Investment involves the commitment of resources

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1.0 Introduction

Investment involves the commitment of resources with the expectation of future rewards (Allsopp, 2002). Individuals have to choose from a vast number of investment opportunities that maybe available at a given time. This will mean that they have to evaluate the different investments by looking at the different factors that may affect their returns and choose which ones are the best to invest in. This according to Mathews (2005) is what decision making is all about. Mathews (2005) defines decision making as the process of choosing alternatives from different alternatives. A decision maker has to carefully evaluate the different alternatives and choose the best among all the alternatives.

The process of choosing the best investment out of all the alternatives is the investment decision. As different individuals decide on which companies to invest in, they need to be aware of all the factors that exist in the business environment that might affect the value of their investments. Factors that may influence the investment decision include the risk involved with investing in a particular asset, the returns expected, economic situation at time of invested and the amount available for investment among other factors (Johnssonm et al 2002).

According to the investors' journal, an investor is someone who looks at the fundamentals of a company, considers outside market variables,and sees potential for good returns on his investment. An investor is distinguished from a speculator, who seeks to make quick, large gains from price increases on risky assets. Generally, an investor has a longer time horizon for achieving a return.

To be able to understand the investment process in an organized manner an analysis of the basic nature of investment decisions, division of activities in the decision process and the major factors in the investors' operating environment that affects their investment decision requires a thorough analysis (Jones, 1985). The basic nature of all investment decisions is the trade - off between expected risk and return. Jones (1985) continues to explain that this trade off always slopes upwards because an investor expects high returns if he assumes high levels of risk.

Johnsson et al (2002) observed that instead of high returns, investors have had to settle for ordinary returns and often experience little peace of mind due to increased volatility of these returns. This has caused economists such as D. Kahneman and A. Tversky, to investigate why there is increased volatility of returns and why there is a gap between expected and actual returns. As they continued with their examination process, they identified that one of the reasons why this gap exists is due to presence of fundamental mistakes made by investors while trading in the markets. In other words, they found out that investors are irrational in their decision making especially due to psychology factors such as fear, greed, and other emotional responses to price fluctuations and dramatic changes in an investor's wealth. These psychological factors impact on investments and volatility of return on these investments.

As investors and potential investors consider different types of investments they must ensure that they are well aware of all the different variables that may affect their returns or increase the volatility of those returns. Investors and financial advisors often look at the performance of potential investments through the published financial statements, through their performance in the financial markets, liquidity of the investment among other financial related variables. However, most often than not the psychological aspect of the market participants is often ignored. Every investor differs from the other psychologically due to various factors such as demographic factors, socio-economic background, age, sex, level of education and race. These factors may cause behavioral biases among investors which may distort the performance of a security in the financial market (Bernéus et al, 2008).

1.2 Background Information

The traditional finance paradigm, seeks to understand financial markets using models in which agents are “rational”. Rationality means two things. First, when they receive new information, agents update their beliefs correctly, in the manner described by Bayes' law. Second, given their beliefs, agents make choices that are normatively acceptable. This traditional framework is appealingly simple, and it would be very satisfying if its predictions were confirmed in the data. Unfortunately, after years of effort, it has become clear that basic facts about the aggregate stock market, the cross-section of average returns and individual trading behavior are not easily understood in this framework (Barberis & Thaler, 2002).

Researchers such as Kahneman and Tversky (1979), Poteshman and Serbin (2002) and Stein (1989) uncovered a surprisingly large amount of evidence that as individuals make decisions about investments, they do not act rationally even when all information is available. A good example of irrationality would be an investor holding on to his stocks when it would be wealth-enhancing to sell them Poteshman and Serbin (2002). Poteshman (2001) further shows evidence of investors not properly reacting to volatility information in the securities market amounting to irrationality of investors in security markets. Finally, Bakshi et al. (2000) provide evidence that agents often trade in a manner that causes option prices to move in a manner inconsistent with comparative statics obtained from traditional assumptions of rationality. Many examples of irrational behavior and repeated errors in judgment have also been documented in academic studies, the most influential of them being Kahneman and Tversky's (1979) papers on judgmental heuristics and biases and on prospect theory a framework for choice under uncertainty.

Behavioral finance is a new approach to financial markets that attempts to explain the difficulties faced by the traditional finance theory. In broad terms, it argues that some financial phenomena can be better understood using models in which some agents are not fully rational. More specifically, it analyzes what happens when we relax one, or both, of the two tenets that underlie individual rationality. The collapse of the U.S housing market that left the whole world's economy at a bad state has caused many economists to examine why it happened. Jickling (2009) asserts that, factors such as failure of risk management systems, lack of transparency and accountability in mortgage finance caused investors to be unable to make independent judgments on the merits of investments. However a financial analyst called Andrew Lo looked at human frailty as a cause of the economic crisis.

Lo (2008) agrees to the fact that the 2008-2009 economic crises was triggered by the collapse of the U.S. housing market, but he also believes that it had been made worse by the human element. He argues that the crisis was about more than economic forces. In his mind the human element at play had a lot of emotions of greed and fear of the unknown. In other words, investors became greedy, and, as Lo put it, this greed was spurred on by the profit motive, the intoxicating and anesthetic effects of success. And then the greed turned to fear as everything began to collapse. Fear froze the markets, leading to liquidity runs on financial institutions, even those who were not facing insolvency. This shows that even in recent times psychology of the humans plays a major role in the financial markets. This is a clear indication that the “human element”, played a big role in the crisis. This is what is referred to as behavioral finance where the psychology aspects of human beings tend to make them irrational while making decisions about investments.

