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Traditional Finance And Behavioral Finance

Info: 8038 words (32 pages) Example Literature Review
Published: 13th Oct 2021

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Tagged: Finance


This research studies the relation between Traditional Finance & Behavioral Finance. Extensive literature investigates the reactions of the investors in different situations & personality traits. Traditional Finance focuses on the Efficient Market Hypothesis (EMH). The EMH proposes that competition between investors seeking abnormal profits drives prices to their correct value. In contract, Behavioral finance assumes that, in some situations, financial markets are informationally inefficient.

Behavioral Finance in getting momentum & becoming an important alternative to market efficiency in explaining many of the empirical anomalies observed over the past few decades. The study is conducted to understand the factors which force investors to behave differently are & how these factors influence their post investment behavior. Based on the traditional finance perspective, investors are rational & act on the information available in the market which is a main pillar in their investment decisions. While behavioral finance looks at irrationality of the investors where they make their own analysis mainly based on personality traits or past behavior.

This study is an attempt to understand whether investors always follow traditional finance perspective or catch by their own beliefs or trial & error behavior. Behavioral finance proposes that investors follow Goals based investing where they try to meet important or basic needs first then move on towards aspirations.

Traditional Finance tends to think in terms of investment results in terms of percentage returns, statistical risk & many investors define their investing objectives quite differently (Behavioral Finance). Most of the time, they define them in terms of personal lifestyle objectives or Goals based investing. Reframing the investment process in terms of investor’s Goals can provide clearer picture of how investment decisions are related to different variables not captured by traditional finance.

Literature Review

In the literature of finance, Behavioral finance is a relatively new development. There are number of studies conducted by researchers where behavioral finance has been added with traditional analysis to assess the differences in the investment decision. The impacts, estimations & application of behavioral finance in investment decision making have been originated by academicians, but now it is fast growing in the practical field when analyst or portfolio managers construct the investor’s portfolio.

Kausar, Taffler (2005) focused on to explain market over & underreaction in both bad & good news & concluded that investors suffer from such behavioral biases as overconfidence, self attribution biases & representativeness, tested the impact of going concern announcement which reveals that investors take these things positive & start basing their decision on this good news in future as well even market is depicting or giving other information which may change their return expectations. By looking at Heuristic (Rule of Thumb) that good news will always bring positive returns clearly shows investor’s decision based on past behavior for which he is using as representative.

Shiller R. (2004) worked on underlying behavioral principles, which come primarily from Psychology & sociology, depicting that these personality traits do have important & profound effect on efficiency of the financial system but on the other hand concluded that traditional finance has shown over a period of time efficiency in the financial system. These behavioral traits impact the financial system & lead towards inefficiency because every investor has heterogeneous expectations & act on the investment based on the way the information received & in which condition that information is received (Frame Dependence).

Shefrin & Thaler (1988) have identified a process of Heuristic-driven bias in the investment process where people develop general principles as they find things out for themselves, they rely on heuristic (rule of thumb) to conclude or draw inference from information at their disposal, people are susceptible to particular errors because the heuristics they use are imperfect & people actually commit errors in particular situation. Representativeness is the heuristic process identified by which investors base expectations upon past experience, applying stereotypes. It can take many forms where any time investor bases expectations for the future on some past or current characteristic or measure, the individual is applying an “if-then” heuristic. That is “if this has happened, then that will happen.

Shefrin & Thaler (1988) have also concluded that investors when trapped by Heuristic-driven bias tend to become overconfident in their abilities to predict & start believing that they are better able to interpret the information & place greater confidence in their forecasting abilities. This overconfidence tends to systematically underestimate the risk inherent in the investment decision. Overconfidence leads investors to witness surprises sometimes positive & sometimes negative making the financial market inefficient based on their wrong forecasts because of their trap with overconfidence.

Biais et al. (2000) also revealed some interesting results suggesting that there is indeed a correlation between some of personality traits & judgment biases measured by psychology questionnaire & the behavior & performance of the subjects in the experimental trading game. This shows that investors when taking decisions sometimes ignore the traditional finance perspectives & start behaving as per their traits which make them involve in trading game to transact more in the hope to realize more profit. They tend to place more orders but they do not tend to place unprofitable orders more frequently. This trading game affects behavior which investors make as a base for future forecasting leading to sometimes misjudgment in properly forecasting the investment return.

