Implication of Bf

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International Research Journal of Finance and EconomicsISSN 1450-2887 Issue 66 (2011) EuroJournals Publishing, Inc. 2011http://www.eurojournals.com/finance.htm

Interaction between Demographic and Financial Behavior

Factors in Terms of Investment Decision Making

Suleyman Gokhan Gunay

Faculty of Economics and Administrative Sciences, Department of Business Administration

Trakya University, Balkan Yerleskesi 22030 Edirne/Turkey

E-mail: [email protected]: +90-284-2357151; Fax: +90-284-2357363

Engin Demirel

Faculty of Economics and Administrative Sciences, Department of Business Administration

Trakya University, Balkan Yerleskesi 22030 Edirne/Turkey

E-mail: [email protected]: +90-284-2357151; Fax: +90-284-2357363

Abstract

The purpose of this study is to show that there is an interaction betweendemographic and financial behavior factors in investment decisions. It is found that genderhas interaction with five of the financial behavior factors (overreaction, herding, cognitivebias, irrational thinking, and overconfidence). The second finding of our study is that thelevel of individual savings has an interaction with four of the financial behavior factors(overreaction, herding, cognitive bias, and irrational thinking). Based on these findings, it

would not be wrong to argue that gender and savings level are effective demographicfactors that interact with behavioral finance factors in investment decisions. On the otherhand, no interaction is found between age and behavioral finance factors in this study.Finally, it is also found that behavioral finance factors are effective in individualsinvestment decisions.

Keywords: Behavioral Finance, Demographic Factors, Herding, Overreaction, CognitiveBias, Irrational Thinking, Overconfidence, Media Effect

1. IntroductionBehavioral finance is concerned with psychological influences in financial decision making andmarkets. Investors make decisions while staying afloat in a sea of uncertainty. When predictability islow, people may be prone to unjustified beliefs that may survive and even flourish in such anenvironment (Kyle and Wang, 1997; Benos, 1998; Gervais and Odean, 2001; Hirshliefer and Luo,2001).

Lintner (1998) defines behavioral finance as being the study of how humans interpret and acton information to make informed investment decisions. According to Olsen (1998), behavioral financedoes not try to define rational behavior or label decision making as biased or faulty; its purpose is tounderstand and predict systematic financial market implications of psychological decision processes.


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Decision making related with behavioral finance, can be defined as the process of choosing aparticular investment alternative from a number of alternatives. It is an activity that follows afterproper evaluation of all the alternatives (Mathews, 2005). Many investors have, for long consideredthat psychology plays a key role in determining the behavior of markets. Paul Slovics (1972) study onindividuals misperceptions about risk and Amos Tversky and Daniel Kahnemans studies (1974) onheuristic driven decision biases and decision frames (Kahneman and Tversky,1979) have played aseminal role in behavioral finance. The results of these studies are in conflict with the rational, self-

interested decision-maker posited by traditional finance and economics theory.Fama (1980) and Lazear and Rosen (1981) are among the first supporters of the idea that

investment decision might be influenced by career concerns. Smith and Goudzwaard (1970) havesurveyed the relevance of education to the practical investment management and found a gap betweenteaching and practice. Literature focuses on herding due to signal congestion between different types ofmanagers (Scharfstein and Stein, 1990) and due to inefficient information transmission (Banerjee,1992; Bikhchandani et al. 1992). Chevalier and Ellison (1997) emphasized that career issues ofinvestors play a significant role in their decisions about risk.

Loss aversion is another important psychological concept which receives increasing attention ineconomic analysis. The investor is a risk-seeker when faced with the prospect of losses, but is risk-averse when faced with the prospects of enjoying gains. This phenomenon is called loss aversion

(Venkatesh, 2002). Ulrich and Zank (2005) discuss the loss aversion theory with risk aversion andaccept the Kahneman and Tversky views. Loss aversion and risk taking require all the investors avoidtheir losses and protect their investments. As noted by Thaler and Shefrin (1981), investors are subjectto temptation, and they look for tools to improve self control.

Baker and Nofsinger (2002) have also examined the common investment mistakes and andgrouped these mistakes into two categories in their study. They have tried to find how investors thinkand feel during financial decision making processes. In addition, they have discussed the social factorsthat affect financial decisions. According to this study, investors often have difficulty on identifyingthe psychological habits that affect their financial decisions. Investors can establish realistic investmentobjectives in terms of their return requirements and risk tolerances in order to reduce the influence ofpsychological biases. Investors can avoid investing on emotional rumor, and stories or other

psychological biases in order to develope a set of quantitative investment criteria.Proper diversification on financial investment decisions can help investors extreme loses and

shield them against the psychological biases. Brinson et. al. (1991) and Ibbotson and Kaplan (2000)indicate that main portion of overall investment returns arise from log term asset allocation decisions.One of the finding of these financial behavior research on decision making is that investors shouldperiodically review and keep track of their investments and also compare their investment to specificinvestment goals.

