ITÄ-SUOMEN YLIOPISTOYhteiskuntatieteiden ja kauppatieteiden tiedekuntaKauppatieteiden laitos

RESPONSIBILITY OVER INVESTMENT PORTFOLIO’S PERFORMANCE AND THE DISPOSITION EFFECT.

Pro gradu -tutkielma, Taloushallinto ja rahoitusSamuli Peura (250765)

ABSTRACTUNIVERSITY OF EASTERN FINLANDFaculty of Social Sciences and Business StudiesMaster’s Program in Accounting and Finance

PEURA, SAMULI U. I.: Responsibility over investment portfolio’s performance and the disposition effect. Master’s Thesis: 72 pp.Instructor: Professors Jyrki Niskanen and Markus Mättö May 2019

Keywords: Disposition effect, behavioral finance, prospect theory, regret, investor sophistication

Investors tend to prefer realizing stocks which have gained value instead of stocks which have lost value. This tendency is dubbed as the disposition effect and it is harmful for investors’ wealth. Past winning stocks have been shown to provide better returns on average than losers, and the reasons for holding on to losers remain unclear. This study asks, whether the disposition effect disappears, when stocks are not picked by investors themselves, as suggested in literature. A non-probability sample of 80 respondents took part in a questionnaire. The participants were asked to take control over an investment portfolio which they have inherited from a relative. The results suggest that investors without feeling responsibility over the investment portfolio’s performance do no exhibit the disposition effect. Different investor characteristics - investor sophistication, gender and education - were used as variables for further analysis of the effect. Unlike in the literature, more investment-wise sophisticated participants show a greater reluctance for loss realization and tend to cut their winners instead. Education does not seem to affect the tendency, but gender does. Men were found out to be more prone to the disposition effect. Providing straightforward causes for behavioral biases is difficult, yet it seems that disappointment in the poor performance of stocks is not enough for the disposition effect to arise. The results suggest that regret, or fear of feeling regret, is needed for investors to hold on to their losers.

TIIVISTELMÄITÄ-SUOMEN YLIOPISTO Yhteiskuntatieteiden ja kauppatieteiden tiedekuntaKauppatieteiden laitos Taloushallinto ja rahoitus

PEURA, SAMULI U. I.: Vastuu sijoitusportfolion tuottokehityksestä ja luovutusvaikutus.Pro gradu tutkielma: 72 s. Tutkielman ohjaajat: Prof. KTT Jyrki Niskanen ja KTT Markus Mättö Toukokuu 2019

Avainsanat: Luovutusvaikutus, käyttäytymistaloustiede, prospektiteoria, katumus, sijoittajan kokeneisuus

Sijoittajilla on taipumus realisoida osakkeita joiden arvo on noussut nopeammin, kuin osakkeita joiden arvo on laskenut. Tämä on todennäköisesti vahingollista sijoittajien varallisuudelle, sillä osakkeiden joiden arvo on viime aikoina noussut on havaittu tuottavan paremmin kuin osakkeiden joiden arvo on laskenut. Ilmiöön on vaikeaa löytää rationaalista syytä, eikä käyttäytymistaloustieteen kirjallisuudessa vallitse yksimielisyyttä irrationaalisistakaan syistä. Tässä tutkimuksessa selvitetään ovatko sijoittajat yhä taipuvaisia realisoimaan voitot ennen tappioita, jos he eivät ole itse valinneet osakkeita. 80 osallistujan näytettä pyydetään vastaamaan kyselylomakkeeseen, jossa he ovat perineet sijoitusportfolion. Heitä pyydetään tekemään halutessaan muutoksia portfolioon. Tuloksista käy ilmi, että vastaajat mieluummin realisoivat tappioitaan vallitsevan teorian mukaisesti. Vaikuttaa siltä, että sijoittajan tulee tuntea, tai pelätä, katumusta, jotta haluttomuus tappioiden realisointiin syntyisi. Tähän tutkimukseen vastanneet sijoittamiseen paremmin perehtyneet henkilöt ovat taipuvaisempia pitämään kiinni tappiollisista osakkeistaan ja myymään voitolliset vallitsevan teorian vastaisesti. Koulutustasolla itsessään ei ole merkitystä, mutta sukupuolella näyttää olevan.

TABLE OF CONTENTS

1 INTRODUCTION..................................................................................................................12 LITERATURE REVIEW.......................................................................................................5

2.1 Decision-making under risk..............................................................................................52.2 The Disposition Effect......................................................................................................6

2.2.1 Causes......................................................................................................................102.2.2 Outcomes.................................................................................................................27

2.3 Emotions.........................................................................................................................323 METHODOLOGY...............................................................................................................38

3.1 Research approach..........................................................................................................383.2 Questionnaire..................................................................................................................403.3 Data sample.....................................................................................................................433.4 Data analysis...................................................................................................................45

4 RESULTS.............................................................................................................................474.1 Investor sophistication....................................................................................................514.2 Gender and the disposition effect...................................................................................564.3 Education and the disposition effect...............................................................................58

5 CONCLUSION.....................................................................................................................606 REFERENCES.....................................................................................................................66

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1 INTRODUCTION

The foundations of traditional financial literature in the 20 th century have been laid on two

main assumptions. Markowitz (1952) created the modern portfolio theory (MPT). He explains

that by combining assets it is possible to create an efficient portfolio, a group of stocks and

assets, with the lowest possible risk for a given expected return. MPT argues that risk and

profit of investments should not be viewed individually, but in consideration of how they

affect the portfolio’s overall risk and return. The theory implies that investors take more risk

only if they are expecting a bigger reward. (Markowitz, 1952.) Another prevailing theory was

formulated by Fama in 1970. His theory of efficient markets, later referred as efficient market

hypothesis (EMH), states that all information about stocks have already been reflected to the

stocks’ price or market value. The theory implies that stocks are trading at their true value and

active traders cannot achieve superior returns that beat the entire market. (Fama, 1970.)

These foundational theories about stock markets and investing include an implication that

investors make rational decisions. It is assumed that investors update their beliefs about

investments correctly when they receive new information according to Bayes’ Law. Based on

updated beliefs, they “make choices that are normatively acceptable” as described in Savage’s

Subjective Expected Utility. (see Barberis & Thaler, 2003, 1053.) In short, the investors are

assumed to make decisions which maximize their wealth in markets, where the assets are

perfectly priced. These tenets, however, have been questioned since. More specifically, new

models have been found to work better when one, or some, of the aforementioned

assumptions of traditional finance have been relaxed. There have been times when investors

have not made fully rational decisions affecting the prices in the markets, and those events

have sparked interest for research. The actual behavior of investors deviating from the

traditional tenets was found out to be common and thus, behavioral finance was born.

Behavioral finance studies the effects of psychological, emotional and cultural elements on

individuals’ economic decisions.

Psychology forms a building block for behavioral finance, and it is in center of this thesis.

Allais’ (1953) paradox was a famous decision-making problem. It shows, that people are not

consistent with their choices regarding probabilities as forecasted in the expected utility

theory and challenged the paradigm. Consequently, it opened the field for a new way of

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research. Especially in experimental studies, it was found out to that people have certain

irrational behavioral biases in their investment decision-making. Overconfidence, wishful

thinking, representativeness, anchoring and availability bias are few common distortions in

people’s thinking patterns. In investing, these patterns do not lead investors to maximize their

wealth with the lowest risk possible. There are investors holding undiversified portfolios,

trading excessively or taking unnecessary risks. Acknowledging these common pitfalls is not

enough. Even experts, who most probably have at least heard of them, still have biases. The

experts might have different biases than amateurs, but still even they are not behaving fully

rational.

This thesis studies a behavioural bias called the disposition effect. It was first introduced by

Shefin and Statman (1985). A large amount of people take part in the stock market, but many

of them are found to be unsuccessful in it. One reason is that some people tend to get rid of

their good stocks and hang on to their bad ones. Barber and Odean (2011, 1534) put it this

way: “Unlike those in models, real investors tend to sell winning investments while holding

on to their losing investments - a behavior dubbed the ‘disposition effect’”. This effect is

shown in many research papers both experimental and empirical, revealing robust evidence of

investors’ disposition to sell winners and hold losers. Odean’s (1998) empirical research

shows investors realizing their winners 1,5 times more often than their losers. He also

presented evidence that past winners clearly outperform past losers on average. Investment

advices often indicate to cut the losing stocks and let the winning stocks run. In practice, this

recommendation doesn’t seem to take a grasp.

There is no consensus in the field why people sell their winning investments and hold on to

their losing ones. The literature about prospect theory (Kahneman & Tversky, 1979), mental

accounting (Thaler, 1980, 1985), regret aversion (Shefrin & Statman, 1985) in explaining the

disposition effect will be reviewed in the thesis, but the underlying cause remains unclear.

One of the reasons for the lack of explanation is probably that there are many reasons and the

reasons might be various for different people. Research also shows that the disposition effect

does not occur among all investors, at least in the same magnitude (Da Costa, et al. (2013).

However, experts neither are immune to it, so maybe some underlying features of the human

nature might lead us to be prone for such irrationality. In this thesis, some warring

explanations for the disposition effect will have a voice, but the layout of this research is

leaning towards emotions. This thesis will focus on the view that by making decisions, people

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commit to them. Emotions have been often neglected from especially traditional economic

models, but they do have an important role in decision-making under risk. People’s cognitive

evaluations of risk are not always in line with their emotional reaction to them (Loewenstein,

2000). The distinction might encourage behavior to deviate from fully rational economic

agent.

The aim of the thesis is to test theoretical implications presented by Duxbury and Summers

(2012) in a slightly different setting. They found out that people do not tend to sell their

winning stocks and hold on to the losing ones, when the stocks were not initially chosen by

them. Zeelenberg et al. (1998) have found out that that positive (negative) outcomes of events

infuse different positive (negative) emotions depending on the situation. Responsibility of an

outcome is a key feature. Bad weather on a day when there was supposed to be an outdoor

event makes a person feel disappointment, but an investment decision, which turned out to be

unprofitable makes him/her regret the decision he/she made. Zeelenberg et al. (1998) believe

that regret, or fear of feeling regret, is more difficult to process than disappointment and

might be set aside easier. Regret makes one feel a want to undo the events, and therefore, it is

needed for an investor to be reluctant to realize losses.

Humans need a better understanding of how emotions influence behavior and specifically

how they affect their choices. Lives are packed with different choices potentially influencing

dozens of coming years. That is why an understanding of the decision-making process and the

factors which have a strong impact in the choices we make is needed. Kahneman and Riepe

(1998) say: “The goal of learning about cognitive illusions and decision-making is to develop

the skill of recognizing situations in which a particular error is likely.” Thus, the goal here is

to raise awareness of a common investing pitfall and to provide insight for investors to make

better financial decisions. In this case, that is to ride on their winners and let their losers go.

The purpose of the thesis is to contribute to the literature about the underlying causes of the

disposition effect. This will be done by improving Duxbury and Summers’ (2012) study with

adding more risky assets into a similar questionnaire as the one they used. Also, instead of

studying a sample of mere undergraduates, more depth will be added by a non-probability

sample gathered from an internet questionnaire. An investment portfolio with six stocks

inherited from a relative will be presented to the participants. The stocks have had different

past returns and the participants will be asked to organize the portfolio in the way they want.

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The inheritance removes the possible emotional commitment to the stocks, and according to

theory, will not incur the disposition effect. The questionnaire results will be analyzed by

using tested reliable measures of the disposition effect. The results will be further compared

between investor groups of different education level, investing sophistication and gender. The

focus is on the investment sophistication, because according to the literature gender and

education do not have a clear impact. This study asks whether there is a disposition effect, if

the investors have not committed to the stocks by making the investment decision themselves.

The main questions in this thesis are:

1. Do the investors exhibit the disposition effect, if they have not chosen the stock

themselves?

2. Does higher investor sophistication mitigate the disposition effect in these conditions?

After this introduction, the literature considering the disposition effect will be reviewed.

Following the literature review, in the methodology part, the questionnaire, sampling and the

methods used in the results section will be presented. Next section gathers together the

answers of the questionnaire and analyzes the disposition effect exhibited. The last chapter,

conclusion, gathers together the key findings, compares them with literature presented and

discusses the deductions.

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2 LITERATURE REVIEW

This chapter presents the theoretical background for this thesis. First, we will take a short look

on cognitive biases in decision-making. From the broader view, we will move on to the

disposition effect. The term, disposition effect, will be defined and shown, how it has been

proved both empirically and experimentally. Then, we will focus on the possible reasons

which causes the disposition effect. The most famous psychological explanations, including

the prospect theory, mental accounting and loss aversion, will be discussed. The question,

why studying the disposition effect is important, will be answered by showing what it induces

for individuals, as well as markets. The explanations, which lead to disposition effect have

their own challenges, either in robustness or generalizability, which motivates to dig deeper in

to the emotional sphere of the disposition effect. Through fMRI brain scanning, researchers

have proved that people derive utility not only from consumption, but also from realization.

Lastly, the literature regarding emotions in investing and decision-making will be analyzed.

The theoretical implications surrounding emotions serves as the background for the design of

this thesis’s research methods.

2.1 Cognitive biases in decision-making

In our daily lives we humans face a massive number of different situations where we have to

make decisions. Most of the decisions are simple and are processed in the brain almost

automatically. An example of an automatic decision is whether to accelerate or brake when

driving a car. On the other hand, some of the decisions are complicated involving many

variables, different choices, probabilities and possible outcomes. Tversky and Kahneman

(1974) show that “people rely on a limited number of heuristic principles which reduce the

complex tasks of assessing probabilities and predicting values to simpler judgmental

operations.” Sometimes these heuristics are useful and especially make our lives simpler and

more fluent, but sometimes they also lead to systematic errors in terms of rational decision

making. (Kahneman & Tversky, 1974.) Investor behavior research combines topics of

psychology and investing. Of interest in this thesis are psychological aspects affecting

decision-making, and especially how it makes us to deviate from rational behavior.

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Sometimes it is difficult for us to see “the bigger picture”. Markowitz (1959) states that

humans understand outcomes as gains and losses, rather than as changes in the states of

wealth and welfare. This leads humans to evaluate events separately from each other.

Consider the following example. A poverty-stricken person wins 20 euros from a lottery, or

he/she gets two extra hours from work and earns 20 euros more than normally. In which

situation it is more likely that the person spends the money in unnecessary things, for example

a beer and a pizza? Because that lottery money is in some sense extra money, it is easier to

spend in things we actually don’t need. With that being said, neither the causes and outcomes

of actions and decisions are always fully clear for us. As Duxbury and Summers (2012) put it:

“In most real-world situations an investor will choose which stocks to hold, and may feel that

these choices are guided by their expertise and experience”. But psychological research has

shown that there are many different variables intercepting our decision-making than our

perceived expertise. In Goetzmann et al. (2016) it is shown that according to historical data,

the probability for a strong stock market price meltdown in a single day is low. However,

their survey of individual and institutional investors, reveal that the beliefs of investors are not

consistent with that. According to them, an availability bias highlighted by media induces

investors to set their beliefs about the crash irrationally high. This is just one example of a

cognitive bias, a heuristic, used in humans thought processes. These biases lead us sometimes

to err in terms of rational decision-making. The next chapter will introduce the disposition

effect as an example of sub-optimal decision-making, alongside a discussion about cognitive

biases which might lead to it.

2.2 The Disposition Effect

This thesis concentrates on the phenomena called the disposition effect, which was first

introduced by this name by Shefrin and Statman in 1985. The section 2.2 aims to shed light

on the research what is meant by the disposition effect. Also relating academic research,

which lead to believe there is such an effect and the possible reasons causing it will be

introduced.

According to Shefrin and Statman (1985), the disposition effect refers to the investors’

tendency to sell winners too early and ride losers too long. By winners they mean stocks

which have risen in value and losers are referring to stocks which have lost value. The

expressions “too long” and “too early” derives from the comparison to Constantinides’ (1984)

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optimal stock trading strategy theory. Constantinides’ (1984) theory is backed up with tax

considerations which suggest that losses should be realized while they are short-term, while

gains should be realized only when they are long-term. Shefrin and Statman (1985) still find

in their study that: “the disposition to sell winners too early and ride losers too long operates

in the opposite direction”. Barber and Odean (2011, 1557) add that even though taxes have an

effect on the trading of individual investors, the disposition effect cannot be explained with

only taxes. They claim that if taxes are considered rationally, investors should continue to

hold their profitable investments. So, the reasons for disposition effect must lie down

somewhere else.

In the study of Shefrin and Statman (1985), the disposition effect is revealed by people’s

behavior in realizing gains and losses in taxable investments. Their behavior is compared to

assumed rational behavior presented by Constantinides (1984), how the investments should be

realized that it makes sense if they paid attention to tax consequences. Odean (1998) studied

the disposition effect by analyzing trading records from 1987 through 1993 for 10000

accounts at a large discount brokerage house. The accounts were chosen randomly to the

study by the criteria that they had at least one transaction in the year 1987. The data Odean

used consists of two sets: the first has 162,948 records and contains the corresponding

account’s identifier, the trade date, identifier for a security traded, a buy-sell indicator, the

quantity traded, the commission paid and the principal amount. The second set of the data

embodies monthly positions’ information for the 10000 accounts from the research period.

The author points also out that the data set may have some bias in favor of more successful

investors, since the accounts which were closed during the research period were not replaced.

(Odean, 1998.)