Ricciardi & Simon (2000) have concluded that Standard finance is the centerpiece of the behavioral finance as behavioral finance involves different fields of study in consideration & there is an integration of fields in behavioral finance which makes it totally unique in the finance field. Ricardi & Simon (2000) have proposed that behavioral finance attempts to explain & increase the understanding of the reasoning pattern of investors including the emotional processes involved & the degree to which they influence the decision making process & explaining Why, What & how of finance & investing, from a human perspective. Ricardi & Simon (2000) have also proposed that psychological & social factors impact the decision making process of the investors & their reactions in different timings & different personality traits.

Shefrin (2000, p 4) also described the behavioral finance as the interaction of psychology & financial actions & performance of the practitioners (all types/categories of investors). He recommends that these investors should be aware of their own “investment mistakes” as well as the “error of judgment” of their counterparts. Shefrin (2000, p 4) stated that one person’s mistakes can become another person’s profit.

Barber & Odean’s study (cited in Ricciari & simon 2000, p 3) stated that “people systematically depart from optimal judgment & decision making”. Fuller’s study (cited in Ricciardi & Simon 2000, p 3) described his viewpoint about behavioral finance by noting that people systematically make mental errors & misjudgment when they invest their money as a portfolio managers or as an investors, recognizing the mistakes of others (a mis-priced security such as a stock or a bond) may represent opportunity to make a superior investment return.

Wood’s study (cited in Ricciardi & Simon 2000, p 3) described the prolific evidence that money managers & investors are not able to come up to the expectations. In quest for reasons, academics & practitioners alike are switching to behavioral finance to find clues & hints to deviations in their opinions & actual outcome. Wood’s study (cited in Ricciardi & Simon 2000, p 3) demonstrated that it is the study of our behavior as a human & investors can not be rational in the way equilibrium models (traditional finance models like EMH) are. Rather investors play games that include self interest, self attribution etc & financial markets are real games. They are the arena of fear & greed. Our apprehensions & aspirations are acted out every day in the market place… So perhaps prices are not always rational & efficiency may be a textbook hoax.

Mahajan’s study (cited in Ricciadi & Simon, 2000, p 3) proposed overconfidence as “an overestimation of the probabilities for a set of events”, as human being; we have a tendency to overestimate our own skills & predictions for success. In both the areas of psychology & behavioral finance the subject matter of overconfidence continues to have substantial presence. As investors, we have inherent ability of forgetting or failing to learn from our past errors such as bad investment or financial decision. This failure to learn from our past decisions further adds to our overconfidence dilemma.

Barber & Odean’s Study (cited in Ricciardi & Simon 2000, p 4) have produced very interesting findings of differences in trading habits according to an investor’s gender. The study found that men were more overconfident that women regarding their investing skills & that men trade more frequently. As a result, men not only sell their investment at the wrong time but also incur huge trading cost. Females trade less (buy & hold their securities), at the same time reducing trading cost. The study found that men trade 45% more than women & more surprisingly, single man trades 67% more than single woman. The trading cost reduced men’s net return by 2.5% per year compared to 1.75% for women. This difference in portfolio return over time result in women having greater net wealth because of the power of compounding interest over a 10 to 20 years time horizon. (Known as time value of money)

Merton’s study (cited in Ricciardi & Simon 2000, p 4) states that people feel internal tension & anxiety when subjected to conflicting beliefs. As individuals, we attempt to reduce our inner conflict in one of two ways (a) we change our past values, beliefs or opinions (b) we attempt to justify or rationalize our choice. This may apply to investors or trades in stock market who attempt to rationalize contradictory behaviors, so they seem to follow naturally from personal values or viewpoints.

Goetzmann & Peles’s study (cited in Ricciardi & Simon 2000, p 4) examined the role of cognitive dissonance in mutual fund investors. They argued that some mutual fund investors may experience dissonance during mutual fund investment process, especially decision to buy, sell or hold. They have shown that investor’s dollar is more allocated to leading funds (mutual funds with strong performance gains) than outflow from lagging funds (mutual funds with poor investment returns). Essentially, investors in the poor performing funds are reluctant to admit that they made a bad investment decision. The appropriate course of action would be to sell underperforming more quickly. However, investors choose to hold on to these investments. By doing so, they do not have to admit they made investment mistake.