The field of Behavioral Finance emerged in the 1980's as a critique of Fama's Efficient Market Hypothesis, (EMH) that concentrated on the rationality of the markets. The theories within Behavioral Finance took a different approach when explaining market movements. They looked at the human aspect within the financial markets. After all, the market is determined by people, and people can not always be considered rational in all their investment decisions, especially not during times of financial distress (Shefrin, 2000).

In essence, Behavioral Finance attempts to explain and increase understanding of the reasoning patterns of market participants, including the emotional processes involved and the degree to which they influence the decision-making process (Ricciardi & Simon, 2002). Lintner (1998 pp 7-8) defines behavioral finance as being “the study of how humans interpret and act on information to make informed investment decisions”.

Olsen (1998, pp 10) asserts that ‘behavioral finance does not try to define ‘rational' behavior or label decision making as biased or faulty; it seeks to understand and predict systematic financial market implications of psychological decision processes.”

Sewell, (2001) describes Behavioral finance as the study of the influence of psychology on the behavior of financial practitioners and the subsequent effect on markets.

According to Glaser et al, (2003) Behavioral finance mostly examines agents' rationality. It attempts to explain how investors' human behavior is affected by cognitive illusions. These are grouped into two main concepts: heuristics and prospect theory.

Tversky and Kahneman (1974) introduced the idea of heuristics. This idea means that people tend to use rules of thumb when making a decision due to their lack of ability to process information fully rationally especially when they are faced by time pressures. Under heuristics other factors such as representativeness, over confidence, anchoring, gamblers fallacy and availability bias all affect the rationality of investors. Prospect theory on the other hand deals more with regret and loss aversion. These concepts shall be discussed in detail in chapter two

Behavioral finance does not disregard the other modern financial theories such as EMH and CAPM but rather helps explain and understand the highly irrational behavioral patterns of the investor who dictate the market. A co existence should therefore be established between the different theories to help financial analysts and investors understand the markets better. This study will seek to find out whether Behavior of the investors does affect the investors decision making and the markets (Bernéus et al, 2008).

The will study will concentrate on MBA students at Daystar and will examine whether behavioral biases affect the investment decisions of the MBA students at Daystar University. Most MBA students at the University that the researcher has interacted with have a form of income from employment and self employment. Thus it is possible that most of them are involved in some kind of investment or another. Earlier research studies have mostly concentrated on professional and institutional investors and thus this study will concentrate on students to determine whether what they are taught in class especially on efficient markets is reflected in their investment decisions.

1.3 Problem Statement

Recent economic crises such as the internet hysteria in the 1990's and the housing market crash in the U.S has raised many questions such as why the so called “rational investors” were also affected by such crises. This shows that something is fundamentally wrong with the current models of rational market behavior (Johnsson et al, 2002). Swedish author C-G Gyllenram (1998) also disputes the concept of the rational investor inherent in the classical economic theories. He argues that human being beings are not always rational and that they tend not to, learn from all their mistakes and are greatly influenced by what other people think. Humans are also affected by emotions and when making their investment decisions they tend to rely more on their emotions than on logical thinking. Even though logical thinking can be one factor underlying a selling or buying decision, other factors such as group mentality and previous losses or gains can contribute as well. The individual's current mental state might at times be a larger factor than anything else when it comes to decisions regarding investments.

As investors are full of irrationalities and inconsistencies, they tend to be overconfident and use their own skills to make investment decisions. This causes them to venture in very risky investments. When investors use wrong beliefs when trading in security markets they may not be able to survive in the stock markets and they are prone to making huge losses on their investments and thus making their survival in the trading markets rather difficult (Paul, 2007).

Whereas a number of prior research studies on Behavioral finance (Hannes et al, 2008; Johnssonm et al 2002) have concentrated on institutional investors, there is only one study that has concentrated on students: Behavioral Finance (Kamran et al, 2008) No research study, however, has been undertaken examining the role of behavioral finance on Kenyan investors and in particular Kenyan students. This research study will seek to therefore, investigate the role of behavioral finance in investment decisions by MBA students at Daystar University. It will also seek to narrow the existing gap by answering the questions: What causes this irrational behavior among the student investors and do these irrationalities affect investors return? Are students who are aware of such psychological factors affected by the same as they invest? These are some of the questions that will form the framework of this research.

1.4 Purpose of the study

The purpose of this study is to assess whether student investors show tendencies of irrational behavior when exposed to certain psychological dilemmas related to the financial world. It will further establish what these psychological factors are and whether such factors affect their investment decision. The characteristics of students who invest will also be examined.

1.5 Objectives of the study

Specific Objectives

  1. To establish whether there exists a relationship between behavior and the decisions made by student investors.
  2. To establish what are the characteristics of the students that invest in the stock exchange.
  3. To establish whether student investors act irrationally when exposed to psychological dilemmas.
  4. To determine which factors of behavior mostly affect the investment decision

1.6 Research questions

  1. Is there a relationship between behavior and decisions made by student investors?
  2. Do student investors act irrationally when exposed to psychological dilemmas?
  3. What personal characteristics do student investors possess?
  4. What are the significant factors of behavior that affect the investment decision?

1.7 Justification of the study

Little is known about behavioral finance especially In Kenya. Therefore it is important to do this research and enlighten investors, financial advisors and financial analysts on the role of human behavior on performance of investments. When assessing the performance of various investments, investors and financial analysts only look at the “market” and any factors that may influence the market, however they miss out on a very important aspect, “themselves” and how their emotional and psychological factors may affect the same market negatively.