Odean (1998) assumes that in his research period, there was an upward-moving market. This

may lead to mistakenly believe that investors sell more winners than losers without having a

preference to do so since most of the securities traded in overall are winners. He aims to

remove this possible effect by concentrating at the frequency with which the investors sell

winners and losers relative to their opportunities to sell each of them. The formula the author

uses to find out this phenomenon is presented next in the equation (1). (Odean, 1998.)

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Equation (1), Odean (1998, 1782):

The equation (1) introduces realized gains and realized losses, and paper gains and paper

losses. The term realized gains stands for all the stocks an investor sold for a higher price than

she initially bought them. Realized losses then stands for all the assets the investor sold for a

lower price than she initially acquired them. Paper gains represents the shares bought by the

investor which have increased in value but are not sold yet. Paper losses then depicts stocks

which have lost value and not sold yet. Odean (1998) then points out that: “A large difference

in the proportion of gains realized (PGR) and the proportion of losses realized (PLR) indicates

that investors are more willing to realize either gains or losses.” (Odean, 1998.)

In Odean’s (1998) data set commissions are included and they are deducted from the sales

price. Dividends are not included, because they don’t affect capital gains and losses for tax

purposes. Tax considerations are the normative standard to which the disposition effect is

being contrasted in his study. The study has two hypotheses. First hypothesis states that the

proportion of gains realized (PGR) is bigger than the proportion of losses realized (PLR) for

the entire year. The second hypothesis claims that the subtraction of the PGR from the PLR is

bigger in December than in other times of the year. Odean (1998) uses various ways to test

these hypotheses; he considers the size of the portfolio the investors hold, he calculates the

proportions using monetary amounts of gains and losses and calculates PGR and PLR for

each account instead of the whole market. Still after these careful examinations, he finds out

that both hypothesis stands with a high degree of statistical significance. Odean (1998) states:

“The ratio of PGR to PLR for the entire year is a little over 1.5, indicating that a stock that is

up in value is more than 50 percent more likely to be sold from day to day than a stock that is

down”. Grinblatt and Keloharju (2001) critizes Odean (1998) of that he does not measure if

the realization of large proportion of losses compared to gains are caused really by the

disposition effect, or for example contrarian beliefs of the investors.

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Weber and Camerer (1998) have also replicated similar results in an experimental analysis.

They provided 6 risky assets for investors. The chances for the assets’ value to rise was given,

one value for each asset, but it was not determined which stock had which chances. The

stocks were not given real names, rather they were called Stocks A-F. The aim was also to test

theories of portfolio selection in addition to the disposition effect. The experiment itself was

carried out in 14 periods and stocks’ prices changed in each. The authors claim that investors

behaving rationally would have inferred the trends of the stocks after 8 periods, and would

have stayed with the winners since, and get rid of losers. They say that: “Our data show a

disposition effect: subjects tend to sell fewer shares when the price falls than when it rises.

They also sell less when the price is below the purchase price than when it is above.” Weber

and Camerer (1998) believe that the reasons for this behavior is explained in the prospect

theory. (Weber & Camerer, 1998.)

Grinblatt and Keloharju (2001) monitor the trading, buys, sells and holds, of individuals and

institutions in the Finnish stock market. The underlying question was to find out why

investors trade so much. Like in Odean (1998), investors trade until they lose money already

before transaction costs. What Grinblatt and Keloharju (2001) tries to add to for example

Odean (1998) and Shapira and Venezia (1998), that they aim to understand how traders

“behave in equilibrium” to find out the differences and similarities between market

participants. Also, Grinblatt and Keloharju (2001) bring the differentiation between contrarian

beliefs and the disposition effect (i.e. selling/holding due to capital gains/losses) to the table.

They manage that “by controlling for both the stock’s pattern of past returns and the size of

the holding-period capital loss” (Grinblatt & Keloharju, 2001.)

Grinblatt and Keloharju’s (2001) data set was remarkable because it had all Finnish investors,

both individual and institutional, and also includes investor attributes in detail. The two main

reasons for selling a stock which the investor owns are tax-loss selling and the disposition

effect. The hold on the losers is particularly strong when to losses exceed 30 percent and

monthly highs and short-term large positive returns are the triggers for selling. In addition to

monthly highs bringing the sells on the table, also the lows give a birth to contrarian beliefs.

They are especially strong for the household, government and nonprofit institution investors

groups. This is an example, that the past returns’ influence on the trading decisions is

complicated by equilibrium limitations (Grinblatt & Keloharju, 2001.)

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Lee, et al. (2008) study the disposition effect in virtual marketplaces, i.e. electronic trading

platforms in websites. They claim that the nature of e-trading is faster, stocks are bought and

sold more quickly. The websites also contain information about stock and market trends,

financial statements of the companies, market news et cetera. In an experimental analysis,

Lee, et. Al. (2008) found clear evidence for the disposition effect. The average holding period

of winning stocks was 3.95 days whereas for losers it was 6.21 days. The difference in the

lengths of the holding periods between losers and winners was relatively bigger than in Odean

(1998), but there the holding period is matter of months, not days.

There are numerous academic studies showing the irrational behavior described as the

disposition effect. Researchers have given evidence about it both experimentally (e.g. Weber

& Camerer, 1998; Chui, 2001; Oehler, et al., 2002) and empirically (e.g. Odean, 1998;

Grinblatt & Keloharju, 2001; Shapira & Venezia, 2001; Coval & Shumway, 2005; Dhar &

Zhu, 2006, El-Khari, 1995, amongst others). Barber, et al. (2007) for example find that 84

percent of the Taiwanese investors are prone to the disposition effect. They studied 4 million

individuals trading over one billion trades, and find individuals, corporations and dealers

selling their gains more eagerly than losses. Only mutual funds and foreigners don’t show this

behavior. However, Henderson (2011) has found that investors will finally sell after the asset

has reached low Sharpe ratio enough.

2.2.1 Causes

The investors make trading decisions based on various reasons: for example, they have beliefs

about the future of the stocks, they might react to gains and losses, a goal set by them may

have been reached or they want to rebalance their investment portfolio to match their

preferences and risk tolerance. The reason causing people to sell their profitable investments

and conversely holding on to their unsuccessful ones are not well understood. Kahneman and

Tversky’s (1979) research gained popularity among the scientific field in explaining the

disposition effect but after all that too, has been questioned since. It is evident that the

behaviour shown in the research of the disposition effect is harmful for investors in the stock

market. In despite of the vast amount of research and robustness of the evidence, the tendency

to sell winning stocks and holding the losing ones is still visible. That is why it is important to

dive deep in to the reasons causing the tendency. By fully understanding the details of the

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underlying causes it is possible to help investors to tackle the irrational behaviour and make

better decisions.

It is not an easy task to make robust conclusions about investor behavior. The seemingly

irrational trading behavior of investors might be in some cases actually rational, or the

triumph of gain realization over loss realization can have other reasons than a general

tendency. Some investors believe in mean-reversion, i.e. that the stocks which have lost value

will after all turn the tides and end up being a winner soon. It is also difficult to distinguish

which trades are motivated by tax reasons, or perhaps seasonal momentum strategies. In this

chapter the goal is to go through the existing research about how to spot the disposition effect

among other factors affecting investor behavior.

Lakonishok and Smidt (1986) discuss and analyse the motives for stock trading. They claim

that investors might sell winners and stick to losers due to tax-related reasons or to keep their

portfolios balanced. There is a consensus about how losses in trading should be treated, but

the optimal strategy for gains is not clear. Taxation offers a motivation to realize losses before

they are held over a year, because taxes are settled annually. Based on the tax-motivated

assumptions to realize losses, the authors draw a connection to increased volume in stocks,

which prices have decreased. Especially short-term losers should show a clear spike in the

trading volume. Winners’ volume, in contrast, should rise in the first months of them

becoming long-term. Lakonishok and Schmidt’s (1986) results, however, are not in line with

above discussions. They find evidence that winners tend to have higher volume than losers.

Also, they conclude that: “We find clear evidence that tax incentives influence trading

volume, although they are not the predominant influence.” The reasons for higher trading

volume amongst winners remain unclear. (Lakonishok & Smidt, 1986.)

Odean (1998) studies the rebalancing of portfolios by selling winners. Rebalancing might

offer a reason to sell a portion of the holding of a winner, but a complete realization “is most

likely not motivated by the desire to rebalance”. After removing these partial sales in his

calculations, he still finds a tendency to sell winners and hold losers. So debunking the

rebalancing of portfolios in explaining the disposition effect. Odean (1998) also considers the

possibility that investors might hold on to losers due to belief that they will outperform

winners in the future. This might explain the reasons for described trading behaviour, but the

belief has been clearly proven false by him (1998) and for example Jegadeesh and Titman

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(1993). The difficulties for these hypotheses to explain the disposition effect has turned the

attention to Kahneman and Tversky’s (1979) prospect theory, which will be reviewed next.

2.2.1.1 The prospect Theory

Kahneman and Tversky (1979) present a theory called “the prospect theory”, where they

show people defining gains and losses in relation to a reference point. Its goal is to forecast

behavior and it tries to correct the expected utility theory. Every decision-maker has their own

reference point, which value can change over time. The actual amount of gains and losses is

then compared to the reference point. The reference point’s value is connected to the decision

maker’s own expectations and can also be affected by the presentation of the possible options

in the decision-making situation. The reference point in investing is usually connected to the

purchase price of the stock. (Kahneman & Tversky, 1979.)

In the prospect theory, Kahneman and Tversky (1979) coin a term value function. It tries to

explain the psychological value of events and objects to humans. Standard economic theory

assumes, that a gift, salary increasement or lottery win of 200 euros increases the wealth of a

consumer by 200 euros, and its value for the consumer is always the same. Value function

tries to replace or improve the standard economic theory of a consumer by changing the idea

of that economic value. It tries to achieve its goal by changing the attention of the formula to

changes in wealth, rather than the overall value of wealth hold by person after the changes.

The psychological value of 200 euros is probably different for a homeless person, and a CEO

of big multinational company.

According to Kahneman and Tversky (1979), people do not resonate to the actual final state

of wealth, but perceive changes in wealth either negative or positive. The reference point and

the magnitude of change are the variables that matter. Kahneman and Tversky (1979) say that:

“the same level of wealth may imply abject poverty for one person and great riches for

another – depending on their current assets.” They conclude that personal value of events for

an individual is useful to be considered as a mix of two variables: the reference point and the

amount and direction of the change from the reference point. Kahneman and Tversky (1979)

state that: “Many sensory and perceptual dimensions share the property that the psychological

response is a concave function of the magnitude of physical change.” The authors propose

that this is especially true for monetary situations and it is best described by examples.

13

Kahneman and Tversky argue that adding 200 euros to the initial wealth of 200 euros, so

making it 400 euros, has a clearly bigger effect on the subject than if he had 1100 euros in the

beginning and ended up with 1300 euros. That example shows that the value of 200 euros can

be perceived differently depending on the situation, i.e. reference point. The hypothetical

value function will be shown in the next figure (1). (Kahneman & Tversky, 1979.)

Figure (1): A hypothetical value function presented by Kahneman & Tversky (1979),

“Prospect Theory: An Analysis of Decision under risk, p. 279”

The value function (figure (1) is S-shaped and is steepest at the reference point, which is

where the three lines meet in the figure (1). The value function aims to replace or improve the

standard economic theory of consumer in the event of decision-making. What is notable in the

value function, is that it gives credit to deviations from the reference point, rather than the

states of final wealth. It is concave for gains and convex for losses and it is steeper for losses

than for gains. (Kahneman & Tversky, 1979.) Thaler (1985) adds that the introduction of the

reference point in the value function allows framing of choices to influence choices of an

individual. By framing of choices, he means how the choices are presented, suggesting that

the value of events is not clear for the individual itself. Thaler (1980) has also shows that

losses have more powerful effect than the equivalent amount of gains for humans, an effect he

calls the endowment effect. He presents an example that people will not pay the same amount

for an item to acquire it, than they would ask for it as a vendor.

14

The prospect theory has been prevailing in explaining the disposition effect seen in the stock

markets. The reference point in the value function is assumed to be the purchase price of the

stocks, and the psychological value of the stock’s price movements for investors are thought

to follow the S-shaped line presented in the figure (1). The difference how people react to

gains and losses might cause people to seek more risk in the domain of losses and be more

risk averse in gains. This risk-tolerance difference might make people afraid of losing their

already achieved gains, and willing to take more risk after losses hoping that they will break-

even in the future.

Kaustia (2004) amongst other researchers however cast a shadow on the prospect theory in

explaining the disposition effect. He questions the nature of the reference price. He argues

that Kahneman and Tversky (1979) don’t specify what the reference price is, and considers

static settings, where the current asset price serves as a reference price. Barberis and Xiong

(2009) model explains that the prospect theory predicts the disposition effect “more reliably”

in the case of realized gains and losses, but not so well annual gains and losses. The failure of

the co-operation of the two theories (prospect theory and the disposition effect) in explaining

the behavior of an investor facing annual gains and losses will be analyzed in detail next.

Barberis and Xiong (2009) model the trading behavior of an investor with the prospect

theory’s preferences. They argue that the prospect theory does not always predict the

disposition effect. The evidence they provide for their claims will be presented in the next

figure (2) and will be discussed below. The figure (2) is created by Barberis and Xiong (2009)

on the foundations of Kahneman and Tversky’s (1992) S-shaped value function. (Barberis &

Xiong, 2009)

15

Figure (2): An example in which prospect theory fails to predict a disposition effect presented

by Barberis & Xiong (2009), p. 767.

The figure (2) shown by Barberis and Xiong (2009) is an example in which the prospect

theory fails to predict the disposition effect. They emphasize that their logic is only proving

disposition effect unexplainable by prospect theory for short time periods, like the two-year

time span used in the following example. In the figure (2) there are three dates and the

interval between them is one year, i.e. the dates are from year 0 to year 2. The possible gains

and losses of the investor are then marked with letters A, B, C, D, B’ and D’. (Barberis &

Xiong, 2009.)

The investors start from B on the date 0. If the stock performs well at time 1, the investor

moves to A. Then his optimal strategy is to gamble to the edge of the concave region: If the

stock does well at time 2, he moves to point B’ and if the stock does poorly at time 2, he

moves to point B. If the stock on the other hand yields a loss at time 1, the investor will move

to C. At that time, his optimal strategy is to gamble to the edge of the convex region: If the

16

stock yields a gain at time 2, he moves to point D’ and if the stock yields a loss, he will move

to point D. The prospect theory assumes that the investor is loss-averse, and so the expected

return on the stock needs to be reasonably high for him/her to buy it in the first place at time

0. The point A is therefore further from the vertical axis than C, which means that the investor

needs more gains to get the same amount of positive utility compared to the negative utility

yielded by an equivalent amount of losses. (Barberis & Xiong, 2009.)

According to Barberis and Xiong (2009), it takes a larger share allocation to gamble from A

to the edge of the concave region than from C to the edge of the convex region. Thus, the

authors conclude, the investor, if following the rules of the prospect theory, wants to sell the

stock after a loss. That violates the theory of the disposition effect. Also, they argue that the

prospect theory in explaining the disposition effect is flawed, because the value function is

only mildly concave in the region of gains. For that reason, Barberis and Xiong (2009) states:

“the only reason an investor would take a small position in the stock after a gain is if the

expected stock return were unattractive, in other words, if it were only slightly higher than the

risk-free rate. In this case, the investor would not have bought the stock at time 0.” In the end

of their discussion, they however admit that this interpretation of the prospect theory works

only in short time spans. A longer time span then lowers the investors’ initial risk aversion

and would be open to buy the stock at time 0 even with only a slightly better expected return

than the risk-free rate. This leaves also a possibility for the prospect theory to explain investor

behavior. (Barberis & Xiong, 2009.)

Kaustia (2010) also contradicts that the prospect theory has only a preference-based

explanation for the disposition effect. The implications that the purchase price serves as a

reference point and the investors become more risk-averse after seeing gains and risk-seeking

after losses leads to investors’ reluctance to sell the stock whether the price moves up, or

down. The author finds in his data, that investors in Finland show a significant higher

propensity to sell at zero capital gains on less than a three-year period. (Kaustia, 2010.) Hens

and Vlcek’s (2011) model questions whether investors with prospect theory preferences

would even buy stocks in the first place. They claim that the prospect theory in explaining the

disposition effect is an ex-post argument. As they say it: “An investor who weights outcomes

with the decisions weights as proposed by Tversky and Kahneman (1992) and who is quite

risk averse in the domain of gains and quite risk-seeking in the domain of losses never invests

in the risky asset in t = 0 implying that he is not prone to the disposition effect”. In the

17

standard argument of the prospect theory explaining the disposition effect, it is assumed that

the investor has already acquired the stock. Hens and Vlcek (2011) question the logic of this

argument, by pointing out that the argument does not really reason if the agent will really

behave in this way. They assume that the true disposition effect derives from backward

looking optimization and the use of mental accounts. Mental accounting is a term coined by

Thaler (1985), and it will be explained in the next section.

Lee, et al. (2008) however, support the value function in explaining the disposition effect. In

their study about disposition effect in e-trading, they find that: “a task that required

assumption of a linear relationship between outcomes and subjective values assigned to them

completely eliminated the disposition effect”. They claim that this proves that the disposition

effect was not risen in their experimental setting due to subjective beliefs about future price

changes. In their opinion, based on this task eliminating the effect, the disposition effect arises

from “differences in the values they assigned to future gains and losses for winners versus

losers”. The disposition effect was also found to be vanished when participants made buying

and selling decisions on behalf of another person, further backing up the value function

explanation. Lee, et. Al. (2008) still admit, that the value function explanation is not

excluding other possible factors affecting the people to exhibit the disposition effect at least in

addition to the different attitudes towards gains and losses. Their results promote using an

investment agent to handle investing but call for future research on the conditions when also

the professionals show the disposition effect.