2. Literature Review on Financial Behavior FactorsThis study includes six main variables in order to explain financial behavior factors on investment

decision making. These are overreaction, herding, overconfidence, media effect, irrationality orrational thinking, and preconception.

2.1. Overreaction

Overreaction is a term, which states that investors overreact to some news, such as news abouteconomy, politics or companies. Overreaction refers to predictability of good and bad future returns ofinvestment by comparing them with the returns of past performance (De Bondt and Thaler, 1985;Lakonishok et. al., 1994). Overreaction includes investment decision strategies that sort on proxies forrecent performance in a given direction (Braw and Heaton, 2002). Daniel et. al. (1998) have developeda model on overreaction and underreaction from investors overconfidence in their private signals and


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149 International Research Journal of Finance and Economics - Issue 66 (2011)

their biased updating in the light of public information. Another model about overreaction andunderreaction is developed by Barberis et. al. (1998). They have found the same anomalies with arepresentative investor subject to two cognitive biases. Hong and Stein (1999) have also evaluatedoverreaction and underreaction, and modelled the interaction of investors who idealistically fallowprice trends in their research.

2.2. Herding

There are many specific studies about herding behavior. As defined by Graham (1999) the herdingbehavior is often said to occur when many people take the same action, perhaps because some mimicthe actions of others in making investment. Herding has been theoretically linked to many economicactivities, such as investment recommendations (Scharfstein and Stein, 1990). The herding behaviorcan be subdivided into three types (Devenow and Welch, 1996); 1) informational cascades, 2)reputational herding, and 3) investigative herding. An individual may choose to mimic the action of thecrowd rather than acting on his private information. If this scenario holds for one individual, then italso holds for anyone acting after this person. This domino-like effect is often referred to informationcascade (Graham, 1999). Reputational herding takes place when an agent chooses to ignore his or herprivate information and mimic the action of another agent who has acted previously (Prendergast andStole, 1996). Investigative herding means that obtaining information is only worthwhile when othersalso procure this information (Spiwoks et. al, 2008)

2.3. Overconfidence

According to studies about overconfidence, investors expect good things to happen to themselves moreoften than to their peers (Weinstein, 1980; Kunda, 1987). When some investors overestimate theirability to do well on investment decisions, there exists overconfidence. These overestimates increasewhen the situation is perceived to be controllable (Weinstein, 1980), and when it is of personalimportance (Frank, 1935). In addition to these studies, Gervais et. al. (2003) investigate the positiverole of overconfidence and optimism in investment policy. Bernardo and Welch (2001) has a study onthe evolution of overconfidence, and Oskamp (1965) has case study judgment on overconfidence.

2.4. Media Effect

Media is an important factor that may effect financial behaviors of individuals in making theirinvestment decisions. The media effect on investment decision making is discussed on Clark et. al.(2004). Stock prices effect on news coverage is studied by Cutler et. al. (1989). Tetlock (2007) hasstudied the role of media pessimism as a forecasting factor on investor sentiment. Tetlock has foundthat timing and media pessimism has important role on investment decisions. On the other hand,Engelberg and Persons (2011) compared the behaviors of investors with access to different mediacoverage of the same information events.

2.5. Irrationality

There are many studies about the experimental psychology on irrationality of human decision-makingin financial markets (Bazerman, 1998; Hogarth, 1987; Russo and Schoemaker, 1991). Also the study ofHilton (2001), briefly considers the sources of collective irrationality that may further plague financialdecision-making and investigates on financial decisions that has irrational choices on investors riskaversion.

2.6. Cognitive Bias

In the search on decision making under uncertainty individuals and investors mainly select one ofknown set of alternative choices with certain outcomes. This is mentioned in detail by the study ofSamuelson and Zeckhauser (1998). Previous research suggests that this bias is quite pervasive among


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non-experts but there is very scant evidence of its intensity among experts also (Olsen, 1997). Thetendency of the investors is to make their decisions based on past their experiences. De bondt (1998)indicate that analyses are biased in the direction of recent success or failure in investors earningsforecasts, the characteristic of stereotype decisions.

