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}{% \vskip8pt \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt } \usepackage[absolute,overlay]{textpos} \makeatother \usepackage{lineno} \linenumbers \begin{document} \author[1]{Dr. Tarika Singh} \affil[1]{ Prestige Institute of Management} \renewcommand\Authands{ and } \date{\small \em Received: 7 February 2015 Accepted: 3 March 2015 Published: 15 March 2015} \maketitle \begin{abstract} Financial Theories say that Investor should act rationally. Emotions do have a powerful impact on everyday decisions we make. They not only shape behavior but also affect every decision taken by an individual. Similarly regret is the most common phenomena observed in individuals especially when they take investing decisions. In the present study researchers have tried to find out influence of Investor Psychology on Regret Aversion by using General Linear Model. The results are useful in Indian context. \end{abstract} \keywords{regret aversion, risk, investor psychology.} \begin{textblock*}{18cm}(1cm,1cm) % {block width} (coords) \textcolor{GJBlue}{\LARGE Global Journals \LaTeX\ JournalKaleidoscope\texttrademark} \end{textblock*} \begin{textblock*}{18cm}(1.4cm,1.5cm) % {block width} (coords) \textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}} \end{textblock*} \let\tabcellsep& \section[{I. Introduction}]{I. Introduction}\par ue to the Liberalization, Globalization and Privatization financial sector is also progressive at a very fast pace and due to which question arising is of what is the effect the investors' psychology on the regret aversion. It is very difficult for investor to take decision and survive in this highly competitive economic world as well s for organizations coming up with financial products. If they are unable to comprehend the investor psychology on regret aversion, they will fail.\par The Investor psychology is the scientific study of investor mind and behavior. Psychology is the study of the human brain including people's behaviors, attitudes, feelings and personality. Investors, like any decision maker, feel regret when they compare the outcome of an investment with what the outcome would have been they invested differently. To take any good decision investor check positives and negatives of each option, and consider all the alternatives.\par Regret Aversion in simple words is the trend to avoid making decision due to the fear of experiencing the hurt of regrets. investor avoid taking decisive actions due to regret aversion because they fear that, in perception, whatever course they select will prove less than optimal. Essentially, this bias seeks to forestall the pain of regret associated with poor decision making. There is a role of regret aversion in decision making. Specifically, it examines how regret aversion influences decision process, choice, and post-decisional behaviors and feelings most investors are familiar with the painful pangs of regret resulting from negative Consequences of a decision, such as receiving a bad grade after not studying, losing money after making a stupid investment, or feeling frustrated after taking the wrong decision about investment. Regret is considered an important negative emotion.\par This research focuses on influence of investor psychology on regret aversion. This study examined investors' decisions to realize gains and losses in the any kind of financial decision they make. Specifically, the attention is focused on the different gender, age, qualification and Income. \section[{II. Regret Aversion}]{II. Regret Aversion}\par Bell, Loomes \& Sugden (1982) came up with very first definition of regret aversion and said that it motivates individuals to engage in decision behaviors and choices that avoid future regret, for example, by choosing the option for which the least regret is expected. Later, \hyperref[b28]{Shefrin and Statman (1985)} suggested that regret aversion is an emotional feeling associated with the ex post knowledge that a different past decision would have fared better than the one chosen, as one of the factors leading to the disposition effect. \hyperref[b24]{Samuelson and Zeckhauser (1988)} said regret aversion refers to the phenomenon that people keep the status quo because they know from experience that options that seem to be favorable given the apparently correct information at the time the decision is to be made, may later turn out to be less favorable than previously assumed.\par Baber and {\ref Odean (1999)} suggested investors want to avoid regret. When investors hold the paper gains stock, investors worry about the stock price will fall, so investors sell paper gains stock to become realized gains. Conversely, when investors ride the paper losses stock, investors will expect the stock price will go up in the future, so they will ride the loss stock. Regret Aversion can be only put as the tendency to avoid making decision due to the fear of experiencing the pain of regrets. People demonstrate regret aversion avoid taking decisive actions because they fear that, in hindsight, whatever course they select will prove less than optimal. Essentially, this bias seeks to forestall the pain of regret associated with poor decision making. Each word has its own meaning. \section[{III. Relationship between Disposition}]{III. Relationship between Disposition}\par Effect and Regret Aversion \hyperref[b20]{Shiller (2000)} argued that regret theory may apparently help explaining the fact that investors defer the selling of stocks that have gone down in value and accelerate the selling of stocks that have going up in value. Since the fear of regret leads investors to postpone losses, symmetrically, the desire for pride leads to the realization of gains. In short it can be inferred that investors might feel regret when they realize a loss, and, conversely, feel pride when they realize a paper gains. \section[{IV. Investor Psychology}]{IV. Investor Psychology}\par Elliott (1930) developed the Elliott wave theory.