Bell’s Study (cited in Ricciardi & Simon 2000, p 5) described regret as the emotion caused by comparing a given outcome or state of events with the state of forgone choice. Regret theory can also be applied to the area of investor psychology within the stock market. Whether the investor has contemplated purchasing a stock or mutual fund which has declined or not, actually purchasing the intended security will cause the investor to experience emotional reaction. Investors may avoid selling stocks that have declined in value in order to avoid the regret of having made a bad investment choice & the discomfort of reporting a loss. Investors sometimes find it easier to purchase the “hot or popular stock of the week”. In essence, investor is just following the “Crowd”. Therefore investor can rationalize his or her investment choice more easily if the stock or mutual fund declines in value. Investor can reduce emotional reactions or feelings since a group of individual investors also lost money on the same bad investment.

Shefrin & Statman (2000) have proposed that a behavioral portfolio theory & its implications for portfolio construction & security design. Portfolios within behavioral framework resemble layered pyramids. Layers are associated with distinct goals & covariances between layers are overlooked. A simple two –layer portfolio, downside protection layer is designed to prevent financial disaster & upside potential layer is designed for a shot at becoming rich. Behavioral Finance is descriptive in nature compared to Markowitz mean-variance which is prescriptive in nature.

Portfolios recommended by financial advisors, such as mutual fund companies, have a structure that is both common & different from the structure of mean-variance portfolios in the CAPM (Capital Asset Pricing Model). Canner, Mankiw & Weil (1997) note that financial advisors recommend that some portfolios be constructed with higher ratios of stock to bonds than other portfolios, advice which is in conflict with “Two Funds Separation”. Advice consistent with two funds separation calls for a fixed ratio of stocks to bonds in the “Risky” portfolio along with varying properties of risk free asset, reflecting varying attitudes towards risk.

Mean-Variance investors evaluate portfolios as a whole; they consider covariance between assets when they construct portfolios. Mean-Variance investors care only about the expected returns & variance of the overall portfolio, not its individual assets. Mean-variance investors have consistent attitude towards risk, they are risk averse. Behavioral investors build portfolios as pyramids of assets, layer by layer, where each layer is associated with a particular goal & particular attitude towards risk.

Friedman & savage (1948) noted the common tendency among individuals to buy lottery tickets & insurance. Individual investors like institutional investors construct their portfolios as pyramids of assets. They hold cash & bonds in the downside protection layer of the portfolio & the goal of this layer is to prevent poverty. They hold growth stock in the upside protection layer of the portfolio & the goal is to make them rich. The link between goals & choices in the presence of uncertainty is at the center piece of

Lopes (1987) proposed two-factor theory of risky choice. The first factor focuses on the goals of security & potential. The goal of the risk averse people is security & the goal of the risk seeking people is potential. Lopes (1987) notes that some people are primarily motivated by security & others are primarily motivated by potential, the two motivations exist in some strength in all people. The second factor in lopes theory is aspiration level. Aspiration level varies among people. Many people aspire to be rich but they differ in the amount of money they define as being rich.

Shefrin & Statman (2000) proposed that in sum, behavioral portfolios are structured as separate layers of a pyramid. Their contents depend on five determining factors. First are investor goals. An increase in the weight attached to the upside potential goal will be accompanied by an increase in the proportion of wealth allocated to the upside potential layer. Second are the reference points of the layers of the portfolio. A higher reference point for the upside potential layer will be accompanied by the selection of securities that are more “speculative.” Third is the shape of the utility function. Higher concavity in the domain of gains reflects earlier satiation with a given security, and early satiation leads to an increase in the number of securities in a layer. Fourth is the degree of inside information, real or imagined. Investors who believe that they have an informational advantage in some securities will take more extreme positions in them. Fifth is the degree of aversion to realization of losses. Investors who are aware of their aversion to the realization of losses hold more cash so as to avoid the need to satisfy liquidity needs by realization of losses.

Moreover, portfolios of such investors contain securities held solely because selling them entails the realization of losses. These portfolios might seem well diversified, but the large number of securities they contain is designed for avoiding the realization of losses, not the benefit of diversification.