In this chapter the most famous and popular explanation for the disposition effect, the

prospect theory, was introduced. In the theory, people’s irrational behavior in the stock

markets, in this case a harmful treatment of gains and losses, is validated by their different

psychological valuations of positive and negative monetary amounts. This explanation is too

simple for some researchers, and has raised questions, arguments and needs for other

explanations for the robustly evident phenomena. In the following chapters different theories

are reviewed with the goal to find the ground of the disposition effect in mind.

2.1.1.2 Mental Accounting

Thaler (1985) introduces a theoretical model called mental accounting to replace the standard

economic theory of the consumer. According to Thaler (1985): “standard (economic) theory’s

paradigm is to first characterize the solution to some problem, and then to assume the relevant

18

agents act accordingly”. In his opinion, the mental accounting system causes humans to break

a simple economic tenet. In the next equations (2 and 3) will be presented the standard

economic theory of the consumer as presented by Thaler (1985). Afterwards his corrections to

the formula will be presented and discussed.

max

z¿u ( z )

¿ (2)

s .t .∑ pi zi≤ I (3)

Equations (2 and 3): The standard economic theory of the consumer presented by Thaler,

(1985), p. 200.

The equations (2 and 3) explains the decision-making process as presented in the standard

economic theory of the consumer. In the equations (2 and 3) U represents the consumer’s

utility, p marks the prices for goods and z stands for the goods available in the economy. The

outcome of the formula is I, which stands for the consumer’s wealth. All in all, the formula

represents how the consumer’s decisions in choosing the right amount of goods available for

the offered price leads to his maximized wealth. Thaler (1985) aims to revise the value

function to depict how consumers behave in real world. First, he replaces the formula’s utility

function with the value function presented by Kahneman and Tversky (1979). Second, Thaler

(1985) corrects the formula by introducing the reference price directly into the value function.

Third, the principle of fungibility is relaxed, meaning that wealth can be described in other

terms than those presented in the standard economic theory. The aim is to add a behavioral

aspect to the theory of consumer choice. The revised function provides a concept of

transaction utility which refers that people derive utility also from transactions itself and not

only from consumption. (Thaler, 1985.)

Richard Thaler (1985) presents also experimental evidence on mental accounting calling the

phenomena segregation and integration. He suggests that multiple gains are psychologically

better to face segregated, and not fixed together, in other words it is nicer to win 20 euros

twice, than 40 euros once. Multiple losses on the contrary are psychologically easier to face

integrated, for example paying only one credit card bill instead of paying every price

separately. In a situation of mixed gains and losses when there is a net gain people tend to

19

prefer integration, sparing themselves of seeing the losses. Receiving mixed gains and losses

resulting a net loss is more complicated. That is situational, and depends on the actual

amounts; for example ending up greatly at loss segregation is preferred, but if the amounts are

close to each other, integration is probably preferred. (Thaler, 1985.)

Thaler’s (1985) research contains a sample of 87 undergraduate students in a statistics class at

Cornell University. He presented the students 4 questions introducing Mr. A and Mr. B. In the

examples both received either costs or gains in a surprising way, but the monetary amounts of

each imaginary persons were in the same as the matter of actual final state. For example, in

one exercise Mr. A won 50 dollars from one lottery ticket and 25 dollars from another lottery

ticket. Mr. B then, won 75 dollars from a single ticket. After presenting 4 scenarios like this,

he asked the participants questions like: “Who was happier, Mr. A or Mr. B?” In all of the

four exercises the participants were behaving in a manner predicted by his theory. In this

particular question, 56 of the 87 participants thought that Mr A is happier and only 15 thought

that there is no difference. Thaler (1999) concludes that “Mental accounting is the set of

cognitive operations used by individuals and households to organize, evaluate and keep track

of financial activities.” Accounting systems in organizations have clear rules of tracking the

gains and losses, but unfortunately humans don’t have a similar structure built in them.

Mental accounting is trying to describe the psychology of choice. According to Richard

Thaler in mental accounting “money in one mental account is not a perfect substitute for

money in another account”. That violates the fungibility of money and leads to irrational

behavior. (Thaler, 1985, 1999.)

Paper gains and losses are key terms in this thesis. If a stock has made loss in the investors’

portfolio, the regret and pain of selling the stock, i.e. closing the mental account for that stock,

is still yet to be realized. Only when the stock is sold and the corresponding mental account is

closed, the regret of accepting and admitting a wrong decision must be experienced. The

knowledge and anticipation of such a painful event may paralyze the investor and keep her

from changing it to more profitable investments. Kaustia’s (2010) data shows a tendency to

sell at zero capital gains. This is consistent with the will to avoid closing mental accounts at a

loss. The investor might be searching for the highest utility by realizing a successful

investment decision and letting losses untouchable. By keeping the negative outcome as a

paper loss, he keeps the pain of failure lower compared to realized losses. The advantage of

using two mental accounts, one for realized gains and losses and the other for paper gains and

20

losses, is that the stocks in the paper account have far lower effect than the realized account.

This allows a psychological trick to maximize the utility. (Hens & Vlcek, 2011.)

A mental accounting system, keeping track of gains and losses separately on different

“accounts” in one’s mind, might take the pride of generating the disposition effect. Positive

and negative outcomes of stock’s performance, triggering emotions seems a perfect setting for

taking immediate rewards, while ignoring the painful equivalents of admitting one’s

incapability in decision-making. While the emotional system of human beings initially

motivates profitable behavior, which in reality includes cutting losses, at the same time it may

easily deceive itself by aiming to thrive in the short term on behalf of the long.term success.

2.2.1.3 The Pain of Losses and the Pleasure of Gains

A very common cause offered for the disposition effect is loss aversion. This is at least

discussed in Shefrin and Statman (1984), Odean (1998), Lakoniskoh and Smidt (1986),

Grinblatt and Keloharju (2001), Shapira and Venezia (2001), Muermann and Volkmann

(2006) and Dhar and Zhu (2006). Loss aversion is connected to Kahneman and Tversky’s

(1979) prospect theory. Above in the prospect theory section, it is shown that a part of the

literature doubts the prospect theory explanation for the disposition effect. The biggest

concern about the explanation is that it considering investment decisions in a static setting. In

reality investing is dynamic, decisions and price movements are happening constantly in

continuity.

Benartzi and Thaler (1995) coin a term myopic loss aversion. They pose a question, why

would anyone hold treasury bills or bonds because stocks have provided 7 times larger profit

since 1926. They explain that in Kahneman and Tversky’s (1991) prospect theory, the utility

function suddenly jumps at the origin; going down the loss side is steeper than going up the

gain side with a ratio of two. In other words, the pleasure of gaining something is half great

compared to the pain of losing it. Benartzi and Thaler (1995) also show that as the holding

time period grows longer, the more willing to take risk the investors get. From that point they

derive the connection to loss aversion and so coin it as myopic loss aversion. And the more

risk seeking the investors are after seeing their losses run, the more reluctant they will be in

cutting the losses.

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Two main emotions related to investing are pride and regret. Lee, et al. (2012) claims that

regret originates in counterfactual thinking and is caused by the clash of obtained outcome

and what could have happened. Further, pride is a positive emotion experienced after

successful effort or abilities. In investing, winning stocks are connected with pride and losing

stocks are connected with regret. In the financial decision-making setting, there are also two

varieties of these above-mentioned emotions: anticipated regret and anticipated pride. The

original emotions, pride and regret, are experienced after realization of gain or loss. The

anticipated versions of the emotions are in play when gains and losses are still on paper.

According to Shefrin and Statman (1985) this anticipation of emotions may cause the

disposition effect.

Duxbury and Summers (2012) claim that unclear future and especially the unknown

movements of the stock’s price enables optimistic beliefs of the stock’s future situation.

Beliefs and hopes then open the way for emotions. Muermann and Volkamm (2006) assume

that people are more concerned about regret than they are about pride. In their study with a

dynamic setting, they find that anticipated regret and pride can help in explaining the

disposition effect. What if it is regret aversion instead of loss aversion?

2.2.1.4 Self-control

Thaler and Shefrin (1981) introduce an economic theory of self-control. They present

individuals to be both a farsighted “planner” and a myopic “doer”. This multi-self sets

constraints on its own behavior and is in conflict, because “doers” are selfish. The authors

claim that a person, who has a salary of 1000 euros each month and a 2000 euros bonus once

a year, will save more annually than a person who receives 1200 euros every month. The

salary without a bonus needs more complex self-controlling saving plans and the “doer” will

interfere in this. Shefrin and Staman (1985) offer lack of self-control as an explanation for the

disposition effect. They assume that the investors’ “planner”-side is not strong enough to

control the “doer”. The latter wants to keep on riding losing stocks, not causing a negative

emotion, and selling winning stocks, causing a positive emotion. Professional traders use

personal rules and stop-loss orders to avoid this kind of behavior. This is suggested by Brown,

et al. (2006) results also. They find that the disposition effect tends to decrease in the larger

investments. Maybe it is a cause of investors putting more effort and additional self-control to

22

larger investments and thereby becoming able to resist the “doer” side of pursuing for easy

emotional rewards.

Self-control theory seems to be working well especially with mental accounting in explaining

the disposition effect. It is not surprising that the average human-being lacks self-control, how

else would be many harmful temptations so popular? However, Duxbury and Summers

(2012) state that in revealing the reasons of disposition effect, self-control deficit is to be seen

secondary and that is only needed in the situation where investors show a reluctance to act. In

the case of the disposition effect this reluctance means selling of losing stocks. In their

opinion the question is, where does this tendency to keep the losers come from. Duxbury and

Summers (2012) seem to hit the right tone asking about the origin of the tendency. That is

what is truly needed to find out to tackle the disposition effect scientifically, as well as

practically. Their doubt, on the other hand, is also not watertight, since seemingly self-control

is needed also in resisting the hunt for positive outcomes.

The problem with both theories, self-control and mental accounting, is their testability. It is

fairly difficult to come up with an efficient and trustworthy examination of these two

psychological propensities. A questionnaire of investor’s feelings about their decisions

retrospectively is probably not the most precise tack, neither it is easy to spot these biases by

analyzing a data set of trading decisions consisting only of numbers. Therefore, there is a need

to truly detect what conditions are enough to bring about the disposition effect.

2.1.1.5 Investor Characteristics

Investors are a heterogeneous group. The differences in investors’ trading styles and beliefs

(e.g. Goetzmann & Massa, (2002) and Dhar & Kumar, (2002)) raises questions, that is the

aggregated mean value of the disposition effect in the stock markets the right way to approach

these questions about investor biases. Are there some characteristics that influence the

proneness for disposition effect? Dhar and Zhu (2006) aims to answer that question, thus their

focus is on the individual level. In their data, one-fifth of the investors show no evidence of

the disposition effect at all, but their results show strong evidence of the disposition effect on

average. Brown, et al. (2006) have studied the disposition effect among insurance companies,

government investments, incorporated companies, nominee companies and individuals. Other

investor groups than individuals have much bigger investments and relatively few numbers of

23

trades, which leads to flatten out the disposition effect in dollar amounts. Brown, et al. (2006)

argues that this is also due to the superior investor sophistication of professionals compared to

common folk and is a characteristic, that mitigates the disposition effect. Choe and Eom

(2009) have also found that the disposition effect is more common for individual investors

than institutional.

There are a lot of research backing up Brown, et al.’s (2006) argument that investor

sophistication mitigates the disposition effect. Seru, et al. (2010) provide an examination of

trading records of individual investors in Finland from 1995-2003. They find that the

disposition effect declines with experience, when experience is measured in number of trades.

The drop in the disposition effect is much less when trading experience is measured in years

showing a need to be exposed to the gains and losses to learn how to deal with them correctly.

Dhar and Zhu (2006) use professional vacancies and income-level as proxies for investment

knowledge which they presumed advantageous for rational trading behavior. The highest

disposition effect values are seen in the group of low income and non-professionally occupied

investors. This is “particularly unfortunate” and suggests that these investors should be helped

by informing them about the harmful consequences of such biased behavior. Trading

frequency also was found out to lower the disposition effect. (Dhar & Zhu, 2006). One might

argue, that the high trading frequency is not always so rational, as seen in Barber and Odean’s

(2000) suggestion, that trading is hazardous to investors’ wealth. Wasting money on iterative

transaction fees is not certainly very profitable, but nor is refusing from cutting the losses.

Picking up the winners among stocks is a difficult task, and no one can forecast the future

with enough accuracy to always make the correct trades. But a simple rule of thumb for

investors might be just cutting the losses and letting the winners run, which also might lead to

modest amount of trades by refraining from trading the winners. That seems to be the key

how professional investors’ performance deviate from financially unsophisticated traders. But

nothing is perfect. Feng and Seasholes (2005) as well document that the disposition effect

fades away with trading experience. They find that sophisticated investors are 67% less likely

to realize gains over losses than the average investor, but no sophistication is enough to

completely remove the tendency to realize gains. The sophistication mostly eases the

reluctance to realize losses. These foundings imply, that the market level evidence of the

disposition effect is making the unprofessional investors looking better and conversely the

professional investors looking worse.

24

Much of the literacy about behavioral finance tell a sad story about human beings and their

decision-making skills. Maybe we are just not made for handling complex financial decisions

with many variables. Fortunately, we are adaptable. Cognitive ability and financial literacy

are not untrainable personality traits and moreover even cognitional biases, like

overconfidence and heuristics are possible to be mitigated in to a point that they are more

useful than not. Kahneman and Reipe (1998) suggest that only becoming aware of these

common pitfalls and biases helps diluting their effects. Awareness combined with being

subjected to them stimulates already great results. Although it is quite clear that financial

literacy, or more specifically the trading experience, circumscribes the disposition effect,

there are contrarian evidence also. Locke and Mann (2000, 2005) provide data, that shows

professional traders failing to realize their losses soon enough. The evidence shows that also

these traders whose income is dependent on their trading success, still consistently hold losing

stocks longer than winning ones. However, they find that the more successful professional

traders show the reluctance to realizes losses to a lesser extent. Chen et al. (2007), show that

sometimes the disposition effect is not even ruled out by investor sophistication. They realize

that Chinese investors are more prone to the disposition effect than U.S. ones, and in China

even more experienced market participants fall into the disposition effect significantly often.

This is also true in Shapira and Venezia’s (2001) study in Israel and Locke and Mann (2005).

Their result, however, cast doubt on the harmfulness of the disposition effect, and suggest that

this does not induce any losses for them and might even be somewhat rational, retelling

Fama’s (1991) suggestion.

In addition to investor sophistication, other characteristics should be reviewed also as

potentially influencing the disposition effect. A matter supporting the self-control theory

could be the notion in Frederick (2005), that the disposition effect is connected to intuitive

thinking. In his experiments, an undergraduate participant with lower IQ preferred 3400

dollars now than 3800 dollars next month. 35% of the low IQ group chose to wait until the

next month to receive the bigger monetary amount. This was true in 60 percent of the high IQ

group; almost double the amount of higher IQ investors were patient enough to wait one

month to receive 400 dollars more. The different IQ groups were measured with a “CRT-

test”. It measures “the ability or disposition to resist reporting the response that first comes to

mind”. Intuitive response, sometimes referred also as heuristics (see for example Kahneman

and Tversky, 1982), is often correct especially in simple tasks or at least provides a

sufficiently correct answer. However, an intuitive response might not be the correct approach

25

to financial problems which often have long-term consequences. Therefore, a CRT-test is a

functional way to find out person’s capability of dealing with economic circumstances.

Further backing up the better financial survival skills, the high CRT group also showed no

tendency to gamble in the domain of losses instead of the domain in gains, compared to the

low CRT group. The prospect theory’s predicted greater willingness to take risks to avoid

losses compared to achieve gains is “spectacularly true” for the low CRT group (Frederick,

2005). This difference in the attitudes towards the same monetary amounts depending

whether they are positive or negative, also shows a fruitful grounding for mental accounting.

Lower financial skills probably complicate the outlining of financials as an ensemble and

makes one more vulnerable to react to events as separate from the whole, as suggested in

Thaler’s (1985) mental accounting.

Education is one thing to consider. Chevalier and Ellison (1999) show that mutual fund

managers with high education, MBAs in particular, outperform those without an MBA. This

is even more highlighted in undergraduate institutions with higher SAT scores. SAT is a

standardized test widely used for college admissions in the United States. This can be due to

variety of reasons; the students enrolled as a member of a high SAT university might have

higher inherent abilities, they are receiving better education, they have better connections, et

cetera. Regardless, there is a connection with education and investing performance, and the

better education, the better performance (Chevalier & Ellison, 1999 and Golec, 1996). At the

same time, investors’ education is not any proof of better performance., Alexander, et al.

(1998) show that in the United States, majority of the investors are well educated. However,

they present evidence from a survey, that dozens of per cents of the surveyed investors lack

knowledge of mutual fund fees, stock fees and their influence in the overall investment

performance. 12 percent of them even believe that stock funds cannot yield negative returns.

This is, without saying, possibly very harmful for investors success, and shows that education

is not a guarantee of investor knowledge and potential.