3. Literature Review on Demographic Factors

There are many aspects and literature on interaction between demographic factors and behavioralfinance related with investment decision making. Gender is one of these demographic factors.Psychological research demonstrates that men are more overconfident than women in areas such asfinance. Thus, it is predicted that men will trade more excessively than women investors (Barber andOdean, 2001). Age is another demographic factor that affects investment decision making. Forexample, Korniotis and Kumar (2011) have examined the older investors about their investmentdecisions. Davis and Chen (2008) concluded that all predictors were significant predictors of theinvestment. In this study, although age differences on amount of investment were not significant,interactions between participant age and vignette information are found. Results of the study indicatethat older and younger adults make similar decisions using different pieces of information.

Felton et. al. (2003) have studied the effect of gender and optimism on the riskiness of

investment choices of sixty-six students in a semester long investment contest with both monetary andacademic incentives. They have concluded that males make more risky investment choices thanfemales, and that this difference was primarily due to the riskier choices of optimistic males. Inaddition, males demonstrated greater variability in final portfolio value than did females in this study.The findings in this study suggest three main points; 1) the well documented gender difference ininvestment strategies of men and women may be due to a specific subgroup of males 2) optimism maylead to different behavioral tendencies in men and women depending on the domain; and 3) thebenefits of optimism may be restricted to domains in which continued effort and information seekingare likely to lead to desired outcomes.

4. Methodology and Hypotheses of the StudyWe have developed eighteen hypotheses related with the interaction of demographic and financialbehavior factor. These hypothesis are as follow:

H1: Gender and overreaction has an effect on financial behavior.H2: Gender and herding has an effect on financial behavior.H3: Gender and overconfidence has an effect on financial behavior.H4: Gender and media has an effect on financial behavior.H5: Gender and irrational thinking has an effect on financial behavior.H6: Gender and cognitive bias has an effect on financial behavior.H7: Age and overreaction has an effect on financial behavior.H8: Age and herding has an effect on financial behavior.H9: Age and overconfidence has an effect on financial behavior.H10: Age and media has an effect on financial behavior.H11: Age and irrational thinking has an effect on financial behavior.H12: Age and cognitive bias has an effect on financial behavior.H13: Individual savings level and overreaction has an effect on financial behavior.H14: Individual savings level and herding has an effect on financial behavior.H15: Individual savings level and overconfidence has an effect on financial behavior.H16: Individual savings level and media has an effect on financial behavior.H17: Individual savings level and irrational thinking has an effect on financial behavior.H18: Individual savings level and cognitive bias has an effect on financial behavior.


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The first set of hypotheses (H1 H6) show the effect of the gender on six financial behaviorfactors (overreaction, herding, overconfidence, media, irrational thinking, cognitive bias). The secondset of six hypotheses (H7 H12) show the effect of the age on financial behavior factors. Finally, theeffect of individual savings level to behavioral finance factors in investment decision making is shownin the third set of six hypotheses (H13 H18). The study is conducted in Edirne city, Turkey. Aquestionnaire is developed and seventeen questions are asked to the respondents based on theseeighteen hypotheses. Three of these questions are about demographic factors and fourteen of these

questions are about financial behavior factors. The questionnaire is distributed to 397 respondents.

5. The Findings of the StudyFirst, cronbach alpha is calculated in the analysis. The result of cronbach alpha is 71% for the sixfinancial behavior factors. Second, normality tests are conducted about financial behavior factors. Ascan be seen in Table 1, none of the variable shows normality based on Kolgomorov-Smirnov test.

Table 1: Test of Normality for the Financial Behavior Factors

Kolmogorov-Smirnova

Statistic df Sig.

Media Effect ,189 396 ,000Cognitive Bias ,181 396 ,000Irrational Thinking ,152 396 ,000Overreaction ,082 396 ,000Herding ,151 396 ,000Overconfidence ,117 396 ,000

Since financial behavior factors do not show normal distribution, a non-parametric test(Kruskal-Wallis) is used in the study. It is found that gender has interaction with five of the financialbehavior factors (overreaction, herding, cognitive bias, irrational thinking, and overconfidence). In allof these findings, male respondents use more behavioral finance factors than females in theirinvestment decisions. It is also found that the level of individual savings has an interaction with four of

the financial behavior factors (overreaction, herding, cognitive bias, and irrational thinking). On theother hand, no interaction is found between age and financial behavior factors. In all of these findings,Kruskal-Wallis test results are significant at the 1% and 5% levels. As a result, nine of the hypothesesare accepted and nine of them are rejected.

The interaction between gender and overreaction can be seen in Table 2. As can be seen inTable 2, male respondents show more overreaction than female respondents in investment decisionmaking.

Table 2: The Interaction Between Gender and Overreaction

Gender N Mean Rank

Overreaction

Female 154 180,64

Male 242 209,87Total 396

The interaction between gender and herding can be seen in Table 3. As can be seen in this table,male respondents show more herding behavior than female respondents in their investment decisions.

