Ways to use sentiment data by the investors in the market especially during important events

The research study conducted by (Mclean, r.d. and zhao, m, 2014) determine that tracking sentiment is best way to use sentiment data in the effective way. It is an accurate way to evaluate the direction of the market. On the other hand, (Arif, 2014) conclude that the best way of using the sentiment data is to follow the principle of the financial market. It helps investors to understand the nature of the stock and market. It is important to gain high profit in the stock market activities. Economists tend to distance themselves from traditional financial theory during stock market crisis (Zouaoui, 2011). (Shiller, 2000) surveyed investors and the study revealed that many investors infer the stock market crash as an outcome of other investors psychology than financial variables.

According to (Peng, et al, 2015), the best method of using the sentiment data depends on collection of data. It does not matter what kinds of stock are purchased. In order to access the good and effective data, investors should be concerned on with the utilization of best resources available.  In addition to this, (Kim and Kim, 2014) suggest that investors should analyze the data for important insights. The data of financial market and views of investors should match with the stock market. Likewise, it has also been found in the research strategy of (Deeney, 2015) that put to call ratio is an effective way to use the information of the investor sentiment. The puts to call ratio is a kind of option contract between the seller and buyer at a preset price. It is helpful to predict the market price of the security. On the other hand, (Bathia, D & Bredin, D, 2013) believe in the survey result of the American association of individual investor’s sentiment. The member of AAII, every week estimate the price of the stock which predicts whether it will increase or decrease in the future.

2.5 Summary

This literature review critically analyzes various previous literatures on the relationship between investor sentiments and stock returns. From this, it can be summarized that there is a significant role of investor sentiment in different economic issues such as bank crisis, poverty traps and currency crisis. It also plays an important role to make an investment decision. Based on the literature we can also infer that investor sentiment is also significant to save profits of the investors in the financial market but, at the same time, it has also been found that incomplete information and illusion can affect investment made by investors.     

CHAPTER 3: RESEARCH METHODOLOGY

3.1 Introduction

This chapter will consist of a brief overview of the research process identifying the research strategy, research philosophy, the design and the approach.

3.2 Research Philosophy

In the words of (Taylor, 2015) in the research methodology, the research philosophy represents the thought of the researcher regarding the research problem. It guides a researcher to conduct a good research (Blumberg, 2008). Typically, there are three kinds of research philosophy -positivism, realism and interpretivism. We specifically for the purpose of this research use the positivism philosophy to collect the data quantitatively. On the other hand, interpretivism philosophy is used by researchers to analyse the research issues while developing an in-depth knowledge & understanding of the research topic while adopting an empathetic view. At the same time, realism philosophy concerns with the reality presented in the environment amidst the people.

In the context of this particular study, the paper uses positivism style as data is undertaken in a structured manner and not influenced by views. As put by Saunders, quantitative data with large samples using statistical testing is a major facet of positivism (Saunders, 2009). The literature review undertaken supports this positivism approach to test investor sentiments and stock markets (Baker, M. & Stein, J, 2004).

3.3 Quantitative Research Approach

This research paper adopted quantitaive method since the objective of this study was to analyze and evaluate sentiment data and stock returns. As mentioned by (Creswell, 2009) a quantitaitve technique analyses and tests objectives by exploring the relationship between variables.

The research used the inductive research approach to accomplish the research aim (Saunders, 2009) At the same time, inductive research approach is more suitable with interepretivism philosophy. It provides the flexibility to the researcher to collect the data and information for a research study. Additionally, the nature of this research study is based on theoretical aspect developed after analysis and data collection (Khan, 2014). Since, Stock markets and Consumer sentiment data can be best determined through a large sample, using quantitative approach would be the best method for this study.

3.4 Data Collection

This research is based on secondary data. For the collection of secondary data, relevance and reference to various literatures were used to identify the investor sentiments. Data for various variables was sourced from Trinity College Library Database, Bloomberg, DataStream Reuters, Google Scholar, ISEQ (Irish Stock Exchange), ESRI (Economic and Social Research Institute), Consumer Confidence Index, S&P 500, Michigan Consumer Sentiment Index. All of these sources are accurate and frequently used. Monthly data from 2008-2017 was used for this research. Additionally, this study gives consideration in including the relevant sources towards increasing the reliability of the research outcome and literature (Johnston, 2017). Stock return and sentiment relationship is evaluated by using Consumer Sentiment index and ISEQ, the relevant index data is provided in Appendix C. Consumer Confidence Index is the most preferred sentiment indicator used by various researches (Welch, 1988) and hence formed the base to use this index for this research. It also acts as a market index in the context of comparative study. Use of this index is easy as data is available for all major countries of the world.  There are number of studies conducted by the researchers to evaluate the investor sentiments in different countries however Ireland is an exception. The Sentiment indicator for Ireland was sourced from ESRI and KBC Ireland Investor Sentiment Survey Index. ESRI and KBC Ireland conduct monthly surveys in Ireland and aim to analyze a pattern of consumer and investor sentiment and identify trends in the economy. These surveys focus on current economic conditions and investor expectations.