Shefrin & Statman (2000) also explained the differences in behavioral investors who are identical except that one is more aggressive than the other. The more aggressive investor attaches greater importance to the upside potential goal, and has a higher reference point for that goal. That investor allocates a higher proportion of his wealth to the upside potential layer, and a lower proportion to the downside protection layer. Which securities will the investors choose for the two layers?

Bonds and cash (the risk-free asset) are well suited to the downside protection layer but not to the upside potential layer. Indeed, some behavioral investors use a heuristic that excludes securities with the bond label from consideration for the upside potential layer and excludes securities with the stock label from the downside protection layer. Aggressive investors who use that heuristic use stocks to increase the allocation to the upside potential layer, thereby increasing the proportion of stocks to bonds in the overall portfolio.

Shefrin & Statman (2000) covered the issue where mean-variance portfolio theory and behavioral portfolio theory contrast is the “home bias.” or “Familiarity”. The home bias refers to the finding that investors hold more of domestic stocks and fewer foreign stocks than the amounts predicted by mean-variance optimization. The home bias is consistent with behavioral portfolio theory. It is one manifestation of the role of labels, a role that does not exist in mean-variance portfolio theory. Consider a foreign stock and a domestic stock with an identical distribution of payoffs. Since foreign stocks seem less familiar than domestic stocks, the foreign label acts on perceptions of payoffs as if there has been an actual increase in the variance of payoffs. That perception leads to a low allocation to foreign stocks. A direct implication of a behavioral portfolio theory prediction that the home bias would decline as investors became more familiar with foreign stocks. There is no such prediction in mean-variance portfolio theory.

Shefrin & Statman (2000) covered & proposed that the behavioral framework is similar in structure of a consumer choice model. Securities are evaluated like commodities. Think of cash, bonds, and stocks as normal goods. A reduction in the expenditure in the downside protection layer leads to fewer purchases of both cash and bonds. If bonds are unsuitable for the upside potential layer, as they will be for all but the least aggressive investors, then the shift in expenditure from downside protection to upside potential will lead to a reduction in bond holdings.

Shefrin & Statman (2000) also presented a contrast between mean-variance portfolio theory and behavioral portfolio theory pertains to the shape of the payoffs of optimal securities. In particular, behavioral portfolio theory predicts that payoff distributions of securities will feature “floors,” such as the floor created by a call option or the limited liability of stocks. Again, there is no such prediction in mean-variance portfolio theory.

Shefrin & Statman (2000) explained the issue of risk. Each mean-variance investor has a uniform risk-averse attitude toward risk, an attitude that applies to the portfolio as a whole. However, each behavioral investor has a range of attitudes towards risk, attitudes that vary across the layers of the portfolio. So, for example, behavioral investors might insist that their money market funds include no corporate bonds, even as they buy IPOs. The contrast between mean-variance portfolio theory and behavioral portfolio theory is especially sharp on the issue of securities with artificial risk, such as lotteries.

Shefrin (2002) identified & described different ways to look at investor’s investment behavior focusing on “Situational Profiling” which places investors into categories according to stage of life or economic circumstances. As investor’s characteristics differ, caution needs to be applied when categorizing individual within broad situational profiles. Situational profile is the first step to understand an individual’s preferences, economic situations, goals & desires.

Shefrin (2002) also explained the sources of wealth of individual & how it impacts the investment decision making, investor whose wealth is created in a passive way or through windfall indicate unfamiliarity with risk & return. In this process, starting point is to classify these individuals as having above or below average willingness to tolerate risk.

Shefrin (2002) mentioned that the key to measuring wealth is that it is not the absolute size of the portfolio that matters but rather the perception an individual has regarding his wealth level. In general, a positive correlation exists between perception of portfolio size & the level of risk tolerance. Shefrin (2002) explained that behavioral finance assumes investor exhibit three personality characteristics: first is the loss aversion, investors prefer large uncertain losses to smaller certain losses, second is Biased expectation, investors have too much confidence in their ability to forecast the future, third is Asset Segregation, instead of evaluating an investment’s impact on the overall portfolio basis, investors focus on individual assets. The result can be more risk than is necessary due to lack of diversification (This is referred as mental accounting or pyramiding)

Nevins (2004) proposed goals oriented investing where investors look at risk in behavioral perspective as probability of shortfall while returns are considered as expected final value over a period of time. Investors tend to report their investment objective in goals rather than in percentage return demonstrating that investors follow behavioral traits in investment decisions or they are trapped by biases in making investments to achieve goals set for a particular event & look at loses, the probability of shortfall is the most relevant measure of risk.