How about men and women and their disposition effect? In Frazzini’s (2005) CRT-test, a

difference between genders is also found; men scored higher. He is careful about that and

limits out the possibility of sampling procedure causing the results, and according to him it

appears that the CRT-test measures something that men have more of. He is speculating that it

may be due to men’s higher interest in mathematical problems, since the tests are

mathematical in nature. The interesting part is that women seem to give more intuitive

26

answers than men. The test was formulated so that there are seemingly easy questions to

which people normally have a quick intuitive answer, but which is usually wrong. Women’s

wrong answers hit the sphere of common intuitive wrong answer often, while men’s wrong

responses contained a lot of results of an erroneous thoughtful work. Women were also found

to be more risk averse than men. He concludes the gender results by saying: “Expressed

loosely, being smart makes women patient and makes men take more risks.” He finds that risk

taking is only seen growing in the domain of gains (Frazzini, 2005). From empirical sphere,

Barber and Odean (2001) have shown that men trade 45 percent more than women. They

propose that the difference derives from men’s overconfidence. Single men trade even 20

percentage points more. Prince (1993) show also that men take more risk especially in

financial decisions. Lundeberg, et al. (1994) show that undergraduate males are especially

overconfident. Deuax and Emswiller (1974) argue that the gender differences are at their

biggest in masculine tasks. They generally argue, that both genders are overconfident, but

men are even more.

2.2.1.6 Realization utility

The traditional view of utility in the field of economics is that people derive utility from gains

and losses, rather than from final wealth levels. This is already suggested by Markowitz

(1952). The more known and popular view and model created on the base of that is

Kahneman and Tversky’s (1979) prospect theory, which digs deep in to the subjective value

of final wealth, and changes in wealth. As discussed earlier, humans tend to put more

attention in to the changes. A more undiscovered view, already proposed by Shefrin and

Statman (1985), is that humans derive utility from realizing the gains. The more gains/losses

they realize, the more positive/negative utility they derive already in the act of realization.

Barberis and Xiong (2012) offers two explanations for the realization utility theory. They

assume that investors get utility in the result of their own cognitive processes linked in to

investing; humans think of their stock holdings as a series of separate investing episodes, and

evaluate them one by one. The story what investors tell themselves might be something like:

“Selling a stock at a gain relative to purchase price is a good thing – it is what successful

investors do” and vice versa. Therefore, realizing a stock at gain gives the investor a positive

feedback and he/she associates himself/herself as a successful investor. Barberis and Xiong

(2012) suspects that this is motivating investors to exhibit disposition effect. After all, who

27

wouldn’t want to consider himself/herself as successful investor? However, they also admit

that realization utility itself is not fully capable of explaining the disposition effect. There

might be even bigger gains to be realized in the future to derive more utility from.

A modern and technical way of testing the theory has already been done. The untraditional

suggestion that already the act of realization gives utility definitely needs strong proof.

Frydman, et al. (2014) use functional magnetic resonance imaging (fMRI) data from subjects

to test realization utility. FMRI measures neural activity in the brain and the goal of the

analysis is to detect correlations between brain activation and a task the subject performs

during the scan (Logothetis, 2008). Frydman, et al. (2014) test whether there is certain neural

activity in the brain already before actually selling the asset. The goal is to try to analyze

whether the activity is in line with the magnitude of the capital gain or loss. In other words,

they want to know if there is a positive correlation between brain activity and the outcomes of

trading. And if there is a connection with the neural activity and stock realization, is the

strength of the neural activity positively correlated with the strength of the disposition effect.

The analysis of the subjects’ fMRI data strongly backs up the realization utility theory.

Frydman, et al. (2014) find a great difference between the proportion of gains and losses

realized, and also see a connection between the size of the capital gain and the activity in

ventral striatum, “an area in the brain known to encode information about changes in expected

lifetime utility”. However, they don’t find a similar connection with loss realization, what

might be due to failures in their model (Frydman, et. al. (2014). It is probable that realization

utility is not the only thing at work when disposition effect is displayed, but it certainly does

play a part. Also, using neural evidence to test economic theory has proven to be successful. It

is intriguing that these totally unconscious reactions in our brain and body might in fact be

driving our real-world actions and decisions.

2.2.2 Outcomes

It is a robust scientific finding that people behave as forecasted in the disposition effect

theory. It has been shown both experimentally and empirically by dozens of researchers.

Nevertheless, the outcomes of the disposition effect are unclear. It is difficult to estimate what

results from a behavioral bias especially on a market level. In this chapter we take a closer

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look what does the literature has to say where does the disposition effect lead us on the

perspective of individuals, and what it does to the markets.

2.2.2.1 Effects for individuals

A behavioral bias is by definition behavior, which is wrong and potentially damaging for the

individual. If the biased behavior is not corrected by luck, the outcomes are often harmful,

and at least suboptimal. Investing is considered to be action, where money is put into financial

schemes, shares or property with the expectation of achieving a profit. The disposition effect

being a behavioral bias in investing, it is easy to say that it should lead to suboptimal financial

performance for investors. A direct negative impact of the disposition effect is the transaction

cost when a stock which have gained value is sold. However, that is part of the nature of

investing and is not suboptimal itself. A further look into the literature is needed to find out

about the indirect costs of the bias in question.

One reason the disposition effect has raised so much attention in the literature might be

Terrence Odean (1998) finding about the missed opportunities of investors. He shows that the

stocks which have gained in value and were sold by investors, provided on average 3,4%

higher returns than the stocks which had lost value and investors kept holding on to. Also,

Jegadeesh and Titman (1993) have shown that: “buying past winners and selling past losers

realize significant abnormal returns over the 1965 to 1989 period.” Their strategy was based

on buying the stocks, which had positive price performance past 6 months, and held the

stocks for the next 6 months. This provided 12,01% excess return on average.

Barber, et al. (2009) show that investors trading too much causes them to lose money. In a

huge Taiwanese dataset, the aggregate individual portfolio suffers 3,8 percentage points of

loss because of excess trading. This is also true in an earlier study of Barber and Odean

(2000) in United States of American’s stock exchanges. Households achieve on average

almost the same gross return as the market, but the difference lies in the net return. Trading

makes them lose to the market a massive 6,5 percent points. Needless to say, the loss is even

stronger if only the winnings stocks are traded.

Investors trading in herds cause their own stocks the be more unpredictable. Frazzini (2006)

tests how stocks react to news and how the disposition effect affects the reaction. He finds

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that investors with mental accounting and prospect theory attributes cause stock prices to

underreact to news. When good news is announced for a stock, its price reacts positively. This

motivates the disposition effect prone investors to realize their gains, braking down the

stock’s price from increasing. This leaves the stock’s price depressed, preventing it from

increasing to the point of fully reflecting the news. He finds return predictability in short-term

in the case of good news, as well as in bad news. The predictability is most severe when

capital gains and the news have the same direction. Frazzini’s (2006) conclusion is: “Stocks

with large unrealized gains underreact to good news, and to good news only, and stocks with

large unrealized losses only underreact to negative news”. This is also shown by Barber and

Odean (2009).

Although it is clear what disposition effect -prone investors cause to themselves, there might

be other outcomes also. Dhar and Zhu (2006) suggests that rational investors may get

advantage of biased behavior. This is backed up with Barberis and Shleifer’s (2003) findings

that prices in the markets deviate significantly from fundamental values and the markets have

great opportunities for combining contrarian and momentum strategies (also Li & Yang,

2010). The opportunities might not be easy to take, but the offered profits on the markets

caused by the disposition investors might explain some of the success of substantially well

performing individuals. Barber, et al. (2007) however, shows that the disposition effect does

not lead to momentum at least in Taiwanese stock markets so this theory still needs some

testing.

2.2.2.2 Effects for markets

A straightforward effect of disposition effect on a market level should be seen at least in the

trading volume. If it is as expected, that traders are reluctant to realize losses and far too eager

to realize gains, it should mean that stocks losing value should have lower volume than the

winners. Providing proof on a market level is relatively difficult, because investors tend to

buy the stocks at different times, and it is difficult to say which stock in reality is a winner and

which a loser. That depends of who you are asking that from.

Kaustia (2004) especially highlights the difficulties in the reference price, to which individual

investors compare their stocks’ performance. The determinants of the reference price for each

investor are unique. The purchase price, being the most obvious determinant for the reference

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price, is constantly changing and thus almost unique for buyers. Also, it is not perfectly clear

that all people compare their stocks’ performance to the purchase price. Kaustia’s (2004) tries

to tackle that problem by studying the disposition effect in the case of initial public offerings

(IPOs). n an IPO, a company transforms from a privately held company into a public

company by offering shares of the company to be sold for investors for a common purchase

price. There the purchase price of the stock cannot affect investors’ reference price differently

and thereby provides a “clear setting to investigate the disposition effect in aggregate”. He

finds that stock’s trading below the purchase price in the IPO has their volume significantly

suppressed. This is consistent with the disposition effect, an unwillingness to realize losses.

However, the evidence is slight for winner IPOs awaking the disposition effect. Also,

particularly the price changes in smaller loser firms in his sample provided strong effects on

volume, but he mentions that market patterns are usually stronger for small firms. Moreover,

Kaustia (2004) finds that record prices, both high and low, steps up the volume significantly.

Especially record highs produce a strong increasement in the amount of trades.

Further evidence on volume has been provided by other authors also. Ferris, et al. (1988)

show that the trading volume in winning stocks will exceed the volume in losing stocks in

every month of the year robustly holds. In somewhat rationally it would make sense to sell

more losers in December due to tax considerations, but still selling winners prevailed. This is

consistent with Lakonishok’s (1986) findings. Cunha (2011) also finds an asymmetric

volatility effect between losers and winners caused by the disposition effect. Market is illiquid

for losers and that increases the price change when there are demand shocks. Furthermore,

they show that volatility change is smaller after capital gains. This altogether means that there

is an asymmetric volatility effect between losers and winners and Cunha (2011) argue it is a

consequence of the disposition effect.

Odean (1998) points out a fear that the disposition effect could contribute to market stability

near prices at which substantial trading has taken place. If large amounts of investors acquire

the stock at a certain price, it may become a common reference point. Now, if the stock loses

its value from its reference point, these investors may be averse to selling it for a loss and by

this reducing its supply of potential sellers. This reduced supply may slow the further price

decrease, keeping the stocks’ price higher than they should be. On the other hand, in the case

of rising prices, the investors fueled with disposition effect may decrease the rate of

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increasing prices. These possible effects affecting the supply of stocks may lead to delay of

information reflected to stock prices. (Odean, 1998.)

Grinblatt and Han (2005) show that the disposition effect circumscribes stock’s price reaction

to information. This, causal or not, creates also a spread between stock’s fundamental value

and its equilibrium price, offering a possibility for momentum investing strategies. In their

opinion, this “generates predictable equilibrium prices interpretable as possessing

momentum”. This might be caused by investors holding on to their losing stocks and

liquidating their winners, and means that stocks with substantial amounts of unrealized capital

gains yield better returns than those with unrealized capital losses. This offers an opportunity

of a profitable momentum trading for sophisticated investors. Li and Yang (2010) question

that. They point out that Grinblatt and Han (2005) fail in explaining that “such demand curve

can be generated from prospect theory preferences”.

The disposition effect might play a role in the major events also. In March 2000, 25,9 percent

of the Internet stocks were held by institutions. At the same time, institutions held 40,2

percent of non-Internet stocks. This tells a story, that there was a strong demand from retail

investors to Internet-based stocks which lead to the creation of Internet-based mutual funds

also. In Ofek and Richardson’s (2003) opinion, this means that “the market was more prone to

the types of behavioral biases that lead to overly optimistic beliefs”. Another evidence of a

substantial amount of retail investors is the volatility of the markets. Internet stocks were 5.9

times more variable than non-Internet stocks. Barberis, et al. (2001) have shown that investors

with the prospect theory preferences create higher mean returns and volatility. The slow loss

realization might have tied up the prices higher further inviting more and more investors to

the market and have accelerated the effects of the internet bubble with other irrational

behavior of the investors.

In conclusion, the markets face several suboptimal consequences of the disposition effect. The

irrational trading behavior of investors might affect market stability by keeping stocks prices

deviating from the fundamentals and so damaging the information reflected by the prices.

There are an asymmetric volatility and volume between loser and winner stocks and the

effects are strong when a big amount of investors have acquired the stocks at about the same

time. The illiquidity of losers exacerbates price changes when the stock in question faces

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demand shocks. At least these effects are relatively robust and clearly affects the perfectness

of the markets.

2.3 Emotions

As Staw (1976) describes it: “Intuitively, one would expect individuals to reverse decisions or

to change behaviors which result in negative consequences.” In reality, we often find people

not reacting as intuitively anticipated. Staw suggests instead, that the “individual will

cognitively distort the negative consequences to more valenced outcomes.“ This combined

with the common bias called “gambler’s fallacy” may lead to a belief that the probability of

gain is increased after former failures. In his experimental study, Staw (1976) shows that the

reactions of participants were stronger and more committed to the outcomes if they had

responsibility for the decision. They were far more inclined to stick to a course of action what

was not going well and also more prone to invest resources in to it, if they were responsible of

the decision themselves (Staw, 1976). This thesis commits more resources into research of

emotions by digging deeper in to their role in decisions-making.

Investing is action towards a goal. As Bagozzi, et al. (2000, 38) put it: “If progress toward a

goal is lower than the desired rate, negative affect is experienced; if it is higher, positive affect

results. If no progress is being made, affect is also negative, and if progress equals the desired

rate, no affect is experienced”. Emotions, negative and positive, might affect the decisions we

make. We often feel emotions already prior to the decision and conversely, sometimes the

decisions we make, cause us to feel emotions. Another implicit connection between decision-

making and emotions is the anticipation of emotions. Our decisions might be affected by

already the forecast of the emotions the decision will arise. In other words, there may be a fear

of negative emotions, or a want to experience positive ones. Sometimes we make decisions

with the immediate effects in mind, ignoring the long-term effects. In this chapter the focus is

on regret and disappointment and their positive counterparts, rejoice and elation, which are

often felt when evaluating the results of investing.

Zeelenberg, et al. (1998) study the slight differences between regret and disappointment. First,

they describe that experience of regret makes people feel a tendency to kick oneself and to

correct one’s mistake, they want to undo the event and get a second chance and they think that

they should have known better. Second, they claim that: “disappointment involves feeling

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powerless, feeling a tendency to do nothing and to get away from the situation, actually

turning away from the event and wanting to do nothing.” Both feelings seem strong, but the

author make a difference in us dealing with the two emotions. In their experiment, it seems

that disappointment can be paralyzing, but it is more easily dealt with and people are able to

forget it and continue on their lives. Regret on the other hand, stays stronger in people’s

minds. The two emotions are undeniably similar, but the author make a difference how them

are brought up. To feel regret, people need to be responsible of the outcome, or that the

negative outcome could have been prevented by one’s own behavior. (Zeelenberg, et al.

1998). Here the difference, and its effects to decision-making, might be striking.

The literature on the impact of choice indicates that generally people expect to feel more

regret over action that leads to a negative outcome than over inaction that leads to the same

negative outcome (Kahneman & Tversky, 1982) So, the emotions are not in line with the

outcomes. The same outcome possibly arises stronger emotions, potentially affecting future

behavior, if the agent has made an action towards it. Coiffi and Garner’s (1996) experimental

study backs up this. Even a tiny action can bind people in to a subject. They show that

committing to a choice with an action, such as blackening a box or writing a statement make

people feel more bounded to the decision. They found a clear difference in engagement

between people who were included in the task as a default, and more specifically, that they

should have actively decide not to commit in to the action.

Emotions arise especially when feedback is received. The feedback in everyday life is

sometimes obscure, but investments tend not to hesitate. Duxbury and Summers (2012) have

studied emotions involved in trading, what kind of different emotions there are, how they are

awoken and what they have to do with the disposition effect. As explained before, the

disposition effect means the tendency to hold stocks which are losing its value and selling

stocks which have gained value. The emotions involved in these situations are dependent on

the emotions the investor has attached to the corresponding stock. The authors state that the

emotions experienced with certainty, e.g. emotions what people experiences for sure after

receiving feedback, are different for a winning stock and a losing stock. An investor selling a

loser stock knows that he/she will experience regret or disappointment, or both, at the time of

selling. Duxbury and Summers (2012) advocates about losing stocks that: “If the person chose

to hold the stock in the first place they will experience both, if they do not own the stock

through their own choice they will only experience disappointment.” And in the case of a

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winning stock the investor will feel rejoicing or elation, or both. On the other hand, if the

stock is hold and not sold, the positive or negative emotions will remain to be unleashed

(Duxbury & Summers, 2012). The fear of experiencing these emotions could be part of the

disposition effect. The key feature here is the story between the investor and the stock. If the

investor feels in a way connected to the stock, there are more and stronger feelings attached to

it. One might argue that which stocks are not picked by the investor, but actually there are

plenty. Stockbrokers and investment advisers are professionals investing on behalf of others

and a recent development is a robo-adviser, an algorithm-driven non-human stockbroker. The

stocks might have also been a gift or inheritance, which is the focus on this study.

Shefrin and Statman (1985) suggests that the disposition to sell winners to soon might be

motivated by impatience to wait for the future positive emotions. Duxbury and Summers

(2012) add to Shefrin and Statman’s (1985) suggestion that the desire could also derive from

the fear of having those possible positive emotions replaced by negative ones as a result of

waiting. This balancing between immediate and anticipated emotions could be the reason for

the investors’ tendency to hold on losing stocks and selling winning stocks. They might feel

pressure to repatriate the gains as soon as they see them earned and additionally, they might

get afraid that these ready-to-be-felt emotions of joy can be replaced by sorrow of losing. The

lost opportunity can even exacerbate the negative emotions by adding the regret of not

repatriating early enough to the normal feeling of disappointment of a negative outcome.