Most studies on behavioral finance deal mostly with individual, professional and institutional investors. No research has been done on Kenyan investors who are students and who may have a better understanding of the markets as they have learnt in class about efficiency of markets and rationality of investors. Daystar MBA students are mostly employed and self employed, thus with their incomes they can invest .the research can therefore concentrate on this population to be able to get an in depth understanding of student investors.

1.8 Significance of the study

This study will benefit the following:

  1. Student investors will acquire new knowledge through this study and be able to understand the financial markets better. If they understand behavioral finance better, they will be able to avoid biases when investing.
  2. Potential investors will also be able to know what to look out for when investing. They will know how to avoid any biases that may cause them to be irrational in their investment decisions.
  3. Financial analysts will also be able to understand the markets better and thus help them give good advice to their clients.
  4. Stock brokers and other investors will be able to make good investment decisions that are free of emotions, herding or any biases. It will help them identify their own mistakes in the markets, understand the reasons for their mistakes and thus enabling them to avoid such mistakes.
  5. This study will also show the human aspect is a very important in the markets and shouldn't be ignored. It will further establish which main aspects of psychology may affect the student investors' way of thinking.
  6. The study will also add more knowledgein the Behavioral Finance field since not much study has been done in this field especially in the subgroup of student investors.

1.9 Scope of the study

Behavioral Finance is a vast field of science with numerous theoretical approaches of varying size and relevance. To be able to cover the study well, the researcher will focus on MBA students at Daystar who show interest towards investing and have knowledge of how financial markets operate.

This population was chosen because there is very little research done on the student investor and because the population of investors in Kenya is too wide spread and the researcher may lack the resources to do research on investors in the whole country to be able to cover it well.

1.10 Limitations

  1. The main challenge of this study is that not much research has been done in the field of behavioral finance especially in Kenya and thus getting information maybe difficult. However the researcher will get reading materials from all over the world through primary collection methods such as questionnaires and secondary sources such as journals and books to ensure the research is thorough.
  2. Another limitation would be withholding of vital information by respondents for fear that their responses may be used to judge them or expose their character the researcher however, will assure them of confidentiality in their responses and that the findings will be for academic purposes only

1.11 Assumptions

  1. It is assumed that the respondents will answer all the questions honestly
  2. It is further assumed that the researcher will be able to identify the different characteristics that the respondents may be unwilling to expose.

1.12 Definition of key terms

Psychology - this is the scientific study of behavior and mental processes, along with how these processes are affected by human being's physical, mental state and external environment (Ricciardi & Simon 2000).

Bias - A tendency or preference towards a particular perspective, ideology or result, especially when the tendency interferes with the ability to be impartial, unprejudiced, or objective.



2.0 Introduction

This chapter reviews and presents the literature related to this research. It will first discuss the standard financial theories which support rationality in investors as they take different investment risks and then followed by behavioral finance that assert irrationality among investors concepts so as to bring out the contradiction between the two financial theories. It will further review and present literature related to the role of behavioral finance in investment decisions and discuss the different aspects of behavioral finance in investment decisions. Literature for this study is drawn from academic papers, dissertations, books and journals and presented so as to give a clear understanding of the role and importance of behavior in investments

2.1 Standard Finance

Current accepted theories in academic finance are referred to as standard or traditional finance. The foundation of standard finance is associated with the modern portfolio theory Markowitz (1952), Capital Asset Pricing Model (CAPM) developed independently by Sharpe (1964), Lintner (1965) and Mossin (1966), and the Efficient Market Hypothesis, (EMH). These theories support that markets are rational and markets are efficient. If markets are efficient and all available information is correctly reflected in asset prices then investors should not expect to achieve in a long term higher returns than the level justified by the amount of systematic risk attached to a particular security.

(Szyszka A. (2007) asserts that even if irrationality becomes common for a relatively large group of investors who act in a correlated manner, and therefore are able to move prices away from fundamental levels, it is assumed that rational investors will quickly notice the mispricing and act appropriately. This is by selling the overpriced asset on one market and buying the same or similar asset on the other cheaper market, they will create additional market forces that will bring asset prices back to equilibrium levels. It is assumed that there are many rational arbitrageurs who act quickly and without any constraints. Behavioral finance is the main critique of EMH and other standard finance theories therefore EMH be discussed in short before the main concepts of behavioral finance are discussed so as to bring out a clear distinction of how the two main theories contradict each other.

2.1.1 Efficient Market Hypothesis (EMH)

EMH theory was developed by Fama (1970). Fama defines “efficient market” as a market where there are large numbers of rational profit maximizers actively competing, with each trying to predict future market values of individual securities, and where important current information is almost freely available to all participants.

The efficient market hypothesis was widely accepted by academic financial economists. They believed that the markets were very efficient in reflecting information about the stocks of a particular company. The accepted view was that when information arises, the news spreads very quickly and is incorporated into the prices of securities without delay. Thus, neither technical analysis, which involves the study of past stock prices in an attempt to predict future prices, nor even fundamental analysis, which is the analysis of financial information such as company earnings, asset values, etc., can help investors select “undervalued” stocks, enabling an investor to achieve returns greater than those that could be obtained by holding a randomly selected portfolio of individual stocks with comparable risk (Malkiel, 1999).