3.5 Sampling Method

In the research methodology, the sampling method refers to select a part of the population to answer the research question. In this, the selection of the sample size can be based on the demographics, behavioral and psychological aspects. There is two type of sampling methods including probability sampling and non-probability sampling. In this, probability sampling method provides an equal chance to each participant in the research. On the other hand, the non-probability sampling is where samples selected are from the total population and each participant may be unable to answer research objectives. (Taylor, 2015).

As the research aims to identify the relationship between the investor sentiment and stock market, this research used non-probability sampling to gather information from a sample of the total population based on Index data. Data obtained was monthly data ranging from Q1 2008 to Q1 2017 from the ISEQ and Consumer Sentiment Index obtained from ESRI.

3.6 Data Analysis Technique

Data analysis technique allows a researcher to analyse the collected data and information. It is an important technique that represents the research outcomes effectively. In this, researcher chooses an appropriate technique to analyse data. For this, a researcher can use content analysis, statistical analysis, factor analysis, and cluster analysis, etc. But, the decision of the selection of the data analysis tool depends on the nature of the collected data (Silverman, 2016).

With regards to this research study, use of statistical analysis technique with the help of the MS Excel, SPSS software, and Eviews was used to analyze the findings of the correlation and regression. The use of SPSS software allows the researcher to represent the final output in a tabulation and graphical format. Data collected from ISEQ and ESRI would be coded onto SPSS and analyzed. Reliability test would be conducted to determine Cronbach Alpha which should range between 0.70 and 1.0 (Saunders, 2009). It will be helpful to any researches, participants and readers to understand the data (Smith, 2015). This test would satisfy the first objective. Regression analysis using ANOVA and Correlation analysis using Pearson’s Co-efficient will be used to understand the statistical significance range which should be below 0.05. We expect to have a positive correlation between sentiments and stock market data.

3.7 Reliability Test

The extent of the reliability and validity of the collected data is important to achieve the research objectives effectively. In order to identify the reliability and validity of the collected data, the researcher conducted the reliability test with the help of SPSS. It is vital to identity the consistency of the responses of the participants. This test represents Cronbach’s Alpha coefficient that shows the reliability of research. In this, the positive value of the Cronbach’s Alpha coefficient depicts that response of the participants are accepted and reliable. On the other hand, negative value of the Cronbach’s Alpha indicates that responses of the participants are unacceptable. Cronbach Alpha test uses scale items which are not correlated. Using quarterly data from 2011-2017 as the scale items for this research, getting a co-efficient within the normal range is important as co-efficient of different variables can increase by increasing the number of scale items (here considering increasing the quarterly data). A high correlated variable which exceeds the maximum range of 0.70 is redundant (Bennet.E, 2013).

3.8 Ethic Consideration

This study aims at understanding the investor sentiments in financial markets in Ireland. (Schuklenk, 2005) states that “Ethics aims to achieve two fundamental objectives: to tell us how we ought to act in a given situation, and to provide us with strong reasons for doing so.” In each research, it is possible that researcher can face an ethical issue. These types of issues can be minimised by giving proper references and citation of the original writers. This research adhered to the ethics guidelines states by Trinity College Dublin and followed accordingly. Since data used was quantitative, usage of appropriate data was given due importance. Also, permission was obtained from ESRI to use Consumer Sentiment Index data in this research paper.

Since ESRI uses survey based method to obtain this data, care has been taken to ensure that the data was not shared with anyone else without approval from ESRI. It is effective to enhance the reliability and validity of the research outcomes  (Flick, 2015).

3.9 Summary

 On the basis of above discussion, it can be summarised that the selection of the suitable and appropriate research approach, philosophy, strategy, data collection method, sampling technique and data analysis techniques are effective for the researcher to collect the required data for research. It allows a researcher to collect data and information with minimal difficulties. Similarly, the use of both data collection methods reduces the gap between the required data and available data in the research. Furthermore, it can also be said the use of the non-probability sampling method reduce biasness in the research and improve the research effectiveness.