Theoretical Framework

In our study we have identified four core factors influencing the investment decisions, therefore, we take investment decision as the dependent variable and overconfidence, regret, pyramids and risk as independent variables as highlighted in following diagram;

  • Overconfidence
  • Regret
  • Pyramid
  • Risk
  • Stock Investment Decisions
  • Independent Variables

Over Confidence

It is overestimating or exaggerating one’s ability to successfully perform a particular task. In terms of investing, overconfidence can be detrimental to stock-picking ability. In a 1998 study entitled “Volume, Volatility, Price, and Profit When All Traders Are Above Average”, researcher Terrence Odean found that overconfident investors generally conduct more trades than their less-confident counterparts because of the feeling that they are more confident and have access to all the material information.

Overconfident investors/traders tend to believe they are better than others at choosing the best stocks and the best time to enter/exit a position. Unfortunately, traders executed the most trades tended, on average, to receive significantly lower yields than the market. Investors take bad bets because they fail to realize that they are at an informational disadvantage, they usually base their decisions on their past fruitful performances. When looking at past investment decisions you’ve made, realize, just because you won the last deal.

Further, keeping in mind those professional fund managers, who have access to the best investment/industry reports and computational models in the business; can still struggle at achieving market-beating returns. The best funds managers know that each investment day presents a new set of challenges and those investment techniques constantly need refining.

One way of illustrating this is asking investors to predict a confidence interval around the expected return on a stock. The investors will consistently make the interval too narrow (they will set the range of possible returns too narrow). That is, they tend to systematically underestimate the risk of the returns on the stock.

The point of concern is that overconfidence can lead to surprises. Since investors continually underestimate the range of possible returns, there is higher than normal probability of a return outside the confidence interval (i.e. a surprise)

The primary factor leading to overconfidence in professionals is Knowledge (education or experience), which leads them to think they know more than they do & con produce better forecasts than they do. They feel their forecasts are based on Skills(an illusion of knowledge), so when their forecasts are inaccurate the blame is usually placed on some outside factors. When asked how well they performed over a given period, analysts tend to consistently overstate their performance (only recall where they performed well). The problem is that they are not deliberately misleading (lying): the inaccurate recollection of their performance is an unconscious attempt to avoid cognitive dissonance. Cognitive dissonance is a disagreement (dissonance) between the analysts actual abilities to forecasts & their perceptions of their ability to forecast.

Another factor which leads investors towards overconfidence is the familiarity of investors with the firm operating in the vicinity where they live or work. This is also called Home Bias where investors place more concern to the domestic firms rather than foreign firms. They feel that they know more about domestic firms or they are familiar with the operations & working of the firms rather than looking at the actual performance, they start investing in domestic firms which leads them to overconfidence attribute finally impact their investment decisions & bad returns. One of the examples easily found is that when allowed, employees tend to invest more in sponsor firm’s stock thinking that they know more about their firm & performance without looking at the actual market information placing employees in risky position as if firm’s performance decreases, they lose their job & investment as well.

One more factor leading investors to overconfidence behavior is the price target revision where investors set a price of the security at certain level when the price of the security moves closer to target, investors become overconfident in their forecasting abilities & revise the price target upward making investors more exposed to risk if the price of the security moves other way around.


Some investors avoid taking decisive actions because they fear, in hindsight, that whatever course they select will end up being less than optimal. Regret aversion can cause some investors to be too timid in their investment choices because of losses they have suffered in the past.

The investors who after making any investment have suffered loses in their stocks, instead of selling their stocks follow a condition called escalation of commitment, in which they constantly hope for betterment of their stock position and justify their decision making in order to avoid cognitive dissonance and hold their investments.

An individual investor, who is confused about buying the stock in a wobbly market, generally decides to wait for a trend confirmation and if the stock breaks out in few trading sessions and he is unable to buy the stock as it hits the upper circuit, then there will be a strong feeling of regret for not buying the stock.