In two experimental studies, Duxbury and Summers (2012) tries to shed light on the

experience of gain or loss in investors. The research is done separately with an investment

choice included and excluded. The authors base their study on findings of Cioffi and Garner

(1996), who imply that active choice influences the level of commitment to decisions. Both

studies done by Duxbury and Summers (2012) were executed with common features

including an indicator whether the stock is a winner or loser, only one option investment

option offered, e.g. one risky stock, and an invitation for investors to rely on intuition by

removing the opportunity to use technical approaches to assess the stock and the use of real

historical price movement data. The participants were offered a 500 pound starting sum either

stocks or cash, depending on in which group they were (choice included or excluded). They

were also motivated by a prize for taking a part. The sum of the prize the participants were

offered depended on their performance in the experiment. (Duxbury & Summers, 2012.)

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In Duxbury and Summer’s (2012) study’s first part, 131 university business school students

were given 10 stocks of Company A worth 50 pounds each. The participants were told that

they had received the stocks from a relative, so removing the choice involved in picking those

stocks. They were not able to trade the stocks at the time 0 for them to be only spectators to

period 1’s gains or losses. The stock yielded 5 pound gains for “winner” group and 5 pound

losses for “loser” group. After period 1 the participants were allowed to cash out the way they

wanted before revealing period 2 price movement for the stock. After period 2, Duxbury and

Summers (2012) compared the proportion of gains realized to the proportion of losses

realized, in the fashion introduced by Odean (1998), between winner and loser group.

According to Duxbury and Summers (2012): “The proportion of stocks sold by those in the

winning condition (mean=31%) was not significantly different to that in the losing condition

(mean=24%, p value for difference >0.1). They explain that the differences in risk preference

between these groups can explain the results, concluding that there was no evidence of the

disposition effect. By removing the initial investment decision which involves thinking and

evaluating in picking the stock, Duxbury and Summers (2012) are able to limit the

experienced emotions of gains and losses to elation and disappointment. Elation is

experienced after a winning stock is sold in which the investor had made no contribution by

choosing the stock, and disappointment is experienced in same ways for a losing stock.

In the other part of Duxbury and Summers’ (2012) study they introduced and “active” or

“passive” factor, which indicated that they had to make an active choice or passive choice to

hold stocks. 234 students participated in the study and were divided randomly in to each four

categories: passive winner, active winner, passive loser and active loser. Passive groups were

given stocks of the company, while active groups got only cash and had to make the choice

consciously. The other major difference to the first part explained above was, that the

participants were allowed to trade already before period 1. The stock traded lost again 5

pounds of its value, or gained 5 pounds, and their experience of gains or losses was outcome

of their own choices. Before period 2 they had another trading opportunity and after that their

final wealth was revealed. In this second part of the study Duxbury and Summers (2012)

followed the initial development of the analytical model of Barberis and Xiong (2006). This

part of the study produced clear evidence for disposition effect to exist, both in active(p<0.1)

and passive (p<0.01) groups. They conclude that the minimum conditions to lead to

behavioral phenomena called the disposition effect requires the presence of choice. The

results also continue to support the evidence provided by Barberis and Xiong (2006) and Hens

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and Vlcek (2005) that the prospect theory is not necessarily the reason for disposition effect to

occur. As Duxbury and Summers’ (2012) put it: “Responsibility for the decision to hold the

stock during the period in which a loss or gain takes place is a requirement for the disposition

effect to manifest.” They conclude the study by stating that the existence of choice brings in

another emotion on side the certain feeling of disappointment in the case of losses and elation

in winnings. Disappointment pairs up with regret and rejoicing joins elation. (Duxbury &

Summers, 2012.)

Zeelenberg et al. (1998, 2000) conclude that regret makes people want to correct the mistake

they have done or to have a second chance. Disappointment makes people feel uncomfortable

with the situation and arises a want to escape the situation or neglect the experience. These

notions of regret fits well in the disposition effect. Disappointment is according to Duxbury

and Summers’ (2012) findings not a strong feeling enough to keep people in their loser

stocks, whereas regret arises a need to continue holding on to the stock to make it even again.

While Duxbury and Summers (2012) concentrate on the anticipated emotions and their effect

on decisions, Lee, et al. (2012) have added experienced emotions to the formula. They claim

that anticipated and experienced emotions affect selling decisions simultaneously. Their

findings are consistent with Shefrin and Statman’s (1985) notion of anticipated emotions, but

they add that regret and pride may have already been experienced before the action. The

following decisions are affected by the strength of the already experienced emotions. If the

investor has experienced already a great amount of regret of a paper loss, the anticipated

regret of selling a losing investment is lower. This leads to greater propensity of cutting

losses. (Lee, et al. 2012.)

In summary, the role of emotions has gotten attention among financial researchers as well.

Humans are not machines. The shape of our bodies and our minds were formulated thousands

of years ago and the tasks they were meant to solve, did not include complex investment

multiple choice questions. However, these skills have become relatively important in modern

times. The investment tasks require cold rationality, which we often lack. Our emotional

reward and punishment system served important tasks in the savannah, but in this

environment, they need to be tamed. Some people may be able to switch the emotions of, or

get them easily controlled, and some not. It is anyway important that we understand how they

affect us. In this chapter the role of emotions in investing decision-making was reviewed.

There are negative and positive emotional responses, which will further divide in to two

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categories. Negative emotions are disappointment and regret in the case of losing investments,

and their positive counterparts, rejoice and elation, are experienced in winning investments.

Regret is a stronger emotion than disappointment. To feel regret, one needs to feel feels

responsibility over the choice which led to a negative outcome. Disappointment is for

example experienced after realizing that the weather forecast was not correct; it is raining

instead of sunshine and you could not do much about that. The research field assumes that

disappointment in terms of investing is not enough to produce the disposition effect. This in

my opinion need more testing. It is very important, because if we are able to track the exact

conditions where the disposition effect arises, we are more capable of understanding and

committing further research in to it.

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3 METHODOLOGY

The disposition effect has been studied in the literature with several methods. There are plenty

of empirical evidence of disposition effect in the stock market trading, but other asset classes

have gotten attention as well. Traditional and highly cited research are usually empirical

studies of individual investor's transaction data, but theoretical and experimental research

have also prevailed. Despite the vast amount of research in the field, it seems that there exists

a huge gap in the literature in explaining the causes of the disposition effect. Pinpointing the

reasons for behavioral biases is difficult from empirical data, because it is almost impossible

to say from transaction data what are the reasons for certain trades. Differentiating the

disposition effect from overconfidence for example is not an easy task. Therefore, this thesis

aims to contribute to the literature by studying the disposition effect in an experimental

setting. Of course, it is not a fool-proof method either, but by limiting the conditions it is

possible to focus more strictly to the disposition effect.

A pragmatic approach used in this research is to study only one transaction opportunity with

six risky assets. It is similar to Duxbury and Summers’ (2012) study, but they used only one

risky stock in two periods. The method used in this study is a survey posted in the internet

which will be discussed in detail in the following chapters. The literature discusses the

differences in trading behavior between certain investor characteristics. For example, high

financial sophistication has been observed to mitigate the disposition effect effectively and

that will be tested in this setting. Gender differences mostly lie in men’s overconfidence,

which has been found to make them trade more than women. Some evidence of higher risk

taking has also been suggested. Education, alternatively, has some controversial results

sometimes having an effect and other times not, thus that will be tested too.

3.1 Research approach

The research question is to find out whether people exhibit the disposition effect, if they have

not chosen the stocks themselves. From this angle, I formulate the first hypothesis.

Hypothesis 1: People are not prone to the disposition effect, if they do not feel

responsibility over choosing the stock.

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The responsibility of choosing the stock by the investor itself will cause the investor feel

regret over an unsuccessful decision, therefore making the investor reluctant to admit the

mistake by closing the mental account, e.g. realizing the loss. In addition, I will test if the

disposition effect is lower among more sophisticated investors. This is the ground for the

second hypothesis.

Hypothesis 2: The disposition effect is lower for more financially sophisticated

respondents.

On side of the two main hypothesis I formulate two sub-hypotheses based on observations in

literature. The first sub-hypothesis claims that women lower values of the disposition effect

than men, and the second sub-hypothesis claims that education itself plays no role in the

disposition effect.

Sub-hypothesis 1: Women have lower values of the disposition effect than men.

Sub-hypothesis 2: Higher education does not necessarily lead to lower magnitude of the

disposition effect

The research will be carried out in the form of a survey, which will be posted in different

social media pages in public settings, that also people outside from my peer group can see it.

The social media platforms are Facebook, LinkedIn and Reddit. In Facebook and LinkedIn,

the most immediate audience will be my “friends and acquantainces”, but Reddit post will be

sent out anonymously via a nickname. The answers will be analyzed in a quantitative method.

Quantitative analysis will be used to find out whether the participants sell more of stocks

which have lost value than stocks which have gained value, and to find out if certain

characteristics correlate with the results. The stocks will be viewed separately, to follow the

theory of mental accounting how the investors perceive their investments. <

Odean’s (1998) equation will be used mainly for measuring the disposition effect. In his

empirical research, he calculated the disposition effect from the market data by comparing the

proportion of gains realized (PGR) to the proportion of losses realized (PLR). If PGR is

bigger than PLR, the investors are more prone to realize winners than losses and thus exhibit

the disposition effect. As done by Dhar and Zhu (2006), the Proportion of Gain Realized and

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Proportion of Loss Realized will be calculated on individual level, in addition to the aggregate

level which Odean (1998) used. The proportions of realized gains and losses are measured in

the amounts of trades in addition to the monetary amounts. If it is to be found that the

participants are more prone to sell winners, it will cast doubt on Duxbury and Summers’

(2012) statement, that these conditions are not enough for the disposition effect to appear.

For ensuring the robustness of the calculations, Weber and Camerer’s (1998) formula (Sales

of Winners – Sales of Losers) / (Sales of Winners + Sales of Losers) and RG/RL-PG/PL will

be implemented alongside the PGR/PLR. With these variations of how to calculate the

disposition effect, it is fairly positive that the true skin of the investors will be revealed.

For simplification, there will be no dividends discussed in this case. Also, the price graphs

how each stock has recently performed will not be shown, that the investors will not try to

apply any technical analysis strategies in the evaluation process. The results will be calculated

individually and compared between them. In addition, the participants will be divided in to

different investor groups according to their characteristics. Gender, education and

participants’ own perceived investing knowledge will determine in which group the

respondent will be set, and the comparison between groups is of interest. Literature shows that

education itself plays no part in mitigating the disposition effect, but the investor

sophistication measured in the amount of trades does.

3.2 Questionnaire

The questionnaire used in this research is somewhat following the procedure used in Duxbury

and Summers (2012). The questionnaire starts with a background story, where the participants

are set in an imaginary investment situation. They have inherited 100 000 euros from their

relative divided unequally in 6 stocks. The participants are shown the 5-year price

performance of each stock in a single percentual figure; half of the stocks have gained value,

and half of the stocks have lost value. The participants are then asked to choose how would

they like to proceed with their investments. In addition to the initial 6 stocks, they have a

choice to withdraw investments and cash out. They are free to choose any combination of the

stocks and cash within the limit of 100 000 euros. The price of each stock is not revealed for

the case of simplicity, and everything will be conducted only in monetary amounts. The

choice is fully theirs. Also, there are no transaction costs involved.

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The stocks used in the questionnaire do not represent any real companies. Kahneman and

Tversky (1982) argue that numerical predictions, such as the future value of a stock, are often

made by representativeness. They say that: “If the description of a company is very favorable,

a very high profit will appear most representative of that description. These predictions will

be insensitive to the reliability of the evidence and to the expected accuracy of the

prediction.” By description, they mean the description the investors have about the stocks in

their mind. For example, if he likes Nike’s products, he is more probable to give a more

favorable prediction for the company’s stock’s future value. They continue by stating that if

there is zero predictability, the same prediction should be made in all cases. In their opinion, if

there are no information available about the average profit of companies’, the same value

should be set for all companies. (Kahneman & Tversky, 1982). This is the reason why the

stocks are not named by real world companies. Instead, they are called Stock A, Stock B,

Stock C, Stock D and Stock E. In the questionnaire, the only feature for predicting offered is

the 5-year price performance percentage. With this few information, it is fair to say that the

only rational choice to answer the questionnaire is to favor the positive stocks, or completely

change everything to cash in lack of information. There is no reason to believe that the

negative stocks would outperform the positive stocks in the future. Here, one might say that

the belief in mean-reversion could take on and provide popularity for the negative stocks, but

that has been already debunked by Weber and Camerer (1998).

An online questionnaire is used for numerous reasons. First of all, there are obvious strengths

shared between all online surveys. They are efficient in the sense of time, paper, money, data

collection (Evans & Mathur, 2005) and it is fair to assumed that an online survey will reach

more respondents than traditional pen and paper. A great strength at these hectic times is that

the respondents themselves can choose the time when they answer to it and return the

answers. Online questionnaires also can be enabled to require all answers before completion,

which eliminates item non-response and the need to throw out improperly filled

questionnaires. Online surveys have also become very common way to gather answers in

research in general. Moreover, to improve the sample there will be two online links: one for

Finnish speakers and one for English speaking people. The use of online questionnaire also

removes interviewer’s interaction with respondents, so removing the questions like “what do

you want me to answer?”, i.e. the interviewer bias. Investing is more often than not a solo

project, where people are needed to make decisions independently.

42

In this instance, the survey benefits from the online platform also in two important senses.

First, since there are monetary amounts in play in the investment task, the online platform

restricts the answers to only consisting of numbers. This also prevents failed answers, because

fulfilling the task wrongly on purpose is not possible. Second, for the investment cash was

100 000 thousand euros, the online platform did not let the respondent to proceed if the

entered sum exceeded or fell short of 100 000. The platform required the stock investments

and cash realization to match perfectly the given amount. This would not have been possible

with pen and paper. The platform gave an error message if the amount did not add up until

100 000, but it did not reveal the needed or exceeding amount. In addition to help preventing

wrong answers, this feature might force the respondents to think about the answers effortfully.

Since there were 7 different options to fill numbers in, it is unlikely that the respondents

would come up intuitively with the answer what is 100 000 divided by seven and thus taking

the easy way out by filling up an even number to every answer box. 100 000 divided by seven

is approximately 14285,7 which is even impossible to fill in the answer boxes, because it only

accepted whole numbers. Even though the respondents used calculator to count the even

number to fill in every box, the questionnaire would give an error, and the respondents were

required to fill in whole numbers. The literature of heuristics shows that this feature forces the

responders to use the part of their brain which is required to solve complex tasks (see

Kahneman & Tversky, 1974) and probably brings higher quality answers.

There are also weaknesses in online surveys. Evans and Mathur (2005) say that they might be

precepted as junk mail, the population of Internet is usually leaning towards wealthy and

male, the respondents might misunderstand the instructions or completely miss some of them.

Sometimes online surveys are considered impersonal and have some privacy issues. The

aforementioned weaknesses in online survey characteristics are not an issue in this

questionnaire. There are quotas set that also women will have a voice among the respondents.

There is no tool to balance the privileged average user of internet on a global level, but it is

fair to assume that the average investors are also privileged on a global level. Of course, the

questionnaire might be perceived as junk mail and people will choose not to answer it, but

that might also result in better respondent quality; those who will choose to answer it will take

their time and read the instructions carefully. The questionnaire is also arguably simple. One

might suggest, that such information is not enough for an investor to make an investment

decision. However, this is also not an issue. If some participants think they are not capable of

43

making investment decisions with the given information, they are able to sell all the stocks

and fully cash out 100 000 euros. This will not even affect the results of the thesis, since the

monetary amount of loser and winner stocks are almost equal. By selling all of the stocks they

have inherited, they don’t exhibit any disposition effect. Also, the research question is to find

out the minimal conditions required for the disposition effect to appear. The questionnaire

was available at www.surveymonkey.com survey software website.

3.3 Data sample

The data sample is a non-probability self-selection sample. The questionnaire was unrestricted

and publicly open for anyone to participate in. Participants themselves opt or opt-out to take

part in to the questionnaire voluntarily. The questionnaire was posted on my account on three

different social media channels in Internet: Reddit, Facebook and LinkedIn. It is impossible to

say how many people chose not to answer to the questionnaire, which means in other words,

how many non-responders there are. Therefore, the sample may include some non-response

bias. It is possible that some people with certain characteristics systematically opt-out of the

questionnaire (Fricker, 2012, 199). But again, this is not an issue for this thesis. The pre-text

containing the link to the questionnaire informed the potential participants that it is about

investing. Therefore, the participants are probably at least slightly interested in investing. On

one hand, if the data sample is biased towards people who are more interested in investing on

average and they fall into the disposition effect, the results might be even stronger in reality.

And on the other hand, if there is no disposition effect to be seen, the results further back up

Duxbury and Summers (2012) results, but probably still need more testing. This however, is

not a proper task for master thesis, since gathering the participants probably needs stronger

incentives, for example a monetary prize. A small money prize relative to the results of an

investment questionnaire is commonly used for motivating the participants to take part and

put on their best effort.