CHAPTER 4: DATA ANALYSIS AND DISCUSSION

4.1 Introduction

This chapter outlines the findings and analysis of quantitative research approach mentioned in the previous chapter while keeping in mind the research objective. The results obtained from SPSS using Cronbach Alpha test and Correlation will be discussed further in this chapter.

4.2 Volatility Indicators

Ireland’s volatility peaked during the financial crisis 2008. From the below chart, we can observe that during the crisis, volatility was at its highest (0.97) until the end of 2008 as Ireland was affected by the global recession which had absorbed the entire global economy. It was at its lowest in 2015 until it rose considerably from 2016 with issues such as currency fluctuations and majorly the impact of Brexit on Ireland as ISEQ suffered a 17% decline. It’s still impossible to predict the outcome and the effects of Brexit on Ireland but Irish economy still proves it can overcome such crisis as it has been one of the fastest growing economy in Europe (Wexboy, 2016).

Fig 2: Volatility of ISEQ                                                          Source: WordPress.com

4.3 Cronbach Alpha Test of Reliability

Table 1 and Table 2 outline the reliability test for Consumer Sentiment Index and ISEQ as a measure of scale reliability. A Cronbach Alpha of 0.679 has been derived.  A reliability test ≥ 0.70 indicates good reliability. Classical theory suggests that 70% of the reliability test s ‘accurate’ while 30% is just ‘noise’. 11 variables were considered for the testing from the consumer sentiment data procured from ESRI as they conduct monthly surveys to gauge consumer sentiment to understand if the data lies under a similar construct. As the reliability test varies with different variables used and the types of constructs measured, a Cronbach Alpha of 0.679 is acceptable but may need to create more constructs and variables for future testing  (Field, 2009).

Case Processing Summary
		N	%
Cases	Valid	100	100.0
	Excludeda	0	0
	Total	100	100.0
a. List wise deletion based on all variables in the   procedure.

Table 1: Case processing summary for Reliability Test

Reliability Statistics
Cronbach’s Alpha	N of Items
.679	11

                                                   Table 2: Cronbach Alpha Test

4.4 Descriptive Analysis

Descriptive statistics of Irish Stock exchange and Consumer Sentiment Index in Table 3 & Table 4 give us standard deviation of 20.24 and 18 indicating a larger spread of index data. It has been considered that the data used involves massive fluctuations and volatility as it covers periods of recessions, Brexit and financial crisis. Judging by the mean and standard deviation from 2008-2017, we estimate average return in ISEQ to be less comparative than Consumer sentiment. The investor sentiment is               more volatile during the financial crisis between 2008 and 2017. Data limitations impose different mean statistics for the indexes. Descriptive analysis of the data showed considerable difference between the means obtained between the sentiment and stock exchange indexes, indicating data is dispersed somewhat different than the mean.

4.5 Test of Normality

Saunders (2009) infers that testing normality for a given data set implies if the data is evenly distributed. Table 6 gives a brief overview of the Shapiro-Wilk test for normality. The statistical significance value should be greater than 0.05 indicating normal distribution of data. Testing our objective if there exists a relationship between stock markets and investor sentiment, p value is 0.698 for consumer sentiment index which can be assumed that data is normally distributed and test of normality with a p value above 0.05 follows null hypothesis distribution which is above rejection threshold and so we can reject the null hypothesis.

Figure 3 represent a histogram for sentiment data and ISEQ. It can be inferred that the curve represents a bell-shaped curve with distribution frequency higher to the left. This shows that the data has normal distribution and agrees with the test of normality.

Figure 3: Relationship between sentiment and stock exchange

4.6 Correlation Analysis

We test our data for correlation to identify if the data displays close to normal probability. -1 probability indicates a perfect negative correlation and +1 indicates a perfect positive correlation. Table 8 and Table 9 represent correlation between the index data and consumer sentiment. Pearson’s Coefficient (r) for Michigan Consumer index and S&P 500 is 0.889 which is almost close to 1 while significance value (p) is 0.003 which is less than or equal to 0.05. Hence, there is significant correlation between consumer sentiments and the stock market as p<0.05. Pearson’s coefficient (r) for Iseq and Consumer sentiment is 0.817 while significance value (p) is 0.002. p<0.05 This concludes that there is significant relationship between ISEQ and Consumer sentiments which means any slight increase or decrease in 1 variable may result in increase and decrease of the other variable.