Ross, Westerfield e Jaffe (2004) classify the market efficiency into three categories based on what is meant as "available information"- the weak form, semi-strong form and strong form. Weak form efficiency exists if current security prices fully reflect all the information contained in historical prices and returns. The return is the profit on the security calculated as a percentage of an initial price. It can also be expressed mathematically as:

Pt = Pt-1 + Expected return + Random error t.

It means that the price of today is equal to the last observed price plus the expected return on the stock plus a random component occurring over the interval. If capital markets are weak-form efficient, then investors cannot earn excess profits from trading rules based on historical prices or returns. Therefore, stock returns are not predictable and so-called technical analysis (analyzing patterns in past price movements) is useless (Malkiel, 1999).

Under semi-strong form efficiency, security prices fully reflect all public information. Public information includes not only past prices, but also data reported in a company's financial statements (annual reports, income statements etc.), earnings and dividend announcements, announced merger plans, the financial situation of company's competitors, expectations regarding macroeconomic factors (such as inflation, unemployment), etc. Thus, only traders with access to non-public information, such as some corporate insiders, can earn excess profits. Under weak form efficiency, some public information about fundamentals may not yet be reflected in prices. Thus, a superior analyst can profit from trading on the discovery of, or a better interpretation of, public information. Under semi strong-form efficiency, the market reacts so quickly to the release of new information that there are no profitable trading opportunities based on public information.

Finally, under strong-form efficiency the current price fully incorporates all existing information, both public and private (sometimes called inside information). The main difference between the semi-strong and strong efficiency hypotheses is that in the latter case, nobody should be able to systematically generate profits even if trading on information not publicly known at the time. In other words, all information even apparent company secrets are incorporated in security prices; thus, no investor can earn excess profit trading on public or non-public information (Malkiel, 1999).

The EMH has had a lot of critics that claim markets are not efficient. The following are some of the arguments presented to show that capital markets are not efficient.

2.2 Behavioral finance

During the 1990s, a new field known as behavioral finance began to emerge in many academic journals, business publications, and even local newspapers. However, (Ricciardi and Simon 2000), assert that the foundations of behavioral finance, can be traced back over 150 years. Several books written in the 1800s and early 1900s marked the beginning of the behavioral finance school of thought. For example, in 1841, MacKay published a book called Delusions and the Madness of Crowds which presented a chronological timeline of the various panics and schemes throughout history. “This work shows how group behavior applies to the financial markets of today.” (Ricciardi & Simon, 2000. pp 1).

Another author called Le Bon also wrote a book, The Crowd: a Study of the Popular Mind, discusses the role of “crowds” (also known as mob psychology) and group behavior such factors apply to the fields of behavioral finance, social psychology, sociology, and history. Selden's 1912 book Psychology of the Stock Market was one of the first to apply the field of psychology directly to the stock market. And according to (Ricciardi and Simon 2000), this classic book discusses the emotional and psychological forces at work on investors and traders in the financial markets. These three works along with several others form the foundation of applying psychology and sociology to the field of finance. Today, there is an abundant supply of literature including the phrases “psychology of investing” and “psychology of finance” so it is evident that the search continues to find the proper balance of traditional finance, behavioral finance, behavioral economics, psychology, and sociology. (Ricciardi and Simon 2000).

Behavioral finance is a new approach to financial markets that has emerged, at least in part, in response to the difficulties faced by the traditional paradigm. In broad terms it argues that some financial phenomena can be better understood using models in which some agents are not fully rational. More specifically, it analyzes what happens when agents and investors relax one or the two tenets that underlay individual rationality (Nicholas Barberis & Richard Thaler, 2003).

Ricciardi & Simon (2000) believe that the key to defining behavioral finance is to first establish the definitions of psychology, sociology and finance.

Source: Ricciardi & Simon (2000).

Ricciardi & Simon (2000) define sociology as the systematic study of human social behavior and groups. This field focuses on the influence of social relationships on peoples attitudes and behavior. In behavioral finance, the argument by those that support it is that the behavior of people does affect the rationality within the makets. Thus the study of people's behavior (sociology) becomes a very vital factor in its contribution to behavioral finance. Finance is defined as a discipline concerned with determining value and making decisions. In deciding on what to invest in the investors have to use different finance measures such as ratios to determine whether to invest in a particular stock or not. Psychology on the other hand is defined as the scientific study of behavior and mental processes are affected by a human being's physical, mental state and external environment. The psychology of individuals involved in investment markets is the main focus of behavioral finance as the psychology of different individuals makes them to react differently to different situations thus causing markets to be inefficient (Ricciardi & Simon 2000). These three factors form an interelationship and are integral catalysts of behavioral finance.

Human decisions are subject to several cognitive illusions. These are grouped into two and are discussed below.

2.3 Heuristics

Heuristics involves a decision process by which the investors find things out for themselves, usually by trial and error. It is also referred to as the rule of thumb and humans use it to make decisions in complex, uncertain environments (Tony Brabazon 2000). This is a clear indication that the investors' decision making process is not strictly rational. Even though investors have collected the relevant information and objectively evaluated it, a process in which the mental and emotional factors are involved, it is often very difficult to separate the emotions from the decisions made and they may end up being good, but many times it may result in suboptimal investment decisions.

The thumb rule is further explained as 1/N rule; such that when faced with N choices for how to invest retirement money, many people allocate using the 1/N rule. If there are three funds, one-third goes into each. If two are stock funds, two-thirds goes into equities. If one of the three is a stock fund, one-third goes into equities. Recently, Benartzi and Thaler (2001) pp 79-98, have documented that many people follow the 1/N rule.