To improve the sample to represent better the general population, and also to formulate

groups big enough, quotas were set for the data sample before posting it on the distribution

channels. Quotas were fulfilled with a good accuracy enough to analyze the results in a

planned fashion. Quotas set for gender, education and investor sophistication will be

presented next. Since investor sophistication is a key independent variable, quotas of 10

people of each level of perceived investor sophistication were set. It is measured on Likert

44

scale, from one to 5, thus needing at least 50 people, but unfortunately this quota was not fully

met. The quotas set with corresponding respondents are shown in the next table (1).

Table 1: Quotas set for perceived investor sophistication (Likert scale, 1-5, where 1 is novice

and 5 is expert) and actual respondents’ amounts.

1 2 3 4 5Quota 10 10 10 10 10Responses 28 27 12 7 6

Education is also an independent variable of interest, thus limitation of at least 10 different

respondents of each education category were chosen for quotas. This means 10 participants

with master level education, 10 with bachelor level education and 10 with high school level

education. The quotas for education and corresponding responses are shown in the next table

(2).

Table 2: Quotas set for different education levels and actual respondents’ amounts.

High

School Bachelor MasterQuota 10 10 10Responses 13 36 31

The internet users are also more commonly males and therefore quotas are set to consists of at

least 20 females and 20 males. The quotas for gender and corresponding responses are shown

in the next table (3).

Table 3: Quotas set for both genders and actual respondents’ amounts.

Female MaleQuota 20 20Responses 33 47

The questionnaire was posted on different platforms on different times to reach as many

people as possible from my peer group. There was one month break between posting it in

LinkedIn and Facebook, since a large share of my peer group on these platforms is the same.

One month is enough for the people to forget it to reduce the feeling of spam. Also, I reckon

that some people had it on mind the first time they saw it and thought about filling it up later.

45

Posting it again on different platform might motivate them to fill it up this time. Both

platforms have mostly Finnish-speaking audience, but also some English-speaking people so

the questionnaire was offered there in both languages. Reddit though is aa English-speaking

community, so the questionnaire was posted there only in English.

Non-probability samples are generally considered not very good for scientific research and

face criticism about especially generalizability. However, there are some contrarian opinions

also. Alvarez et al. (2002) propose that these types of non-probability samples might be useful

and appropriate for conducting experiments. Also, further backing up the decision to use a

non-probability sample, Siah (2005) states that most common criticism of psychological

research is that they rely only on college student samples. Investing is really a common folk

activity, where anyone can opt-in or out to take part as well as the questionnaire used to

gather this data sample. Internet global reach is nowadays massive. In Evans and Mathur’s

(2005) opinion, the assumed weakness of online surveys, the lack of representativeness, is

disappearing. The features of online questionnaire will be discussed more detail in the next

section, but here it is worthwhile to mention that the online platform helps in obtaining a large

sample. Since the questionnaire is so simple, the aim for a sample size was 100 respondents.

Due to lack of time, this was unfortunately also not met. The questionnaire resulted in 80

answers in total.

3.4 Data analysis

From the survey platform, the respondent’s answer will be transferred to Excel for further

data analysis. Each respondents’ data consists of his or hers 4-digit identifier, investment

decisions, education level, perceived investment expertise and gender. Realized gains and

realized losses will be calculated for every respondent individually for each stock. Realized

gains and losses are the remainder of stock’s initial amount as inherited and the respondent’s

own choice. For example, the inherited portfolio has stock A worth of 23000 euros. Then, the

respondent reorganizes the portfolio by investing only 20000 euros in to stock A. Since Stock

A is a negative return stock, the respondent has realized losses 3000 euros in the case of Stock

A. In addition to realized losses, the remaining 20000 euros of Stock A will be identified as a

paper loss of Stock A. Stock C on the other hand, is a positive return stock. The inherited

portfolio consists of 15000 euros worth of Stock C. Then, if the respondent chooses to invest

the realized 3000 euros of Stock A to Stock C, he will enter 18000 euros in to Stock C. This

46

means that the respondent has zero realized gains in the case of Stock C. This example would

result a proof against the disposition effect. The aforementioned procedure will be calculated

for each stock and for each respondent.

After the first calculations, the respondents’ answers are accompanied with realized gains and

realized losses for each stock, and the aggregate sum of all stocks realized. In addition to the

monetary amounts, the quantity of realized losses (maximum 3) and the quantity of realized

gains (maximum 3) will be determined. With these calculated variables, it is possible to

calculate the disposition effect. Apart from individual results, all schemas will be calculated

on a market level likewise.

In addition to the main formula PGR/PLR, the two other equations to be calculated for the

participants to measure disposition effect are RG/RL-PG/PL and SW-SL/SW+SL. RG stands

for realized gains and RL stands for realized losses. PG stands for paper gains and PL for

paper losses. These are useful because they do not depend on portfolio size or trading

frequency. The third formula measures the difference in sales of winner and loser stocks

divided by total number of sales and losses by that subject. SW stands for sales of winners

and SL is sales of losers. PGR/PLR is Odean’s (1998), and the other two are formulated by

Weber and Camerer (1998). All the calculations will be done on individual level, as well as

the sample as whole. Furthermore, the results will be compared between investor groups. The

groups are formed by the characteristics the respondents´ have input in the questionnaire.

Later on, the results will be taken in to SPSS for further analysis and a test for statistical

significance. The dependent variables here will be the three different measures of the

disposition effect, and independent variables are gender, education and perceived investor

sophistication. A two independent samples t-test will be held for both genders. That aims to

check if there is a difference between genders. Men tend to trade more (Lundeberg, et al.,

1994 and Barber & Odean, 2001), therefore we wait that they exhibit more of the disposition

effect. An analysis of variance (ANOVA) is done for three education groups: high school,

bachelor and master to check, if education level plays a role on the disposition effect in this

setting. On top of that, a linear regression is used to model whether it is possible to predict the

disposition effect from knowledge of the investor sophistication. The linear regression will be

backed up by three dummy variables, one from gender and two from education.

47

4 RESULTS

The questionnaire resulted 80 answers in total. 47 (58,75%) of the respondents are male, 33

(41,25%) are female. 13 of the respondents have high school level education, 36 have

bachelor’s degree and 31 have master’s degree or higher, level education. The respondents

were also asked of their perception of their investment skills on a Likert scale (1-5), where 1

represents novice, and 5 represents expert. 28 of the respondents perceive their skills as

novice (1), 27 have some knowledge (2), 12 perceive their skills as average (3), 7 respondents

think they have good knowledge (4) and 6 of them consider themselves as experts (5). The

respondents on average have at least a bachelor level education but consider themselves as

novices in investing. Fortunately, there are also respondents with low level education, as well

as those confident about their investments skills, so it is possible to compare their results and

see if there are any differences in their investment behavior. The data presented in this chapter

is also shown in the next table (4). The table (4) aims to show what kind of education levels

and perceptions of their own investment skills different gendered respondents´ have. PIS

stands for perception of investment sophistication and the numbers are the Likert scale.

Table 4: Respondents and their characteristics.

High

School Bachelor Master PIS 1 PIS 2 PIS 3 PIS 4 PIS 5Male 10 19 18 7 16 12 6 6Female 3 17 13 21 11 0 1 0High

School - - - 7 5 1 0 0Bachelor - - - 9 13 4 4 2Master - - - 12 9 7 3 4

The next table (5) represents the original portfolio, which was given for the participants. In

addition to this, they only had information that the yield percentage is 5-year historical price

performance, and that the stocks have been inherited from a relative. Three of the stocks are

positive and three of them negative. The overall value of the portfolio is 100 000 euros and it

is almost equally divided between losing (53 000) and winning (47 000) investments. The

yield percentages are also quite similar. There is one big positive yield (16,9%) and one big

negative yield (22,5%) and the others are relatively small, around 10 percent. The table (5)

48

representing the portfolio will be presented here among the results section to make

comparison and analyzing the results easier.

Table 5: Initial portfolio given to the participants

Given portfolio Stock A Stock B Stock C Stock D Stock E Stock FYield -8,30 % -11,70 % 16,90 % 12,50 % -22,50 % 9,20 %Invested amount 23 000 12 000 15 000 15 000 18 000 17 000

The answers of respondents in aggregate are presented in the next table (6). The headlines

shows the names of stocks, and after that there is either “+” or “-“, to describe whether the

stock was a positive or a negative return asset. The first row, after stock names, tells how

many times certain stock was sold, but it does not take a stand on the magnitude of the

realization. On the second row the aggregate realized amount of the corresponding stock is

displayed. And the third row tells how much was added of that corresponding stock to the

portfolio in addition to the initial values shown in the table 1. The last column differs from the

others in that sense that there was no cash included in the initial portfolio. Therefore, there are

zero realizations of cash. Unlike in the case of stocks, the first row displays on the cash

column how many times some of the stocks were cashed out without further investing. A

sharp-eyed reader can already spot that the negative return stocks were far more popular to be

realized in monetary amounts, as well as times realized.

Table 6: Investment data gathered from the questionnaire.

Data from

surveyStock A (-)

Stock B

(-)

Stock

C (+)

Stock D

(+)

Stock

E (-)

Stock F

(+)Cash

Times

realized66 57 26 26 60 38 49

Amount

realized €1 042 733 497 000 228 000 243 000 871 734 385 234 -

Amout

added €6 000 97 267 558 267 482 267 152 000 171 000

1 800

900

49

The participants have 100000 euros divided in 6 stocks initially. Three of the stocks are

considered as gains, since they have positive return the past 5-years, and three of them are

considered as losses, since they have negative yields. The gains are worth in total 47000 euros

and losses 53000. In the questionnaire, the investors sold stocks with gains on average for

10702,9 euros and stocks with losses for 30055,9 euros. Even though there were slightly more

losses in the portfolio, the amount of losses realized is significantly bigger than the gains

realized.

Throughout the whole results section values of the disposition effect will be presented (for

example, PGR/PLR), and these values are most of the time calculated from euro amounts.

The other option, which is used in Weber and Camerer (1998), is to calculate the disposition

effect in number of stocks sold regardless of their monetary magnitude. This will be done

also, but it will always be mentioned separately. The reason for this is that the questionnaire

provides participants only with 3 winning stocks and 3 loser stocks. Presumably this will

provide simpler results more prone to bias, because the sample is so low. Odean (1998)

calculated the disposition effect for investors from a data of years of trading, which provides

more insight than only one event. In this questionnaire it is also possible that investors only

sell a losing stock completely and realizes only 5% of the worth of a winner. With Weber and

Camerer’s (1998) way this would result describing the investor selling the same amount of

their losers and winners, which is misleading in this example.

When measured in euro amounts, the average proportion of gains realized (PGR) of the

sample is 0,2278 and the average proportion of losses realized (PLR) is 0,5671. That means

that the respondents on aggregated average tended to realize losses more often than gains,

which implies that they do not exhibit the disposition effect. That is probably due to the fact

that they have not chosen the stocks themselves, as proposed in Duxbury and Summers

(2012). Odean’s (1998a) specific mean estimates of PGR and PLR for U.S. individual

investors are 0.148 and 0.098, respectively. The observations are very different in his

empirical data compared to this thesis’ experimental setting. Dhar & Zhu (2006) suggest that

the disposition effect should only occur in the United States from January through November

due to tax-loss selling in December. Excluding December, they report a PGR and PLR of 0.38

and 0.17, respectively. The trading in this thesis is much more frequent and in higher

magnitudes compared to empirical data. It suggests that people are more willing to make

bigger changes in their portfolio in an experimental setting which was also chosen by others.

50

On an individual level, PGR/PLR is on average 0,5529 for respondents, and on a market level

0,402 when calculated from the average values of PGR and PLR. As mentioned before, the

aggregate market value of the disposition effect is not fully satisfying, since it is known that

for example the investor sophistication lowers the reluctance to realize losses significantly.

Thus, three different types of investors were created to gain a deeper insight on the disposition

effect exhibited by the participants. Respondents are divided in to following groups: men,

female, master, bachelor and high school level education, high expertise (4-5), semi high

expertise (3), semi low expertise (2), and low expertise (1).

4.1 Investor sophistication

Here the participants have been divided in to the groups of their perceived investor

sophistication. That results in 4 groups: high expertise, semi high expertise, semi low

expertise and low expertise. High expertise is participants with a value 4 or 5 in investor

knowledge, semi high is 3, semi low is 2 and low expertise is 1. The results are shown in the

next chart (1).

High expertise Semi high expertise Semi low expertise Low expertise0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

PGR/PLR

Chart 1: the disposition effect in different investor sophistication groups.

51

That provides interesting results. The highest PGR/PLR, the basic formula for the disposition

effect, is seen in the group of higher expertise. High expertise group exhibit DE with a 0,9

value and semi high with 0,7. That means that the participants sell their losing investments

only 10 or 30 percent more than their winning investments, respectively. That is surprising,

because the lower expertise groups realized their losses with a much bigger ratio. Semi low

expertise group have PGR/PLR 0,2 and low expertise 0,3. Inconsistently with the literature

the lower investor expertise participants realize their losses and hold on to their winners, and

high expertise investors sell their winners with almost the same ratio as their losers. When

measured in the amounts of trades, the difference is even bigger. The higher expertise groups

actually realize their winners with even a bigger ratio than their losers and lower expertise

groups show a very clear tendency to get rid of their losers and hold their winning

investments behaving completely rationally. These results are so surprising and inconsistent

with the literature, that they deserve a closer look on the individual answers to find out how

this has happened.

In the group of high perceived investor sophistication (4 and 5), there are two answers who

sold all their stocks for cash, resulting in 100 000 of only cash. This drives the value of DE

close to 1, but only close, since there are 53 000 worth of losers and 47 000 worth of losers.

This does not explain the relatively high DE value of higher sophistication group. There are

also two participants who balanced their portfolio approximately equal between all stocks.

This means that they have certainly put some thought and time in to their thinking, by

calculating the result of 100 000 divided by 6, which is a bit over 16600. These two answers

result in a very low value of DE. They both realized their winners for 400 euros or less and

realized their losers for approximately 7700. This results in a 0,05 DE and the group on

average has DE close to 1. These 4 answers reviewed here are completely rational. There are

still 9 more answer in the higher expertise group, and it seems that these 9 are keen to realize

their winners instead of losers.

The rest 9 answers of the high expertise group are interesting, because they clearly stand out.

First of all, there are relatively few participants who expressed their investment knowledge

being expert-level, or close to one. Only 16,25 % of the participants answered 4 or 5. In

addition to that, all of them have at least a bachelor level education, so they are highly

educated and somehow specialized in investing. The first one to review of this group sold

only winning investments and bought back losers. Worth to mention that he only sold for

52

10 000 euros divided by two of the winners and bought back two of the losers, but there is

clearly a trend. This even flattens out the PGR/PLR, because he gets a value 0, because did

not sell losers at all. The second sold 27 000 worth of winners and 5000 of losers but bought

one of the losers even back for 2000. The rest 30 000 he cashed out, but the majority of it of

winners. His PGR/PLR is over 6, so he realized over 6 times more of his winners than losers.

The third participant continues the trend. She realized 17 000 of her winners and 11 000 of

her losers. In addition to that, she only bought back one share, a loser, for 8000 euros. She

cashed 20 000 out and gets a 1,7 for her PGR/PLR. The next two participants, 4 th and 5th,

realized 0 and 7000 of their winners and the majority of their losers, thus clearly not

exhibiting the disposition effect at all. The 6th and 7th participant continues the trend with the

first three participants. These two have almost identical answers buying back only the losers

and selling their winners. All in all, they sold for 11 000 of their winners and bought back

losers and did not cash out anything at all. A strong sign of the disposition effect.

Furthermore, they also do get a 0 for PGR/PLR, because of not realizing losses at all. The 8 th

participant somewhat diversified his portfolio by dividing the amounts almost equally

between all stocks but concentrated his selling on the loser stocks. A perfectly rational

answer. The last one to review here, the 9th participant sold 17 000 of his winners and only

5000 of his losers. He cashed out 17 000 and bought back a loser for 5000. Again, strongly

backing up the evidence of the literature of the disposition effect by holding on to losers and

realizing winners.

The above chapter in short, 6 of the 13 participants of high investing expertise showed strong

support for the theory of the disposition effect. The stocks they sold were mostly of their

winning stocks, and the stocks they bought back were former losers. But still, the group on

average sold a bit over 3 percentiles more of their losers than winners. When measured in

stocks sold, they even realized more often their winners than losers.

Lower expertise groups do not need so detailed analysis as the high expertise group, because

they are clearly not showing signs of the disposition effect. However, it is worth to have a

look. It is possible to see what is interesting here already in the chart (1), where the groups are

reviewed in comparison. The semi high expertise group is exhibiting stronger DE than the

two low expertise groups. All of the three groups sell more their losers than in winners, both

in monetary amounts and in number of stocks, but there is a clear difference in the magnitude.

Both semi low and low expertise groups have sold in total over 3 times more of their losers

53

than their winners. When measured in number of stocks sold, the difference is almost the

same. However, the semi high expertise group stand out. It is a group of 12 people, almost the

same size as the high expertise group. The semi high expertise group sold their losses for

310 000 euros and their winners for 192 000 euros. There is a clear difference in comparison

to the lower expertise groups. A quick review in their individual answers is worth a while.