4.7 Time Series Analysis

Since our data is of time series, we will try to analyze time series data with help of stationarity using Augmented Dickey Fuller (ADF) test based on intercept assumption.

4.8 Test for Stationarity (ADF)

ADF test was performed on all the variables to test for stationarity. Hypothesis of ADF states that

Ho: ‘Given process has unit roots ‘

H1: ‘Given process has no unit roots’

Table 6 shows the unit tool outcome for the variables. Sentiment data are stationary at the same level. Similarly, stock exchange markets are stationary at the same level. This means that the data is stationary at same levels for all variables. Since the test statistic (t stat) from tables 10-13 refer appendix
is lower than all the critical values, we can reject Ho, null hypothesis at significance level less than 1%. We can thus conclude that there is very low probability of errors in time series with no unit root.

ADF Test Result
Variables	Intercept
CSI	-0.44986
ISEQ	-1.02297
MCI	-1.534045
S&P500	0.679892

Table 6: ADF test

4.9 Wald Test

Wald test is known to identify if coefficient from a regression model is pointedly different from zero.  We test this to understand the significant between investor sentiments and important events. Table 14 shows probability of .000 with f-statistic of 216.9. Probability of 0.00 indicates that our correlation is linked in the long run. Hence, we can say we reject null hypothesis of all variables.

Figure 4: Performance of Consumer Sentiment Index

Figure 5: Performance of ISEQ

Figure 4 shows that in January 2008, the investor sentiment was standing at the 67.01 In the last nine years, there has been significant growth rate with index now standing at 100.70 in January 2017. Comparing this with ISEQ, we determine a similar pattern of growth with a high index rate of 6664.48 in January 2008 and a slight decline in January 2017 where the index closed at 6546.57. From the above graphs, it’s evident how Irish stock markets were at an all-time low during the period 2008-2009, the year when recession affected all economies. When markets went down, investor sentiment too were at a decline which proves our test for correlation between sentiments and stock markets. A 1% increase in one variable cause a significant and similar change in another. These graphs also show that Irish economy has recovered massively since then and is constantly increasing but at a slow pace.

Figure 6: Performance of Michigan Consumer Index

Figure 7: Performance of S&P 500

 

 

When determining the stock return pattern for S&P 500 and Michigan Consumer Index, we determine that both declined sharply during 2008 with S&P closing at 1378.55 in January 2008 and currently closed at 2363.64. MCI was 78.4 on January 2008 and closed at 96.3 in 2017. A sharp decline of 55.8 for MCI was observed in 2011 majorly due to debt crisis affecting the US markets. This weakening reflected investor’s pessimism over growing debt crisis and future of the economy. In comparison S&P 500 fell to a minimal low of 1218.89 during the same period but since then has risen significantly.

CHAPTER 5: DISCUSSION OF THE FINDINGS

5.1 Introduction

This section we will discuss the results obtained from the tests conducted and link it with the relevant literature discussed to identify any flaws or resemblances. Since few research has been done in context to Ireland, this paper tries to identify plausible causes which has an impact on investors and their relationship with the stock market. Implications of the study will be discussed as well.

5.2 To understand if there exists a relationship between consumer sentiments and stock market.

Sentiments and economic conditions are correlated as seen in Table 6 which indicates that there exists a positive linear relationship between as sentiments and views of investors can fluctuate according to the global and economic conditions as identified by (Ahmed, 2013) . Reliability test using Cronbach Alpha was used to identify if the variables used from the research were consistent and viable for testing. Reliability test of 0.679 was obtained from the sentiment data and index as variables were identified from the research survey conducted by ESRI on a monthly basis. 110 data points were inputted using SPSS to derive the reliability of the data which gave a positive outcome. Increasing variables to create new constructs increases the measurement and stability of data for a time series (Field, 2009). Reliability tests is very important as it can fulfill the requirement of the data so desired and helps a researcher in understanding if the variables correlate with the hypothesis and can be a source of future research study when reconducted (Wexboy, 2016). It is found that economic issues can affect globally or nationally in different manner such as bank crisis, poverty traps and currency attack. This interpretation can be supportive by the literature review finding of (Danbolt, J., Siganos, A., & Vagenas-Nanos, E, 2015) who said that the increase in the price points in a bullish market sentiment affect the way how investors trade and tend to see the stock market.