The following are some of the examples of heuristics in decision making:

  1. Overconfidence
  2. Representativeness
  3. Anchoring
  4. Herd behavior
  5. Gamblers fallacy
  6. Cognitive Dissonance
  7. Disposition Effect
  8. Availability bias

2.3.1 Overconfidence

According to (Johnson et al, 2002) the key behavioral factor and perhaps the most robust finding in the psychology of judgment needed to understand market anomalies is overconfidence. People tend to exaggerate their talents and underestimate the likelihood of bad outcomes over which they have no control. The combination of overconfidence and optimism causes people to overestimate the reliability of their knowledge, underestimate risks and exaggerate their ability to control events which lead to excessive trading volume and speculative bubbles. The greater confidence a person has in himself, the more risk there is of overconfidence.

There are several dimensions to confidence. It can give more courage, and is often viewed as a key to success. Although confidence is often encouraged and celebrated, it is not the only factor to success. For example as different individuals invest, they become too overconfident and end up investing too much in a familiar company especially in local companies this means that their investments portfolios aren't well diversified and in case there is a slump in the local investments then the overconfident investor may end up losing out on his investment Johnssonm et al (2002).

Another aspect of overconfidence is usually manifested in the gender of the investors. Research has shown that men tend to be more overconfident than women even when they are making investment decisions. Barber and Odean (2001) recently analyzed the trading activities of people with discount brokerage accounts. They found that the more people traded, the worse they did, on average. And men traded more, and did worse than women investors.

2.3.2 Representativeness

This theory of behavioral finance asserts that investors' recent success tend to continue into the future. People underweight long-term averages and tend to put too much weight on recent experience. This is sometimes known as the “law of small numbers.”. One mental shortcut, the representativeness bias, involves overreliance on stereotypes (Shefrin, 2005 pp17). Representativeness leads people to form probability judgments that systematically violate Bayes's rule

A good company is not necessarily a good investment. Investors tend to think one equals the other. People also make representativeness errors in financial markets. For example, investors often confuse a good company with a good investment. Good companies are those that generate strong earnings and have high sales growth and quality management. Good investments on the other hand include securities that have their prices increasing and if the investor was to sell his security he would make a profit. This raises the question whether stocks of good companies are necessarily good investments. Good companies do not always make good investments. Investors make the mistake of believing they do because they believe that the past operating performance of a company is representative of its future performance and they ignore information that does not fit into this notion. (Solt & Statman, 1989).


The concept of anchoring can be explained by the tendency to attach or "anchor" our thoughts to a reference point - even though it may have no logical relevance to the decision at hand. (Phung, 2008). Anchoring can further be defined as the decision making process where quantitative assessments are required and where these assessments maybe influenced by suggestions. (Johnson et al, 2002).

Phung, 2008, further explains that investors tend to believe that stocks which have fallen considerably over a short period now can be bought at a discount. This misperception is due to the fact that the investor has mentally anchored a high price for that specific stock, a type of base price acting as a reference point. Disregarding the reason for that stock's evident drop, the anchored higher price is mentally considered its “rightful” price. The stock is therefore believed to bounce back over a certain time period.

Shefrin (2000) explains further that anchoring also deals with the concepts of conservatism and adjustment problems. Some analysts do not adjust their earnings prediction properly in response to new information presented in earnings announcements; they conservatively trust and focus too much on their initial forecasts and when things change, this causes them to under-react. But if there is a long enough pattern, then they will adjust to it and possibly overreact, underweighting the long-term average.

2.3.4 Herd behavior

A fundamental observation about the human society is that people who communicate regularly with each other think similarly. One of the reasons why people tend to think or react similarly to situations is when they are reacting to the same information. Social power also has an immense power on individual judgment. For example if an individual has a particular way of thinking but the rest of the people seem to be taking the opposite direction, the individual may change his way of thinking because he thinks the majority cannot be wrong. (Shiller, 2000) This is what is commonly referred as the mob psychology or herd behavior.

Most individuals go back to school for a vast number of reasons; some do so to progress in their professions but a significant number do so because others are doing it. In the case of investments, we see that until recently individuals did not invest as much in the Nairobi Stock Exchange, but it was like a fashion or trend such that most people started investing their money in shares and bonds. Another classic example of herding behavior is the IT-boom in the late 1990's. During this time, the general feeling among investors was that the price levels on the stock market were too high. Yet almost everyone wanted to stay in the market, since they were afraid of missing the ride. When the bubble burst it was too late, and investor's made huge losses. Another important variable to herding is word of mouth. People tend to trust their family members, their friends and colleagues more than other sources of information such as the media. Most people know of investment opportunities through their friends and colleagues rather than newspapers, business magazines and other sources of media. (Bernéus et al, 2008)

2.3.5 Gamblers fallacy

According to M. Kannadhasan, (2006) gambler fallacy arises when the investors inappropriately predict that a trend will reverse. For example, when tossing a coin with a fair chance between head or tail, most people think the probability of getting a tail increases after a run of five heads in a row. This is a common but completely false perception. The chance of getting a head in an individual toss of a coin has always the probability of 50%. People tend to think that every segment of the random sequence must reflect the true proportion.

The fairness of the coin makes the gambler feel that a head will cancel out a tail. In investments when a person is investing if a company has performed well in one year if the investor believes that the head (good performance) cancels out the tail, (bad behavior) then he will believe that in the next year the chance of good performance is higher.