Table 3: The Interaction Between Gender and Herding

Gender N Mean Rank

Herding

Female 154 182,59Male 243 209,40

Total 397


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Male respondents show more cognitive bias than female respondents in their investmentdecisions. This result can also be seen in Table 4.

Table 4: The Interaction Between Gender and Cognitive Bias

Gender N Mean Rank

Cognitive Bias

Female 154 183,98

Male 243 208,52

Total 397

There is also interaction between gender and irrational thinking, which can be seen in Table 5,in investment decisions.

Table 5: The Interaction Between Gender and Irrational Thinking

Gender N Mean Rank

Irrational Thinking

Female 154 182,26Male 243 209,61

Total 397

Finally, there is an interaction between gender and overconfidence behavior, which can be seenin Table 6. Based on these five significant findings, it would not be wrong to argue that gender affectall of the financial behavior factors in individuals investment decisions with the exception of mediaeffect.

Table 6: The Interaction Between Gender and Overconfidence

Gender N Mean Rank

Overconfidence

1,00 154 184,23

2,00 243 208,36

Total 397

Individual saving levels are categorized into five sections. The interaction between individual

saving levels and overreaction can be seen in Table 7. As the level of individual savings increases, sodoes overreaction. In other words, there is a positive relationship between the level of individualsavings and overreaction.

Table 7: The Interaction Between Individual Savings and Overreaction

Individual Savings N Mean Rank

Overreaction

None 141 175,30

0-$150 139 205,00

$151-$450 86 214,19

$451-$900 27 223,31

$900-Above 3 314,83

Total 396

As can be seen in Table 8, herding behavior is in the maximum for the fourth group ($451-$900) and minimum for the first group (0-$150).

Table 8: The Interaction Between Individual Savings and Herding


Herding

None 141 180,98

0-$150 140 205,81

$151-$450 86 196,05

$451-$900 27 263,28

$900-Above 3 234,17

Total 397


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As can be seen in Table 9, cognitive bias behavior is in the maximum level for the fifth group($900-Above) and minimum level for the first group (0-$150). There is a positive relationship betweenthe individual savings level and cognitive bias behavior with the exception of fourth group ($451-$900).

Table 9: The Interaction Between Individual Savings and Cognitive Bias


CognitiveBias

None 141 180,00

0-$150 140 198,43

$151-$450 86 223,55

$451-$900 27 219,24

$900-Above 3 232,83

Total 397

Table 10: The Interaction Between Individual Savings and Irrational Thinking


Irrational Thinking

None 141 167,66

0-$150 140 212,91

$151-$450 86 228,90

$451-$900 27 186,20

$900-Above 3 280,83

Total 397

There is a positive relationship between the individual saving level and cognitive bias behaviorwith the exception of the fourth group ($451-$900). As can be seen in Table 10, irrational thinkingbehavior is in the maximum level for the fifth group ($900-Above) and minimum level for the firstgroup (0-$150). Although findings about the interaction of individual savings and behavioral financefactors do not increase constantly, it is very clear that there is difference among groups of saving levelsin terms of irrational behavior.

6. ConclusionThe first finding of our study is that gender is an important factor in financial behavior. It is found thatmale respondents have tendency to show more financial behavior than female respondents in theirinvestment decisions. Gender has an interaction with five of the financial behavior factors(overreaction, herding, cognitive bias, irrational thinking, and overconfidence). This finding is parallelto the other studies findings in behavioral finance. The second finding of our study is that individualsavings level also affects financial behavior factors in investment decisions. The level of individualsavings has an interaction with four of the financial behavior factors (overreaction, herding, cognitivebias, and irrational thinking). There is a positive relationship between the level of individual savings

and overreaction. Although the same positive relationship could not be found between individualsavings and three financial behavior factors (herding, cognitive bias, and irrational thinking), savinglevel significantly affects financial behavior in investment decision making. Finally, it is found thatthere is no interaction between age and six financial behavior factors (overreaction, herding, cognitivebias, irrational thinking, overconfidence and media effect). Based on these findings, it would not bewrong to argue that gender and savings level are effective demographic factors that interact withbehavioral finance factors in investment decision.

The purpose of this study is to show that there is an interaction between demographic andfinancial behavior factors. This main hypothesis is proved with the exception of one demographicfactor, age. The other aim of this study is to show that behavioral finance is effective in investmentdecision making. This hypothesis is also proved due to the adequate level of cronbach alpha (reliability


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level). In sum, this study has shown that six behavioral finance factors and two demographic factorsinteract with one another in individuals investment decisions.

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Implication of Bf