There are two persons of the 12 who fully realized all of their stocks, which is rational, but

biases the group answer slightly in favour of getting rid of their losers since there is 6000

euros more in losers. There is another two who fully sold their losing investments and stayed

with some winners or bought even back some. Two participants stayed perfectly with the

initial given portfolio and not contributed to the disposition effect question in neither of

directions. One participant sold all winners and one loser completely and put all 100 000

equally divided in two of the losers; an answer unlikely to be seen in the real world. The rest 5

made slight changes to the initial portfolio in various ways, but the trend is clearly cutting

their losses and staying with winners, except for one answer. All in all, the closer look in to

the individual answers tells a story that the semi high expertise group neither provided strong

support for the disposition effect. Granted, more than the two lower expertise groups, which

very clearly sold in trend most of their losers and kept on with their winners, but there is no

fruitful conclusion about them.

In the end of this chapter, the linear regression modelled from the investor sophistication and

the disposition effect is presented. The results of the regression are shown here in the next

table (7). The far-left column in the table (7) shows the dependent variable, second from left

is independent variable, following by sample size (N), coefficient of determination (R2),

regression coefficient (B) and p-value for statistical significance. The analysis was ran for all

three dependent variables. Independent variables are a nominal variable of investor

sophistication on Likert scale (1-5) and three dummy variables: two from education and one

from gender. The results will be discussed in detail below the table (7).

54

Table 7: A linear regression showing how investor sophistication influences the value of the

disposition effect.

Dependent

variables

Independent

variables N R2 B

p-

valuePGR/PLR 80 0,103

Constant -0,37 0,920Bachelor 0,100 0,796Master -0,217 0,591Male -0,540 0,865Expertise 0,300 0,250

RG/RL-PG/PL 80 0,095Constant -0,931 0,040Bachelor 0,135 0,685Master -0,194 0,575Male -0,003 0,990Expertise 0,296 0,011

SW-SL/SW+SL 80 0,151Constant -0,835 0,000Bachelor 0,08 0,672Master 0,094 0,999Male 0,094 0,542Expertise 0,154 0,017

The first dependent variable in the table (7) is PGR/PLR. The respondents realize more

winning investments than losing investments if the value of PGR/PLR is over 1. Sample size

is 80, as in the other two dependent variables. Coefficient of determination for the first

dependent variable is 0,103, meaning that the independent variables can only explain a few of

the changes in the dependent variable. Expertise, also referred as investor sophistication, is of

interest here. The regression coefficient for expertise in PGR/PLR is 0,300. It implies that the

higher investor sophistication, the higher PGR/PLR. More financially sophisticated

respondents have exhibited more disposition effect than less sophisticated. This is surprising,

but the results are not statistically significant with a p-value of 0,250.

The second dependent variable is RG/RL-PG/PL. It aims to answer the relation between real-

ized gains (RG) and losses (RL) fixed by the available realizations, in other words, paper

55

gains (PG)and losses (PL). This variable might be the best measure for the disposition effect

for this sample, because the resulting value does not depend on the portfolio size. The

division (PG/PL) between paper gains (47000) and losses (53000) in the portfolio used in this

experiment is 0,887, so the result of RG/RL has to be over 0,887 for the respondents to

exhibit the disposition effect. Coefficient of determination for this variable is 0,095.

Regression coefficient is 0,296 with a p-value of 0,011. Also, this variable implies that the

higher respondent’s perceived investor knowledge is, the more they realize their winners

instead of losers. Coefficient of determination is rather low, but the results are statistically

significant.

The third dependent variable is SW-SL/SW+SL. It has the same idea as does the second vari-

able and aims to be independent of the portfolio size. This time, instead of monetary amounts

realized and kept in the portfolio, the analysis concentrates on the times of realizations. SW

stands for sold winner and it does not matter how much of the paper gains is sold. If the re-

spondent sells only 10% of the total amount invested in a stock, he gets 1 sold winner, as he

would if he realized the whole position in the stock. The result of this variable is more than

zero if respondent realize more gains than losses, in other words exhibit the disposition effect

Coefficient of determination for this variable is 0,151. Regression coefficient is 0,154 with a

p-value of 0,017. The third measure of the disposition effect further backs up that the higher

respondent’s perceived investor knowledge is, the more they realize their winners instead of

losers. Coefficient of determination is rather low, but the results are statistically significant.

The second hypothesis is that the higher investor sophistication, the lower is the tendency to

realize winners over losers. This is proven to be false with a statistical significance. The

results are shown in individual answers, as well as in linear regression. The respondents’ who

answered 4 or 5 to the question of their perceived investor knowledge showed by far the

greatest tendency to realize their winners and preferred to keep their losers.

4.2 Gender and the disposition effect

To analyze the difference between genders and the disposition effect, an independent two-

sample t-test in SPSS will be done for all three measures of the disposition effect and two

genders. The results of the analysis are shown here in the next table (8). The whole sample

had 47 males and 33 women. On the far-left column, there are dependent variables, the

56

measures of the disposition effect. The next column is gender, followed by sample size, the

mean value of the dependent variable, the standard deviation, t-test value, p-value showing

statistical significance and the results of F-test. The numbers will be written out after the table

(8).

Table 8: An independent two-sample t-test showing gender differences in the disposition

effect.

N Mean SD t-test p-value F

PGR/PLR 1,296 0,059 3,687

Men 47 0,691 1,397

Women 33 0,357 0,571

RG/RL-PG/PL 1,667 0,106 2,681

Men 47 -0,142 1,213

Women 33 -0,517 0,5176

SW-SL/SW+SL 2,308 0,571 0,324

Men 47 -0,286 0,59

Women 33 -0,575 0,49

The first dependent variable in the table (8) is PGR/PLR. The respondents realize more

winning investments than losing investments if the value of PGR/PLR is over 1. Men have a

mean PGR/PLR 0,691 and women 0,357 with a p-value of 0,059. Although neither of the

genders realize more gains than losses, men tend to realize clearly more. The results are

statistically significant.

The second dependent variable is RG/RL-PG/PL. For further analysis of the variable see the

end of chapter 4.1. Like above with the first dependent variable, men have a higher value of

RG/RL-PG/PL. Men have -0,142 and women -0,517. Also, this measure tells that neither of

the genders realize more gains than losses, but men realize clearly more. Like mentioned

before, this measure is probably better for my sample and according to it, men realize almost

the same amount of gains and losses, whereas women prefer clearly to realize their losses.

The results are statistically significant with a p-value of 0,106. So high value of p is accepted

for statistical significance because of the low sample size.

57

The third dependent variable is SW-SL/SW+SL. For analysis of the variable see again chapter

4.1. Here the balance between genders shifts. This measure implies that men have a higher

ratio of loss realization than women. However, this result is not statistically significant, and

the question remains unanswered.

The first sub-hypothesis claims that women exhibit less of the disposition effect than men. In

this case, neither gender exhibit the disposition effect, but men realize clearly more of their

winners compared to losses than women. Men even almost at a level as described in the

theory of the disposition effect. The first sub-hypothesis is proven true and the results are

statistically significant.

4.3 Education and the disposition effect

To analyze the connection between education and the disposition effect, an analysis of

variance (ANOVA) was done in SPSS for all three measures of the disposition effect and

three education levels. The results of the analysis are shown here in the next table (9). The

whole sample had 13 persons with high school education, 36 persons with bachelor and 31

with master level education. On the far-left column, there are dependent variables, the

measures of the disposition effect. The next column is education level, followed by sample

size, the mean value of the dependent variable, the result of the F-test and finally p-value

showing statistical significance. The numbers will be written out after the table (9).

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Table 9: ANOVA, analysis of variance of education and the disposition effect

N

Mean

F p-value

PGR/PLR 0,516 0,599 High School 13 0,383

Bachelor 36 0,694 Master 31 0,460 RG/RL-PG-PL 0,749 0,476 High School 13 -0,478

Bachelor 36 -0,183 Master 31 -0,393 SW-SL/SW+SL 0,370 0,692 High School 13 -0,526

Bachelor 36 -0,368 Master 31 -0,398

The first dependent variable in the table (9) is PGR/PLR. The respondents realize more

winning investments than losing investments if the value of PGR/PLR is over 1. The level of

education had impact on this variable, F(2,77) = 0,516, p = 0,599. While the results are not

statistically significant, they are still worth to mention. High school level education group had

the lowest PGR/PLR 0,383 following up with master level education, 0,460. The highest

value was among those with bachelor level education, 0,694. None of the education groups

realize more gains than losses, which means that they do not exhibit the disposition effect.

The second dependent variable is RG/RL-PG/PL. The result has to be close to 0 or over it for

the respondents to exhibit the disposition effect. For more detailed explanation of the variable,

see chapter 4.1. High school group has RG/RL-PG/PL -0,478, bachelor group has -0,183 and

the master level education group has -0,393. None of the education groups have positive

value, which means none of the exhibit the disposition effect. Again, we see the highest value

of the disposition effect among bachelor level educated people. High school level and master

level educated has nearly the same value, only slightly lower for high school group. However,

the results are not statistically significant.

The third dependent variable is SW-SL/SW+SL. For more detailed explanation of the

variable, see the chapter 4.1 The level of education had impact on this variable, F(2,77) =

0,370, p = 0,692. The result of this variable is more than zero if respondent realize more gains

59

than losses, in other words exhibit the disposition effect. While the results are not statistically

significant, they are still worth to mention. The results are somewhat similar as in the two

former variables. High school level educated has the lowest value, -0,526. They are followed

by the master level educated, -0,398 and the highest value is again in the bachelor group, -

0,368. None of the groups exhibit the disposition effect. What is different from the two first

variables, is that the master group is closer to the bachelor group than the high school group.

It implies probably that master group made more transactions than the high school group, who

concentrated strongly on realizing the losses.

The second sub-hypothesis claims that education plays no role in the disposition effect. The

results imply that at least high education does not lower the proneness to realize gains. The

lowest educated respondents exhibited the least of the disposition effect clearly. The results

are also not statistically significant, but it seems that the second sub-hypothesis is proven true.

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5 CONCLUSION

On a general level, this thesis argues that humans derive utility and detriment also from

financial transactions, not only from their outcomes. This is contrary to the traditional

economic theory and its cornerstone, the utility function. It is rather unsurprising that people

are not machines capable of analyzing complex financial situations and decisions as a whole

correctly. For simplification and ease of life they divide mental tasks into smaller pieces and

answer them separately, one by one. This facilitation of thought process influences financial

decision-making in an unpleasant way from the perspective of the utility function, and wealth.

To lay the foundation of these statements this thesis uses the disposition effect as an example.

It has been proven both empirically (e.g. Odean, 1998 and Dhar & Zhu, 2006) and

experimentally (e.g. Weber & Camerer, 1998 and Duxbury & Summers, 2012). The causes

for such behavior have been laborious to find. The most discussed reason for the disposition

effect is Kahneman and Tversky’s (1979) sculptured prospect theory and its value function. It

describes that people react differently to gains and losses and get risk averse in the domain of

gains, and risk-seeking in the domain of losses. That has been questioned in explaining the

disposition effect (Kaustia, 2004, Hens & Vleck, 2011 and Barberis and Xiong, 2009). They

argue that prospect theory can explain the disposition effect only in short-term, or the

investors with prospect theory preferences wouldn’t buy the stocks in the first place. An

interesting take on the discussion was made by Duxbury and Summers’ (2012) study when

they introduced emotions into the research of the disposition effect. They claim that the

disposition effect arises when people are responsible of choosing their stocks and feel

regret(pride) over their unsuccessful(successful) investment decisions. By choosing not to

sell, the investor gives himself/herself a chance to break-even with the stock and saves

him/her from feeling regret, yet. In this thesis, the above theory is tested by removing the

responsibility over the investment decisions. This is done in an experimental setting, where

stocks are inherited from a relative. Hence the stocks’ past price performance is not an

achievement of the participants’ decisions and this should keep the participants from falling in

to the disposition effect.

Next the results of the thesis will be compared to empirical and experimental results in the

literature, and answer for the first hypothesis will be provided. Dhar and Zhu (2006) analyze

trading records of a major discount brokerage house, and report an average proportion of

61

winning stocks (PGR) of 0,38 and average proportion of losing stocks sold (PLR) of 0.17 in

their empirical data. Their data exclude trading happened in December, because tax-

considerations have been found out to motivate loss realization at the end of the year. The aim

of excluding December is to show how much investors actually prefer realizing winners.

Their results suggest PGR/PLR of 2,24, meaning that investors realize over twice as much of

their winners compared to losers. The PGR in the experiment of this thesis is 0,2278 and

PLR is 0,5671. The proportions are controversial and also much bigger than observed in the

empirical research. The whole market’s PGR/PLR in this thesis is 0,402 and the individual

average PGR/PLR is 0,5529. The trading in this experiment is more frequent and in higher

magnitudes compared to empirical data. It suggests that people are more willing to make

bigger changes in their portfolio in an experimental setting, which was also initially chosen by

others. Duxbury and Summers (2012) have two versions of their experiment; one with an

inherited stock, and one with respondents choosing the stock. They report PGR of 0,309 and

PLR of 0,243 in the case of inheritance, but claim that the difference is not significant and

conclude that the conditions are not enough to cause the disposition effect. The results of

Duxbury and Summers (2012) seem to imply the disposition effect, but the effect was clearly

stronger when participants were responsible of choosing their stocks (0,309 and 0,105,

respectively). The first hypothesis, that investors do not exhibit the disposition effect if they

do not feel responsibility over choosing the stock, is supported in the results of this thesis.

Investor sophistication was not found to decrease the tendency to realize gains in this thesis.

As mentioned before, the aggregate proportions are not fully satisfying in studying the

disposition effect, because for example investor sophistication (e.g. Dhar & Zhu, 2006, Feng

& Seasholes, 2005, Brown, et al. 2005) have been found to mitigate the disposition effect

exhibited. However, this research provided results implying the opposite. The respondents

were asked in the questionnaire of their own perception of their investment skills on a Likert

scale 1-5, 1 being novice and 5 referring to expert. The participants who answered 4 and 5

were put together in to same group because of their low amount, but the rest 1,2 and 3 were

their own group. The high, and semi high (3) investor sophistication groups had their

PGR/PLR 0,9 and 0,7, showing much stronger tendency in their gain realization than the

average of the whole sample. That is very surprising an inconsistent with the literature.

Actually, when measured in the number of stocks sold, they even realized more of their

winners than losers. 2 of 13 respondents in the high expertise group sold only winners and

bought back losers, thus receiving a PGR/PLR value of 0, further implying a strong tendency

62

of the rest of the group. Two of the high expertise group, as well as some in other groups,

fully realized all their stocks for cash. This is not interpreted as disposition effect, because

there were more losses than gains in the portfolio. Another two divided equally their 100 000

in all six stocks. These answers are fully rational, and do not affect the results of the

experiment. All in all, 6 of the 13 showed strong support for the disposition effect theory.

This was proven to be true in linear regression model with a statistical significance for

dependent variables RG/RL-PG/PL and SW-SL/SW+SL, but not for PGR/PLR. I interpret the

results, as mentioned earlier, that RG/RL/PG/PL is probably the best measure for disposition

effect in this thesis, because it does not depend on the portfolio size. Also, participants who

only realized gains and none of their losses, which happens easily in this kind of experiment

because of the low amount of transactions, have PGR/PLR value 0. The second hypothesis

that higher investor sophistication lowers the tendency for gain realization is not supported as

presented above. Dhar and Zhu (2006), Feng and Seasholes (2005), Brown, et al. (2006) and

Seru, et al. (2010) all find that investor sophistication, especially when measured in number of

trades made, mitigates the disposition effect. It is admitted that no sophistication removes the

tendency to realize gains completely, but in this thesis the results suggest the opposite. The

results might imply, that the gauge used for investor sophistication in this thesis is not

sufficient enough to provide information about experience in trading.

It is difficult to estimate the reasons why people who perceive their skills as the highest, fall

in to a behavioral bias the most. There are not many rational reasons for that. It is tempting to

interpret the answers as belief in mean-reversion, but that theory is robustly debunked in

Weber and Camerer (1998) experimental design of similar fashion. In one phase, the

participants were forced to sell their stocks between periods, and after there was no sign of the

disposition effect. This thesis’ experimental setting is somewhat similar, because the

participants had to write down their answers in completely empty boxes. They clearly had a

tendency to hold on to the losers by their own choice. This is not in line with the background

theory of this thesis, which suggests that investors do not exhibit disposition effect if they

have not chosen the stocks initially themselves (Duxbury & Summers, 2012). What makes

these results even more intriguing, is that these answers came from the top expertise group.

Overconfidence might be the reason behind these answers. The strong sense of their own

skills might be dimming their rational decision-making and make them falsely believe in their

superiority in picking the stocks.

63

The sub-hypothesis, that suggest that women exhibit less of the disposition effect, was

formulated on empirical findings. Men are found to be overconfident, take more risk and trade

more (Lundeberg, et al., 1994, Prince, 1993 and Barber & Odean, 2001). Falling to the

disposition effect is an implication of risk-taking (in the domain of losses) and also an

undirect implication for excessive trading, thus this thesis tests whether there is a difference in

the disposition effect between genders. The first sub-hypothesis is supported, since women

have significantly lower values of the disposition effect. The literature suggests that education

plays no part in the disposition effect, since majority of the investors in the US are well

educated (Alexander, et al., 1998). Results about education are not statistically significant, so

that remains slightly unclear, but at least a difference was not found between education

groups. An interesting notion is that education levels are almost equal between genders, but

the perception of their own skills in investing is not. There is only one female with high

perception of her investment skills compared to 12 men, and females were highly

representative in the very low investor sophistication group. That might be the biggest reason

for the high investor sophistication groups’ strong tendency for holding on to their losses and

realizing their gains.