Normality tests as per (Saunders, 2009) was tested to check if the data sourced was evenly distributed. P value greater than 0.05 indicates that elements of the correlated data are normally distributed. P value so derived for consumer sentiment and the stock market was 0.698 which proves the test that data is correlated and there does exist a relationship between sentiment and stock markets. Stock market volatility is another factor which proves our research analysis that volatility in the market does play a significant role in investor sentiment as investors are wary to invest in a market which is not stable and any volatile fluctuations and movements impacts the trading cycle resulting in huge oscillations in the share prices which impacts sentiments in the long run (Portniaguina, Lee., 2002) Sentiment indicators used were Michigan Consumer Sentiment Index and Consumer Sentiment Index of ESRI as both conduct almost similar style of surveys to gage consumer patterns and sentiments which predict how consumers react to stock market volatility. To correlate sentiment data with stock markets, Irish Stock Exchange Index (ISEQ) and S&P 500 were sourced from Bloomberg and DataStream as a base for this research.

Based on the analysis of the correlation and regression, it is found that there is significant relationship between investor sentiments and stock returns. It is because of these findings; the investor sentiment is beneficial for dealing with the various economic issues. As discussed by (Chan-Lau, J. A., Liu, E. X., & Schmittmann, J. M. , 2015) decisions made only on the basis of investor sentiment poses a risk on the research as well as risk to the behavior of the investor as he is dependent only on sentiment indexes. For this reason, it’s important to correlate with stock market index to study past facts and figures which can create new assumptions as investors rely on past figures more than current information. Correlations between Stock exchange index and Consumer sentiment was tested by Pearson’s Co-efficient test of Correlation. Correlation obtained was 0.889 which is close to 1 which indicates a perfect positive correlation between sentiment and stock with p value 0.03 which is less than 0.05. Since this research conducted only a longitudinal analysis pertaining to a single country (Ireland), observations derived will be more tentative as ISEQ index data will have much high average returns as compared to Consumer Sentiment index. The investor sentiment helps potential people to make the decision regarding the investment in the stock market. The above interpretation is also supported by the views of (Bathia, D., & Bredin, D., 2013), as it was depicted in their research that investor sentiment provides several information to investors that helps them to narrow down on an investment decision. Also, investor sentiment plays a huge role in understanding the impact of the inflation. These sentiments help investors and the financial market analysts to recommend the best time to invest in the securities. This interpretation is also supported by the views of (Bathia, D., & Bredin, D., 2013) as it was discussed in their research that financial market investor sentiment is helpful for the investors to understand the impact on the market. It shows the views and opinions of the various economic crisis on the financial market. Likewise, from all the tests conducted we can say there exists a relationship between stock market and investor sentiments a sentiments play sentiment data follows financial markets principles (Arif, 2014).

5.3 To examine if there exists a relationship between sentiments and important events.

Investor sentiment is effective to provide significant information on the stock market. It makes aware investors to know the essential factors that can influence their investments. Therefore, investor can save their money by understating the nature of the stock market. This supports views of (Demirer, R, Kutan, A. M, Zhang, H., 2014) that by the help of the investor sentiment, an investor can protect its profits Sentiments convey various significant factors that can affect the investment.

Ireland has suffered massively since 2008 recession as it was hit by asset bubble, banking scandals, Celtic Tiger years and most recent currency fluctuation crisis and possible Brexit. This research sourced data from 2008-2017 to identify a pattern in the stock market index as the year 2008 was the onset of recession for the entire world. All events were sourced using secondary data found from the Irish Stock Exchange while comparing it with S&P 500 which recovered tremendously since the recession. (Black, 1986) in his research paper terms investor sentiment as the potential noise in financial markets. Since our data consisted of time-series ranging from the year 2008-2017, we tested for stationarity using the Augmented Dickey Fuller (ADF) test to analyze the stationarity of data during such crucial events affecting Ireland.

The test used each of the variables to identify stationarity using the assumption of an intercept as per ADF. Stock exchange index and Consumer sentiment index were stationary at the same level for the selected variables. The ADF test statistic reached -1.03 for stock price data while test statistic reached -1.534 for consumer sentiment index. Thus, we can conclude saying, we reject null hypothesis (Ho) on test critical values at 99% significance level (Gao, 2008)

Since volatility affects how portfolios range in the financial markets, it is an important indicator to be studied.  Irish stock exchange fell to an all-time low to 1987 points during 2009, which is termed as a shocking 14-year low. Central statistics office (CSO) revealed that Ireland was the first to enter recession in the Eurozone. Unemployment and migration were on a rise as with numbers increasing to 326,000. Banks were the first form of rescue to all investors as the then government declared 2-year unlimited guarantee of the debts. There was huge turmoil throughout the country and IBRC came to the rescue in form of a bail out, resulting in signs of recovery since then for Ireland. Using Consumer Confidence Index sourced from ESRI for analysis is beneficial as it uses data from financial market not included in other economic indicators (Zouaoui, 2011).