But what if this normal investor had taken exposure and the stock instead declined sharply? There will be a feeling of regret of having bought the stock. Investors do not sell their profitable positions due to the fear that they might forgo the upside potential. Often, riding winners without a trading plan is risky because the stock could reverse direction and wipe out all the unrealized gains.

Regret aversion forces investors to herd. The rationale is that the market cannot be wrong. Besides, if the investment does turn wrong, the investor can at least console himself stating he was not the only one who got it wrong. At the extreme, investors suffering from regret aversion shy away from a market that has declined sharply. Their fear is that the regret will be higher if the market goes down further. In the process, they sometimes fail to seize the opportunity to buy stocks at a bargain.

This factor also impacts the investment decision of the investors affecting the prices of the securities & making the market inefficient. When we compare the behavior of the investors with mean variance analysis, investors are more concern with those decisions where they end up with loses & try to hide the results fearing that they made bad choice so in order to hide that they hold securities for longer impacting their investment decision & ultimately market efficiency.

Regret leads investors to loss seeking behavior as investors have experienced recent losses so in order to report good performance investors start investing in riskier instruments making the portfolio highly skewed to one direction. When investors are trapped with feeling that they made a bad choice by investing in particular instrument, they hold it in order to minimize their regret impacting their decision to sell which they do not do leading to lack of variety in investment.


Pyramid factor is also taken from previous research studies where different researcher concluded that investors based on personality traits follow behavioral approach rather than taking securities collectively (aggregate). Investors have a tendency to focus to meet basic needs first & then secondary needs. Basically investors follow a layer by layer approach putting important & basic needs in the bottom of the layer which has broad base. When investors follow pyramid approach they first strive to meet those needs & according invest to meet those needs. At this layer, they are more concerned to invest in those securities which can generate cash flows to meet those needs. This typically impact their investment behavior leading to focus only less risky investment. Obviously layers are different for every investor but they follow the same strategy to invest first to cover up bottom of the layers. The set goals over the lifetime & invest according to meet those goals. Once primary goals are achieved they strive & invest to meet next layer of goal for which they find out those securities which give more return but add more risk. Because investors after meeting the primary layer where they were more focused on financially security or stability feel confident that they can now move to bear more risk. This pattern of setting goals & making pyramid impact their investment decision to focus on any particular securities at one point in time. So pyramid is a philosophy of segregating securities means looking at securities at their standalone basis, how much this security is offering return & risk. While standard finance proposes to look at from portfolio’s perspective means to look at the correlation of each security how it is adding risk or reducing risk on overall basis. Pyramid which is purely from behavioral finance looks at segregation of securities to meet investor needs while traditional finance approaches investment from diversification perspective. Pyramid is a strategy that allocates assets according to the relative safety and soundness of investments. The bottom of the pyramid comprises of low-risk investments, the mid-portion is composed of growth investments and the top is speculative investments.

The base (the widest part of the pyramid) would contain government bonds and money market securities, stocks would make up the middle of pyramid and then the top would be options and futures (speculative). Thus, the higher you go up the pyramid, the greater the risk and the potential return.

The investment mix may include investments from each level of the pyramid. However, the amount of each level depends on one’s personal financial situation. Future decisions based on your personal financial goals and realize there is always a trade-off between safety, income or growth.


The most important factor while making any investment decisions is risk involved in it and the return on the investment. If one has to choose between two given projects with the same return but different risks involved than obviously the project with minimum risk will be preferred. Some investors are risk averse and some are loss averse.

Develop a disciplined process to evaluate the level of risk involved in any investment you are contemplating, and determine if you think you will be adequately compensated for that risk. No one can consistently predict how markets will act, since investment types can perform differently under various market conditions, it's important for investors to have a variety of investments.

Risk tolerance will determine how much to put into each asset, since each asset has a different risk level. Cash is the safest and returns the least. Bonds offer income and preservation of capital, but have a bit more risk. Stocks over time offer the best return, but also more risk. The speculative investments such as real estate and commodities are the riskiest of investments.

Risk in behavioral finance has been defined in a different way as investor’s look at loss as probability of shortfall to meet the goals. Investor looks at risk on a standalone basis rather than from portfolio’s perspective where traditional finance recommends to aggregate the securities & their interaction between each other. As the probability of shortfall increases, the expected value required to meet goals decreases reflecting investor’s view towards risk & its impact on investment in any particular security.