Sometimes investors may fall prey to gamblers fallacy, for example if the price of shares keep going up, a shareholder may sell off his shares because he doesn't believe that any further rise will occur. What the investor does not realize is that the share price may still go up in the next trading session causing him to loose out on those returns. (Phung, 2006)

2.3.6 Cognitive Dissonance

(Johnson et al, 2002) describes cognitive dissonance as the mental conflict that people experience when they are presented with evidence that their beliefs or assumptions are wrong. It can be classified as a sort of pain of regret, regret over mistaken beliefs. They further assert that there is a tendency for people to take actions to reduce cognitive dissonance that would not normally be considered as rational such as avoiding new information or developing contorted arguments to maintain beliefs or assumptions. The theory of regret may attribute to the phenomenon of money flowing more rapidly into mutual funds or stocks that have performed extremely poorly because the investors do not want to accept the fact that they were wrong in their predictions.

2.3.7 Disposition Effect

Camerer (1998) describe the disposition effect as: “the tendency to sell assets that have gained value (winners) and keep assets that have lost value (losers)”.

Weber e Camerer (1998) realized an experiment where subjects bought and sold shares in six risky assets. Subjects did tend to sell winners and keep losers, exhibiting the disposition effect. Disposition effect among individual investors is defined by Odean (1998) as a tendency to sell winners too soon and hold on to losers too long. Investors have a notion that making a profit from an investment maintains ones self esteem however, if they make losses they implicitly admit an erroneous investment decision, and hence avoid such investemts. Interestingly, past winners do better than losers following the date of sale of stock by an individual investor, suggesting a perverse outcome to trades by individual investors. Odean (1998) further shows that individuals who trade the most are the worst performers.

2.3.8 Availability bias

According to M. Kannadhasan (2006) availability bias happens when investors place undue weight for making decisions on the most available information. This happens quite commonly. It leads less return and sometimes poor results also. When confronted with a decision, humans' thinking is influenced by what is personally relevant, salient, recent or dramatic. Put another way, humans estimate the probability of an outcome based on how easy that outcome is to imagine.

When investing, availability bias can result in investors paying more attention to stocks covered heavily by the media, while the availability of information on a stock influences investors' tendency to invest in a stock. The boom of 1999/2000 is a great example. The availability of information and media coverage of internet stocks was such that people were more inclined to invest in them than they would have otherwise been (Buffett, 2007).

2.4 Prospect theory

In 1979, Kahneman and Tversky presented an idea called prospect theory. This theory according to Phung, (2008) explains how people value gains and losses differently by preferring anything that is termed in terms of gain. In this context as people make their investment decisions and they are presented with two equal choices, one expressed in terms of possible gains and the other in possible losses, people would choose the former - even when they achieve the same economic end result. Prospect theory is also explained by Kahneman and Tversky, (1979) as an alternative decision-making model to expected utility theory. The utility theory offers a representation of truly rational behavior under certainty and investors are risk averse. Johnsson et al, (2002).

Prospect theory contrasts the utility theory in that the prospect theory is a descriptive theory of choice under uncertainty while the expected utility theory is normative rather than descriptive. Prospect theory focuses on changesin wealth, whereas expected utility theory focuses on the levelof wealth. Gains and losses are measured relative to a reference point. Prospect theory also assumes loss aversion. Prospect theory also incorporates framing where individuals if faced by two related events occur, they have a choice of treating them as separate events (segregation) or as one (integration) (Ritter, 2003).

2.4.1 Mental Accounting

Thaler (1999) defines mental accounting as following: “mental accounting is the set of cognitive operations used by individuals and households to organize, evaluate, and keep track of financial activities” People sometimes separate decisions that should, in principle, be combined. For example, many people have a household budget for food, and a household budget for entertaining. At home, where the food budget is present, they will not eat lobster or shrimp because they are much more expensive than a fish casserole. However, in a restaurant, they will order lobster and shrimp even though the cost is much higher than a simple fish dinner. If they instead ate lobster and shrimp at home, and the simple fish in a restaurant, they could save money. But because they are thinking separately about restaurant meals and food at home, they choose to limit their food at home (Ritter, 2003).

Prospect theory shows that people use mental accounting when making financial decisions. Mental accounting to investors is the tendency to classify different financial decision problems under separate mental accounts, while ignoring that it would be rational to integrate these choices into one portfolio decision. Prospect theory decision rules are then applied to each account separately, ignoring possible interaction(Prast, 2004). Investors mentally keep separate accounts, one for each investment, or one for covering downward risks - for which they use such instruments as bonds - and one for benefiting from the upward potential, for which they use stocks. Although portfolio theory predicts that it would be optimal to integrate these elements mentally, in practice people behave differently.

One reason for this behaviour may be that the investor wishes to exert self-control. If he keeps separate accounts for different sorts of expenditure, he may be less easily tempted to use his nest egg for an impulse purchase (Thaler & Shefrin, 1981). When a new stock is purchased, a new mental account is opened. Another example of mental accounting would be a broker telling his client to “transfer” an asset rather than tell him to “sell” it. By doing this, the stockbroker makes the client feel that he is not selling at a loss but instead he is just transferring money from one mental account to another one (Shefrin, 2000)

2.4.2 Loss aversion

Loss aversion refers to that individuals are more sensitive to losses compared to gains. (Bernéus et al, 2008). Empirical studies have shown that a loss has about twice the negative impact compared to a gain. A person who would have gained kshs 1000 and then lost kshs 500 so that his net gain would be kshs 500 would feel less “happy” compared with a person who would just have gained kshs 500.