A clear conclusion drawn from the results of this thesis’ experiment is that the participants do

not exhibit disposition effect when responsibility over the stocks’ past price performance is

removed. That was the first main research question in this thesis. The results give support for

the hypothesis that the fear of regret is needed for the investors to hang on to their losing

investments and a promise of rejoice is needed for the investors to concentrate on realizing

their winners. Despite of the ill-generalizability of a non-probability sample used in the thesis,

the hypothesis seems robust. Surprisingly, the results suggest that the better skilled investors

in the experiment are keener to hang on to their losers and realize their winners by a clear

margin. Higher investor sophistication was not found to mitigate the disposition effect, what

was the second main research question in this thesis. The lower skilled participants made no

mistake in their loss realization and showed strong want to hold on to the past winners. It is

possible that the measure for investor knowledge used in the thesis did not catch correctly the

higher skilled investors, but more confident. Maybe they are overconfident and have high

hopes of themselves in outperforming the market by their superior decision-making and stock

picking. It is difficult to analyze their reasons for such behavior. Literature suggests that men

are trading more and are more overconfident (Lundeberg, et. al, 1994 and Barber & Odean,

2001). A sub-hypothesis that women exhibit less disposition effect than men were formulated

64

on this basis. Men did not exhibit the disposition effect by definition but avoided realizing

their losses much more than women. The last suggestion drawn from literature that high

education itself is not a sign for better performance in investing and clear sophistication in

financial matters is needed for avoiding common pitfalls. There are no clear results in this

thesis to answer that question, but it seems that education plays no part in this.

One aim of the thesis was to contribute to the discussion about the underlying causes of the

disposition effect. The results seem to suggest that one fundamental reason is difficult to point

out. Realization utility does not work on its own, because this thesis’ conditions do not arise

disposition effect. Prospect theory suggests that people consider losses stronger than the

equivalent amount of gains and that leads to loss aversion. That also do not apply in these

circumstances. Mental accounting combined with regret aversion might be the right direction.

When regret is removed, people have no trouble in their loss realization. When pride from

successful investment decisions is available, people are eager to take it. And conversely, when

regret is looming around unsuccessful investment decisions, people seem willing to avoid it.

It implies that people consider their investments separately from each other in mental

accounts and label emotions to individual stocks instead of the success of the whole portfolio.

Thus, the results propose that it might be useful to get one’s investment portfolio reviewed by

another person from time to time. The use of an investment agent is certainly justifiable, but

by having the same investment agent for too long might lead to similar problems. As literature

and the results suggest, investment sophistication mitigates the disposition effect, but do not

remove it completely. The best kind of investment advisor could be the one who is never the

same person in long-term.

For further testing of the hypotheses I suggest better measures for investor knowledge and a

bigger sample. Also, a proxy for overconfidence is highly recommended. Adding another

investing period with changing prices is also needed for better testing the effects of

responsibility over the outcomes. For future research I suggest qualitative methods in

analyzing the reasons for individual’s falling in to the disposition effect. What I consider the

major contribution of this thesis in the field is the bigger portfolio with multiple investment

decisions compared to Duxbury and Summers (2012) setting and a sample with more variety

in backgrounds than only undergraduates. The results in summary support the literature.

65

6 REFERENCES

Alexander, G. J., Jones, J., D. & Nigro, P., J. (1998), “Mutual Fund Shareholders:

Characteristics, Investor Knowledge, and Sources of Information”, Financial Services

Review, 7(4): 301-316.

Allais, M. (1953), “Le Comportement de L'homme Rationnel Devant le Risque: Critique des

Postulats et Axiomes de L'école Américaine”, Econometrica, 21(4): 503-546.

Alvarez, R. M., Sherman, R. P. & VanBeselaere, C. (2002), “Subject acquisition for we-based

surveys”, Political Analysis, 11(1): 23-43.

Bagozzi, R. P., Baumgartner, H., Pieters, R. & Zeelenberg, M. (2000), The Why of

Consumption, pp. 36-58.

Barber, B. M., Lee, Y-T., Liu, Y-J. & Odean, T. (2007), “Is the Aggregate Investor Reluctant

to Realise Losses? Evidence from Taiwan”, European Financial Management, 13(3): 423-

447.

Barber, B. M., Lee, Y-T., Liu, Y-J. & Odean, T. (2009), “Just How Much Do Individual

Investors Lose by Trading?”, The Review of Financial Studies, 22 (2): 609-632.

Barber, B., M. & Odean, T. (2000), “Trading is Hazardous to Your Wealth: The Common

Stock Investment Performance of Individual Investors”, The Journal of Finance, 55(2): 773-

806.

Barber, B., M. & Odean, T. (2001), “Boys Will Be Boys: Gender, Overconfidence and

Common Stock Investment”, Quarterly Journal of Economics, 116(1): 261-292.

Barber, B., M. & Odean, T. (2009), “Do Retail Trades Move Markets?”, The Review of

Financial Studies, Vol. 22, (1): 151-186.

Barber, B., M. & Odean, T. (2011), Handbook of the Economics of Finance, Vol. 2, Part B,

pp. 1533-1570.

66

Barberis, N., Huang, M. & Santos, T. (2001), “Prospect Theory and Asset Prices”, The

Quarterly Journal of Economics, 116(1): 1-53.

Barberis, N. & Shleifer, A. (2003), “Style Investing”, Journal of Financial Economy, 68(2):

161-199.

Barberis, N. & Thaler, R. (2003), Handbook of the Economics of Finance. Vol. 1, Part B, pp.

1053-1128.

Barberis N. & Xiong W. (2009), “What Drives the disposition Effect? An analysis of a

Longstanding Preference-based Explanation.” Journal of Finance, 64(2): 751–784.

Barberis N. & Xiong W. (2012), “Realization Utility”, Journal of Financial Economics,

104(2): 251-71.

Ben-David, I. & Hirshleifer D. (2012), “Are Investors Really Reluctant to Realize their

Losses? Trading responses to Past Returns and the Disposition Effect”, Review of Financial

Studies, 25(8): 2485–2532.

Benartzi, S. & Thaler, R. (1995), “Myopic Loss Aversion and the Equity Premium Puzzle”,

The Quarterly Journal of Economics, 110(1): 73-92.

Brown, P., Chappel, N., Da Silva Rosa, R. & Walter, T. (2006), “The Reach of the

Disposition Effect: Large Sample Evidence Across Investors Classes”, International Review

of Finance, 6(1-2): 42-78.

Carmen, L., Kraeussl, R. & Paas, L. (2012), “The Effect of Anticipated and Experienced

Regret and Pride on Investors’ Future Selling Decisions”. SSRN Electronic Journal.

http://ssrn.com/abstract=1512493

Cioffi, D. & Garner, R. (1996), “On Doing the Decision: Effects of Active versus Passive

Choice on Commitment and Self-Perception”. Personality and Social Psychology

Bulletin, 22(2): 133–147.

67

Chen, G. K., Nofsinger, K., J. & Rui, O. (2007), “Trading Performance, Disposition Effect,

Overconfidence, Representativeness Bias, and Experience of Emerging Market Investors,”

Journal of Behavioral Decision Making, 20(4): 425-451.

Chevalier, J. & Ellison, G. (1999), “Are Some Mutual Fund Managers Better Than Others?

Cross-Sectional Patterns in Behavior and Performance”, The Journal of Finance, 54(3): 875-

899.

Choe, H. & Eom Y. (2009), “The Disposition Effect and Investment Performance in the

Futures Market,” Journal of Futures Markets, 29(6): 496-522.

Chui, M. W. (2001), “An Experimental Study of the Disposition Effect: Evidence from

Macau”, Journal of Psychology and Financial Markets, 2(4): 215-21.

Chui, M. W. (2004), “Further Experimental Studies on the Disposition Effect”, Proceeding of

the International Conference, Asian Finance Association / Taiwan Finance Association / US

Financial Management Association International, Taiwan.

Constantinides, G. (1984), “Optimal Stock Trading with Personal Taxes: Implications for

Prices and the Abnormal January Returns”, Journal of Financial Economics, 13(1): 65–69.

Coval, J. D. & Shumway, T. (2005), “Do Behavioral Biases Affect Prices?” Journal of

Finance, 60(1): 1-34.

Cunha, C. (2011), “Disposition Effect and Asymmetric Volatility of Individual Stocks”,

Proceedings of the 37th Brazilian Economics Meeting 58, ANPEC, Brazilian Association of

Graduate Programs in Economics.

Deaux, K. & Emswiller, T. (1977), “Explanations of Successful Performance on Sex-Linked

Tasks: What is Skill for the Male is Luck for the Female,” Journal of Personality and Social

Psychology, 29(1): 80-85.

Dhar, R. & Zhu, N. (2006), “Up Close and Personal: Investor Sophistication and the

Disposition Effect.” Management Science, 52(5): 726-740.

68

Einiö M., Kaustia M. & Puttonen V. (2008), “Price setting and the reluctance to realize

losses in apartment markets.” Journal of Economic Psychology, 29 (1): 19–34.

El-Khouri, R. (1995), “Predicting Contemporary Volume with Historic Volume at

Differential Price Level: Prospect Theory vs Regret Aversion”, Journal of Administrative

Sciences and Economics, 6: 141-155.

Evans, J., R. & Mathur, A. (2005), “The Value of Online Surveys”, Internet Research,

15(2): 195-219.

Fama, E., F. (1970), “Efficient Capital Markets: A Review of Theory and Empirical Work”,

The Journal of Finance, 25(2): 383-417.

Feng, L. & Seasholes, M., S. (2005), “Do Investor Sophistication and Trading Experience

Eliminate Behavioral Biases in Financial Markets?”, Review of Finance, (9): 305-351.

Frazzini, A. (2006), “The Disposition Effect and Underreaction to News,” Journal of Finance,

61(4): 2017-2046.

Frederick, S. (2005), “Cognitive Reflection and Decision Making”, Journal of Economic

Perspectives, 19(4):2 5-42.

Fricker, R., D., Jr. (2012), The SAGE Handbook of Online Research Methods, pp. 195-216.

Goetzmann, W., N., Kim, D. & Shiller, R., J. (2016), “Crash Beliefs from Investor

Surveys”, Availabe at SSRN: https://ssrn.com/abstract=2750638.

Goetzmann, W., N. & Massa, M. (2008), “Disposition Matters: Volume, Volatility, and Price

Impact of a Behavioral Bias”, The Journal of Portfolio Management, 34(2): 103-125.

Golec, J., G. (1996), “The Effects of Mutual Fund Managers’ Characteristics on Their

Portfolio Performance, Risk and Fees”, Financial Services Review, 5(2): 133-148.

69

Grinblatt, M. & Keloharju, M. (2001), “What Makes Investors Trade?” Journal of Finance,

56(2): 589-616.

Grinblatt, M. & Han, B. (2005), “Prospect Theory, Mental Accounting and Momentum”,

Journal of Financial Economics 78(2): 311-339.

Hens, T. & Vlcek, M. (2011), “Does prospect theory explain the disposition effect?”, Journal

of Behavioral Finance, 12(3): 131-157.

Hong, H. & Stein, J., C. (1999). “A Unified Theory of Underreaction, Momentum Trading,

and Overreaction in Asset Markets”. The Journal of Finance, 54(6): 2143-2184.

Jegadeesh, N. & Titman, S. (1993), “Returns to Buying Winners and Selling Losers:

Implications for Stock Market Efficiency”, The Journal of Finance, 48(1): 65-91.

Kahnman, D. & Riepe, M. (1998), “Aspects of Investor Psychology”, Journal of Portfolio

Management, 24(4): 52-65.

Kahneman, D. & Tversky, A. (1979), “Prospect theory: an Analysis of Decision Under Risk”,

Econometrica, 47(2): 263-292.

Kahneman, D. & Tversky, A. (1982), “Judgment under Uncertainty: Heuristics and Biases”,

Science, New Series, 185(4157): 1124-1131.

Kahneman, D. & Tversky, A. (1982), “The Psychology of Preferences”, Scientific American,

246(1): 160-173.

Kaustia, M. (2004), “Market-wide Impact of the Disposition Effect: Evidence from the IPO

Trading Volume”, Journal of Financial Markets, 7(2): 235.

Kaustia, M. (2010), “Prospect Theory and the Disposition Effect”, Journal of Financial and

Quantitative Analysis, 45(3): 791-812.

Lakonishok, J. & Seymour, S. (1986), “Volume for Winners and Losers: Taxation and Other

Motives for Stock Trading”, Journal of Finance, 41(4): 951–974.

Lee, H.-J., Park, J., Lee, J.-Y. & Wyer Jr., R., S. (2008), “Disposition Effects and Underlying

Mechanisms in E-Trading of Stocks”, Journal of Marketing Research, 45(3): 362-378.

70

Locke, P., R. & Mann. S., C. (2000), “Do Professional Traders Exhibit Loss Realization

Aversion?”, SSRN Electronic Journal. 10.2139/ssrn.251942.

Locke, P., R. & Mann. S., C. (2005), “Professional Trader Discipline and Trade Disposition”,

Journal of Financial Economics, 76(2): 401-444.

Logothetis, N., K. (2008), “What We Can Do and What We Cannot Do with fMRI”, Nature,

Jun 12, 453(7197): 869-878.

Loewenstein, G. (2000), “Emotions in Economic Theory and Economic Behavior”, American

Economic Review, 90(2): 426-432.

Lundeberg, M., Fox, P. & Punccohar, J. (1994), “Highly Confident but Wrong: Gender

Differences and Similarities in Confidence Judgments,” Journal of Educational Psychology,

86(1): 114-121.

Markowitz, H. (1952), “The Utility of Wealth”, The Journal of Political Economy, 60(2):

151-158

Odean, T. (1998), “Are Investors Reluctant to Realize Their Losses?” Journal of Finance

53(5): 1775–1798.

Oehler, A., Heilmann, K., R., Lager, V. & Oberlander, M. (2002) “Dying Out or Dying Hard?

Disposition Investors in Stock Markets”, EFA 2002 Berlin Meetings Presented Paper.

Ofek, E., Richardson, M., (2003), “Dotcom Mania: The Rise and Fall of Internet Stock Pries”,

Journal of Finance, 58(3): 1113-1138.

Prince, M. (1993), ”Women, Men, and Money Styles,” Journal of Economic Psychology”,

14(1): 175-182.

Seru, A., Shumway, T. & Stoffman, N. (2009), “Learning by Trading”, The Review of

Financial Studies, 23(2): 705-739.

Shapira, Z. & Venezia, I. (2001), “Patterns of Behavior of Professionally Managed and

Independent Investors.” Journal of Banking and Finance, 25(8): 1573-1587.

71

Shefrin, H. & Statman, M. (1985), “The Disposition to Sell Winners Too Early and Ride

Losers Too Long”, Journal of Finance, 40(3): 777-790.

Siah, C., Y. (2005), “All that Glitters is Not Gold: Examining the Perils and Obstacles in

Collecting Data on the Internet”, International Negotiation, 10(1):1 15-130.

Statman, M., Thorley, S. & Vorking, K. (2006) “Investor Overconfidence and Trading

Volume”, The Review of Financial Studies, 19(4): 1531-1565.

Staw, B., M. (1976), “Knee-deep in the Big Muddy: A Study of Escalating Commitment to a

Chosen Course of Action”, Organizational Behavior and Human Performance, 16(1): 27-44.

Summers, B. & Duxbury, D. (2012), “Decision-dependent Emotions and Behavioral

Anomalies”, Organizational Behavior and Human Decision Processes, 118(2) :226-238.

Sung, S. (2007), “The Effect of Pride and Regret on Investors’ Trading Behavior”, Wharton

Research Scholars 44, Available at:

https://repository.upenn.edu/wharton_research_scholars/44

Thaler, R. & Shefrin, H. (1981), “An Economic Theory of Self-Control”, The Journal of

Political Economy, 89(2): 392-406.

Thaler, R. (1985), “Mental Accounting and Consumer Choice”, Marketing Science 4(3): 199–

214.

Thaler, R. (1999), “Mental Accounting Matters”, Journal of Behavioral Decision Making,

12(3): 183-206

Tversky, A. & Kahneman, D. (1974), “Judgment Under Uncertainty: Heuristics and biases,

Utility, Probability, and Human Decision Making” Science 27, 185(4157): 1124-1131.

Tversky, A. & Kahneman, D. (1992), “Advances in Prospect Theory: Cumulative

Representation of Uncertainty,” Journal of Risk and Uncertainty, 5(4): 297-323.

Tversky, A. & Kahneman, D. (1991), “Loss Aversion in Riskless Choice: A Reference-

dependent Model”, Quarterly Journal of Economics, 106(4): 1039-1061.

72

Weber, M. & Camerer, C., F. (1998), “The Disposition Effect in Securities Trading: An

Experimental Analysis,” Journal of Economic Behavior and Organization 33(2):167-184.

Zeelenberg, M., van Dijk, W., W., Manstead, A., S., R. & van der Pligt, J. (1998). “The

Experience of Regret and Disappointment”. Cognition and Emotion, 1(2): 221-230.

Zeelenberg, M., van Dijk, W., W., Manstead, A., S., R. & van der Pligt, J. (2000). “On Bad

Decisions and Disconfirmed Expectancies: The Psychology of Regret and Disappointment”.

Cognition & Emotion, 14: 521-541.