Relationship between dependent and independent variables

Investment decisions are being affected by these behavioral traits, overconfidence makes investors to feel that whatever investment decisions they are taking will result in a positive return & hoping that they can beat the market. Overconfidence positively impacts investors decision to invest in any particular security as they have a tendency to believe that their investment decisions are accurate.

Regret is the attribute where investors try to hide their bad choices they made. Regret negatively impacts their investment decisions in a sense that when their forecasts go wrong they try to avoid reporting or showing loses as this will reflect their aviodence of admitting that they made mistakes. This regret factor makes them to hold those securities longer which will negatively impact their investment decision. Regret makes investors repent on their decisions made earlier & hold those securities negatively impacting their future investment decisions.

Pyramid approach is positively related to the investment decisions, the more sooner the lower levels of pyramids are satisfied (basic needs) the more sooner the investor will be ready to take some calculated investment decisions to move to those securities where he has not initially taken decisions to invest. Pyramiding also positively impact investment decisions to invest in those securities where he is able to meet the goals as set by the pyramid.

Risk impacts investment decision as investors treat the risk of probability of shortfall to meet the certain target set when investors make investment decisions. If investors are risk avers they will not take more investment decisions compared to investor who is less risk averse that aggressively make investment decisions to make more profit. Investors who look at investment as risk is the first area to make investment they will overanalyze the security impacting their investment decisions.


Hypothesis 1 (Variable Overconfidence)

Overconfidence positively impacts investment decisions

Hypothesis 01, to test the investor’s behavior towards the investment decisions that the investor having overconfidence in their capabilities tends to increase their investment activities. This variable from behavioral perspective impacts the investment decision that investors feel they have more information & ability to interpret information compared to others.

Hypothesis 2 (Variable Regret)

Regret negatively impacts investment decisions

Regret regarding investment decisions made earlier has negative impact in a sense that investors try to hide their bad choices made earlier; it also impacts future investment decisions of investors. This variable measures investor’s tendency to decrease investment once their forecasts & expectations do not meet with actual outcome of their investment. It measures how behavioral traits compared to traditional approaches have led investors to react to changes differently.

Hypothesis 3 (Variable Pyramid)

Pyramid impacts investment decisions

It measures how pyramiding recommended by behavioral finance approach impact the behavior of the investor to look at any investment opportunity. It measures the investor’s sentiments towards focusing on primary goals & accordingly makes investment to meet those goals. It measures how investor looks at investment on standalone basis as invest in those securities which are suitable to meet goals.

Hypothesis 4 (Variable Risk)

Risk impacts investment decisions

Behavioral finance looks at risk in a different way compared to traditional finance as investors define risk as a loss aversion rather than risk aversion. It measures how investors take decisions when investing based on the loss level. Some investors based on personality traits are trapped with tendency to look at risk as probability of shortfall which impacts their investment decision.

Research Methodology

Data Collection

The study is conducted in Karachi to understand how behavioral finance approaches impact the investment decisions taken by the investors & why investors deviate from the already taken decision. In order to run this study, data was collected from investors who are involved in making investments in stocks & bonds. Data is also collected from fund & portfolio managers who are making investments for their investors. Not only individual investors are exposed to these biases but also the institutional investors, fund & portfolio managers are exhibiting these biases in their investment decisions. The study is focused only on those investors who are investing in stocks & bonds so that we can administer their behavioral biases compared to model driven results.

Before data collection, we identified variables based on the previous researches so that these traits can be tested on investment decisions. As every human is different in traits, there are so many factors which can contribute to this study but we identified four factors & tested their relationship.

Data is collected through questionnaire from different investors without any information asking for amount of investment he has made as this may adversely affect the whole study as investors do not share this piece of information.

There are five variables, four independent & one dependent variable in this study. For one variable, we have set the thirty respondents so that we can mimic the population. For this study, we sent questionnaire to 150 investors.

Structured questionnaire was developed on Likert Scale with 5 as Strongly Agreed & 1 as Strongly Disagreed. One part was optional regarding the general information of the investor covering Name, Occupation & Contact Number, and Second part is of Demographics of the investors to understand their profile.