The stationarity test result is supportive of the fact that there exists a relationship between financial crisis in the market and sentiments as investors reaction is based on illusion and behavioral finance as they relate stock market crash to be a behavioral issue as it’s a result of other investors perception and psychology (Shiller, 2000). Consumer index is a base to conduct such research as per (Portniaguina, 2002).   Wald test was derived to determine if the variables were significant or not (Ahmed, 2013). Probability of .000 indicates coefficients are related. At the same time, it is also found behavioral finance is important to fulfil the gap between the required information and available information best investment decision. The above interpretation is supported by the views of (Demirer, R, Kutan, A. M, Zhang, H., 2014) as it was induced in their study that behavioral finance undertakes the gap by offering psychology-based theories which enlighten the market anomalies. It also defines that behavioral finance comes under the field of finance that is important to assume the increase and decrease in the stock price. In order to make an investment decision, the investors should also be concerned about the role of the government, interest rate and inflation rate rather than depending only on sentiment data and illusions.

5.4 Summary

From the data analysis, it is found that there is a significant relationship between the stock market and investor sentiment. Sentiment help investors to face financial issues effectively. It also helps the researcher to analyze and evaluate the stock market and make appropriate investment decision. It makes aware investors know the essential factors that can influence the investments. Besides, it is also found that incomplete and insufficient information of investor sentiment affects the decision of investors. The first objective for this research was justified appropriately as per the researcher’s knowledge. Literature review and testing of models which proved that investor sentiment and stock markets have correlation.  A slight increase in one index, can lead to a significant impact on another. Second objective was acceptable as per ADF and Wald test which says there exists a relationship between important crisis and sentiment, though it needs more scope of improvement.

 

CHAPTER 6: CONCLUSION AND RECOMMENDATION

6.1 Conclusion

This chapter concludes the research study undertaken to study the importance of investor sentiments and stock returns for Ireland.

Considering all the sources and data inferred we can say that sentiments are an important source of research and indicator for stock market analysis. With the help of investor sentiment, investors can interpret an economic issue in the form of the bank runs, development traps and currency attack. Investor sentiment is an important aspect for Ireland as sentiments motivates financial markets as they are always in a bullish mood. Markets are risk specific and it is important to correlate their movements. Political and economic factors do have an impact on the mindset of investors. It can be stated that the research objective is achieved by the researcher at modest extent through broad review of literature. In the stock market, investors use fundamental analysis that enhances the knowledge change in the price of equity on the stock market. In this, it can be concluded that the best way of using the sentiment data is to start with good data (Peng, et al, 2015). Research should not depend on purchase of stocks or how the investor is gaging at his portfolio. Consumer Sentiment index has been a useful indicator to gage sentiment data for Ireland. As said by (Kim and Kim, 2014), important events make a huge impact on sentiments and using data from the best sources available make for an effective research. Ireland has a positive outlook towards their investments in the financial markets which proves their positive sentiment result.  Consumer inflation index do have an impact on stock market as its range didn’t correlate with the sentiment data resulting in a negative impact on the market. This research believes that conducting an advanced research on economies surviving recession should be undertaken which would benefit another expert. Also, more research can be conducted for Ireland as Irish markets are less discussed and studied as compared to US.

6.2 Limitations and Future Researches

Limitation for this research was of time constraints and datasets. At the same time, some limitation can be seen in the selected sample size.  An increase in the sample data would have yielded a much better result which would improve the study. Restricting the base country to Ireland, there was lack of proper information and literature for investor sentiment. So, most of the data and information was relied upon Economic and Social Research Institute (ESRI) reports. Also, consumer sentiment index was sourced from ESRI and KBC Bank as ISEQ does not have a separate index.  There is scope and opportunities for the future researcher to conduct the correlation and regression with increasing the sample size. Additionally, future researcher can use other research methods, approaches and strategy which were used by other authors in their literature review that will helps to similar and enhanced results but in a different manner. Also, this research felt it could have improved its understanding on the topic by conducting survey which would give primary information about their perception and how they invest in financial markets as surveys can be another method to test proxies (Baker, M. and Wurgler, J, 2007).