Kahneman and Tversky (1979) conducted a series of studies in which subjects answered questions that involved making judgments between two monetary decisions that involved prospective losses and gains. In their study they established that people were willing to settle for a reasonable level of gains (even if they have a reasonable chance of earning more), but were also willing to engage in risk-seeking behaviors where they could limit their losses. In other words, losses are weighted more heavily than an equivalent amount of gains.

The magnitude of loss aversion can be shown in the diagram below.

As illustrated in the diagram above, it is evident that a loss has about twice the negative impact compared to a gain. A person who would have gained $100 and then lost $50 so that his net gain would be $50 would feel less “happy” compared with a person who would just have gained $50 (Benartzi & Thaler, 1995).

The prospect theory can be used to explain quite a few illogical financial behaviors. For example, there are people who do not wish to put their money in the bank to earn interest or who refuse to work overtime because they don't want to pay more taxes. Although these people would benefit financially from the additional after-tax income, prospect theory suggests that the benefit (or utility gained) from the extra money is not enough to overcome the feelings of loss incurred by paying taxes (Phung, 2006).

Loss aversion also has its consequences. For example people hold on to losers too long and sell winners too soon. Leroy Gross describes the difficulties investors face. “Many clients, however, will not sell anything at a loss. They do not want to give up the hope of making money on particular investment, or perhaps they want to get even before they get out. “The “getevenitis” disease has probably wrought more destruction on investments portfolios than anything else...” (Shefrin 2000, pp. 150).

2.4.3 Framing

Mental accounting, combined with loss aversion and a multi-dimensional risk attitude, results in the framing effect. This is the phenomenon that decisions under risk are influenced by the way the decision problem is framed. If a decision is framed in terms of losses, people tend to choose a risky outcome, whereas they tend to avoid risk when the problem is presented in terms of winning. A frequently cited example to illustrate the framing effect is the following. ‘Imagine that you are an army official in a war, commanding six hundred soldiers. You have to choose between route A, where two hundred soldiers will be saved, or route B, where there is a one-third chance that all soldiers will be saved and a two-third chance that none will be saved. Which route do you take?' Most people tend to choose route A when the decision problem is framed in this way. However, the decision problem can also be framed as follows. ‘You have to choose between route A, where four hundred soldiers will die, or route B, where there is a one-third chance that no soldiers will die and a two-third chance that all will die.' When the decision problem is framed in this way, most people choose route B, although the objective characteristics are no different from the first problem (Belsky and Gilovich, 1999).

2.4.4 Regret Aversion

According to (M. Kannadhasan,) Regret aversion arises from the investors' desire to avoid pain of regret arising from a poor investment decision. This aversion encourages investors to hold poorly performing shares as avoiding their sale also avoids the recognition of the associated loss and bad investment decision. Regret aversion creates a tax inefficient investment strategy because investors can reduce their taxable income by realizing capital losses. In the recent economic downturn that has caused most securities to perform poorly in the markets, most investors in Kenyan for example those who invested in the Safaricom shares, will hold on to them since they do not want to accept the fact that they made a bad investment.

2.5 Conclusion

Though the illusions discussed are observed among investors, they will not affect investors simultaneously the susceptibility of an investor to a particular illusion is likely to be a function of several variables. For example, there is suggestive evidence that the experience of the investor has an explanatory role in his regard with less experienced investors being prone to extrapolation (representativeness) while more experienced investors commit gambler Fallacy. (Kahneman and Tversky, 1979). Similarly, behavioral factors play a vital role in the decision making process of the investors. Ann thus investors has to take necessary steps to minimize or avoid illusions that may influence their decision making process, especially when making investment decisions.

2.6 Conceptual framework on the role of Behavioral finance on investment decisions

The investment decision is the dependent variable. As investors trade in security markets they are faced by a number of different investment decisions. Then the independent variables i.e. the psychological factors will affect the investors perceptions and finally based on the different factors and how they will affect the thinking of the investor, he or she will finally make a investment decision. The psychological factors are broadly characterized into two that is the heuristics and the prospect theory.



3.0 Introduction

Ethridge (2004) defines methodology as the manner in which individuals approach and execute various responsibilities. Methodology constitutes the different rules or procedures that are used to accomplish a task such as a research study. Research methodology provides the guidelines to be used in the study such as how the study will be organized, how it will be planned and the different designs that will be used to perform the study.

This chapter will describe the methods the researcher will use in carrying out the study. It is organized along the following sub sections: research design, target population, sample size and sampling procedures, research instruments, instrument validity and reliability, data collection procedures and data analysis.

3.1 Research Design

According to Peil (1995) a research design involves planning, organizing, collecting and analyzing data to produce the information the researcher is looking for. For this study a case study method will be adopted. A case study is defined by Kothari (1990) as a study that focuses on a specific entity so as to do an in depth study of relationships experiences e.t.c. this method was chosen since it helps better understanding of the problem under study and it enables the researcher to do an in depth study of the institution or entity under study.

A research can either be inductive or deductive. According to Gratton & Jones (2004) deductive research is related to the positivist and quantitative research. Deductive research involves the development of an idea or a hypothesis from a theory that exists and the idea or hypothesis is then tested through collection of data. On the other hand inductive research is associated mostly with qualitative studies. The data is first collected in inductive research and then analyzed to come up with a theory.

The research approach that will be used for this study is the deductive approach since the research is based on theories of behavioral finance. These theories will be used to test the findings of this research.

Since the quantitative method is often associated with deductive research, the same will be the method that will be adopted in this research. A quantitative method is formalized and concentrates on numerical observations. The qualitative method on the other hand is less formalized and tests whether the information is valid (Johnson et al, 2002).