Two questions were regarding dependent variable (investment decision-restricted to stocks & bonds). Four questions are attached to each dependent variable to define that variable.

Overconfidence is measured with four different aspects

  1. Regret
  2. Pyramid
  3. Risk
  4. Selection of a Sampling

Conventional sampling technique (Non-probability Sampling method) was used in which sample of respondents was drawn from the target population. Sample size was fixed at 30 respondents per variable, as highlighted in theoretical framework there are five variables in our study, therefore, the study was conducted on one hundred fifty respondents. Results will be more accurate if study could be expanded to across country as cultural changes also impact the personality traits of the investors.

Research Design

Initially we conducted literature review to understand the behavioral finance approach towards investing. Through this process we found various traits or biases in personality of the investors & decided to take in our study only four variables as expanding the variables require more sophisticated & reliable methods to prove the results.

Quantitative Study is undertaken as we are measuring the impact of the specific group of investors investing in stock & bonds and residing in Karachi. Quantitative study will help to understand the relationship of variables & their impact to extract proper results & then utilizing those results to conclude the study.

Structured Questionnaires on likert rating scale were used as a tool of collecting the primary data from the investors who trade/invest in KSE as individual investors, mutual funds, portfolio managers, research analysts and investment analysts.

Data Analysis

The statistical tools that we used to analyze the data included Microsoft Excel and SPSS.


Increased trading

Q. 9 you feel that you have above average ability to interpret information better than others.

Strongly Agree Agree Neutral Disagree Strongly Disagree

Q. 10 your above average ability to pick investment means high return & low risk.

Strongly Agree Agree Neutral Disagree Strongly Disagree


Q. 11 you prefer to invest in those companies in which you are more aware of that company.

Price target revision

Q. 12 you set a price target for a security, when security price moves towards target, you revise original price target upward.


Loss aversion

Q. 13 when stock price goes down from purchase price, you hold it intending that it will recover.

Regret minimization

Q. 14. you sell a winning security, watching it going higher, you start thinking, “if only I had held litter longer” I would have profited more.

Money Illusion

Q. 15 you prefer high nominal returns even if inflation is low.

Rigid views

Q. 16 you stick to your old views despite the presence of new information in the market regarding security prices.


Q. 17 You try to meet your primary needs first & then secondary needs afterwards.

Q. 18 When you invest in a security, you always look at the risk side first to strive for financial stability.

Q. 19 when your primary needs are met you start investing in riskier investments

Q. 20 you invest in assets with a view to generate regular cash flows for basic needs by investing in those assets which gives regular income with low risk.


Risk aversion

Q. 21 you minimize risk for a given level of return or maximize return for a given level of risk.


Q. 22 you feel holding stocks in isolation is better able to manage risk.

Cautious Investor

Q. 23 you always over analyze investment opportunities, once taken decision, you stick to it.

Spontaneous Investors

Q. 24 Risk takes a back seat in your investment decision making, you always look for hot investments.


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Goetzmann, WN & Peles, N 1993, ‘Cognitive Dissonance and Mutual Fund Investors”, The Journal of Financial Research vol. 20, pp. 145-158.

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Mahajan, J 1992, ‘The Overconfidence Effect in Marketing Management Predictions’, Journal of Marketing Research, vol. 29, pp. 329-342.

Morton, H 1993, ‘The Story of Psychology’, New York, NY: Bantam Double Dell Publishing Group, Inc.

Ricciardi, V & Simon, H 2000, ‘What is Behavioral Finance’, Business, Education & Technology, vol. 2, pp.1-9

Shiller, R 2004, Human Behavior and the Efficiency of the Financial System, in: Taylor/Woodford ed., Handbook of Macroeconomics, 1999.

Shefrin, H 2000, Beyond Greed & Fear: understanding Behavioral Finance & the psychology of investing, Boston, Harvard Business school press.

Shefrin H & Thaler, R 1988, ‘Economic Inquiry’, The Behavioral Life Cycle Hypothesis, vol. 24, pp. 609-643.

Shefrin H & Statman, M 2000, ‘Behavioral Portfolio Theory’, Journal of Financial and Quantitative Analysis, vol. 35, pp. 127-151.

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Wood, A 1995, “Behavioral Finance and Decision Theory in Investment Management: an overview.” Charlottesville, VA: AIMR: 1.

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