Quantitative data will be collected through a survey in the form of a questionnaire that will be given to MBA students at Daystar University town campus. Through the questionnaire, the researcher will try to determine whether the different aspects of behavioral finance do indeed affect the investment decisions.

3.2 Target population

Population refers to an entire group of individual's events or objects having a common observable characteristic. In other words, population is the aggregate of all that conforms to a given specification (Mugenda &Mugenda, 2003).Also Kiess (1989) argues that population is some set of measurements of people, animals, objects, or events, that in principle can be identified. According to Kumar (2005) population is the class, families, living the city or electorates from which you select a few students, families, electors to question in order to find answer to your research questions.

The target population for this study is Daystar MBA students. Daystar MBA students are currently 314 these are divided into the following concentrations:

MBA Human Resource Management


MBA Marketing


MBA Strategic Management


MBA Finance




3.3 Sampling Design

Sampling involves selection of a smaller sub group within the population that represents a large group in which they were selected (Kathuri et al, 1993 ) The sampling adopted for this study will be based on Morgan's (1970) sampling formula

It states:

M= N


Where M=Minimum sample size

Ps=Proportion of total cases expected in the smallest category available

N=Total population

Based on the above model, the following sample sizes are recommended for corresponding populations

Population size
































Source: Kathuri (1993).

The researcher will use the table to choose a sample of 169 respondents.

3.4 Data collection

Data can be collected from primary sources or secondary sources. Primary data is data that has been collected by the researcher while secondary data involves data that already exists but needs to be extracted from the source (Lundahl & Skarvad, 1999). In quantitative research a researcher can use two main methods to collect primary data. It can be through observation or by using a questionnaire (McNabb, 2002). For this research, primary data will be the main source of data and this will be collected through a questionnaire that will be directed to MBA students at Daystar University students to try understand their response to different psychological issues that they maybe faced with when making their investment decisions. The questions in the questionnaire will be close ended. Secondary data obtained from this research is mainly from books, journals, dissertations and the internet.

3.4.1 Advantages of using questionnaires

According to McNabb (2002) the following are some of the main reasons that would encourage a researcher to use a questionnaire in his or her study.

  1. Flexibility such that the researcher is able to design the questions that relate to the research objectives.
  2. The answers from the respondents are easy to code thus reducing time and costs that could have been incurred.
  3. It is less time consuming as compared to interviews since the researcher will just drop the questionnaires explain how they are to be filled and then pick them up later after they have been filled.
  4. The data is easy to analyze as the researcher designs the questions in a way that they attempt to answer the research questions.

3.4.2 Limitations of using questionnaires

Johnson et al (2002) explains that even though the questionnaire is seen advantageous it maybe faced by a number of limitations. These include:

  1. Susceptibility to subjective opinions by the respondents especially when asked about past experiences s they may have changed their way of thinking after the actual results of that event.
  2. The way one respondent understands a question could be different from the other and the researcher may end up with very different answers that may be hard to analyze.
  3. Low response rate may occur as the respondents may feel that their privacy is being invaded.

These limitations will be addressed by the researcher by ensuring that the questions are not ambiguous or vague so as to be able to interpret the data well. The researcher will also assure the respondents on the findings being kept confidential.

3.5 Validity and reliability of research instruments

The confirmation of validity and reliability of instruments is very crucial so as to ensure the information collected is appropriate, correct and useful.

3.5.1 Validity

According to Mugenda et al (1999) validity refers to the accuracy and meaningfulness of inferences, which are based on the research results. It is the degree to which results obtained from the analysis of the data actually represent the phenomenon under study. Validity therefore, has to do with how accurately the data obtained in the study represents the variables of the study. Yin (1994) looks at validity as how well the data collection and analysis captures the true picture of the element being studied. Validity involves asking the right questions that are not ambiguous or vague.

3.5.2 Reliability

Reliability according to Yin (1994) is the ability of a data collection technique being repeated and producing the same outcome. Reliability ensures that if a different researcher was to conduct the same study the results he should draw the same conclusions as the previous research.

To minimize the risk of having unreliable and data that isn't valid, the questionnaire will be sent to a test group selected randomly to check whether the questionnaire is correctly structured and that it covers the objectives of the study. The test questionnaires will be sent to 1% of the target sample. Feedback obtained from the pilot study will assist the researcher in revising the questionnaire to ensure that it covered the objectives of the study elicits exactly the same information every time it is administered. The main reason for piloting the questionnaire will be to ensure as far as possible that the items will detect the kind of responses the researcher intends to get, that they are acceptable in terms of their content, and they adequately cover any aspect of the area which the researcher particularly wish to explore.

3.6 Data analysis

Rossman et al (1988) defines data analysis as the process of bringing meaning to a mass of detailed information. It involves categorizing data interpreting them, and verifying that they do in fact meaningfully reflect the phenomenon chosen for study. Since this study is about the effect of behavioral finance on investment decisions, correlation on the two variables will be tested. This will be done through the Statistical Package for Social Scientist (SPSS). The data will also be analyzed using descriptive and inferential statistical methods particularly frequency charts, pie charts, tables, percentages, mean and standard deviation. The results will be presented using tables and charts.


Andrew Lo. (2008). “Hedge Funds, Systemic Risk, and the Financial Crisis of 2007-2009,” written testimony for the House Oversight Committee Hearing on Hedge Funds, pp 12-20

Barber, Brad, and Terry Odean, 2001. “Boys will be boys: Gender, overconfidence, an