\par Through use of sophisticated measurements that he called "wave counting," a wave theorist could forecast market turns with a high degree of accuracy. Further, Sun1 and Hsiao (1983) proposed Prospect Theory.\par Prospect theory to explain how decision makers actually behave when confronted with choice under uncertainty and formalizes an S-shaped value function to substitute for expected utility function of expected utility theory.\par Weber \& Camerer (1998) found evidence of disposition affect in experimental market by pooling investor responses and analyzing buy and sale trends of sis risky assets. They argued that this was a construct of investor being risk averse with winnings, and risk seeking with losses with the purchase price as the reference point.\par Traditional economic modeling assumes that people make decisions rationally, taking into account all available information (adjusted for the cost of gathering and analyzing the information). However, increasing evidence suggests that people's decision making is influenced by certain behavioral biases and has led to a growing body of work investigating the impact of these biases on financial markets.\par The impact of psychology can be clearly seen in investor behavior, such as "herding". This can lead to bubbles and crashes and fear of regret, for example, where investors avoid selling a poorly performing investment because they do not want to admit to having made a bad decision to begin with. \section[{V. Relationship between Investor Psychology and Regret Aversion}]{V. Relationship between Investor Psychology and Regret Aversion}\par Investor psychology is the mental conflict that people experience when they are presented with evidence that their beliefs or assumptions are wrong; as such, cognitive dissonance might be classified as a sort of pain of regret, regret over mistaken beliefs. As with regret theory, the theory of regret aversion goes parallel. \hyperref[b7]{Festinger (1957)} asserts that there is a tendency for people to take actions to reduce cognitive dissonance that would not normally be considered fully rational: the person may avoid the new information or develop contorted arguments to maintain the beliefs or assumptions. There is empirical support that people often make the errors represented by the theory of cognitive dissonance. McFadden (1974) modeled the effect of cognitive dissonance in terms of a probability of forgetting contrary evidence and showed how this probability will ultimately distort subjective probabilities.\par Goetzmann and Peles (1993) have argued that the same theory of cognitive dissonance could explain the observed phenomenon that money flows in more rapidly to mutual funds that have performed extremely well than flows out from mutual funds that have performed extremely poorly: investors in losing funds are unwilling to confront the evidence that they made a bad investment by selling their investments. \section[{VI. Literature Review}]{VI. Literature Review}\par Recent literature in empirical finance is surveyed in its relation to underlying behavioral principles, principles which come primarily from psychology, sociology and anthropology. In a study of verbal expressions of emotions, \hyperref[b30]{Shimanoff (1984)} found that regret was the most frequently named negative emotion, attitudes toward regret are mainly favorable versus unfavorable, whether individuals are self-serving in their ascription of regret experiences, and which beneficial functions people ascribe to regret versus other negative emotions. Although previous research has offered comparative profiles of various specific emotions in terms of psychology, intensity, or duration the present research is the first to benchmark regret against other common emotions in terms of these basic evaluations.\par Lankman {\ref (1993)} Shefrin and Statman, (1985) examined the influences of overconfidence, mental accounting, regret aversion and self-control on the disposition effect of selling winners too early and holding losers too long. The findings show that (1) overconfidence, mental accounting and self-control positively influence the disposition effect, and (2) self-control negatively influences the disposition effect. As predicted, self control can reduce irrational behavior of investor. \hyperref[b36]{Zeelenberg (1999b)} and \hyperref[b23]{Roese (2005)} found regret can tell us that we could have done better by choosing a different option. The regret experienced after trusting an untrustworthy leader, losing money in a phony investment, cheating on one's spouse, or not blowing the whistle about corporate wrong -doing is likely to increase the probability of better choices in the future. By making better choices, in turn, decision makers should experience less regret. Thus, being willing to experience regret in the short -run might lead to better choices and less future regret. \hyperref[b31]{Simonson (1989)}; \hyperref[b32]{Slavic (1975)} studied the effects of decision making and explained as the result of decision makers, tendency to make easily justifiable reason-based choices. All violate certain normative principles of choice. However, as a pretest showed, the justifications underlying the effects are not all are considered equally unreasonable.\par Janis and Mann (1977) said that anticipatory regret might again lead to increased information purchase and, as a consequence, lead to worse overall monetary payoffs. The results show that making regret salient led to less rather than more information search under these conditions. It appears, then, that anticipatory regret did not lead to "mindless" information collection with the purpose of providing a justification that could protect the decision maker if the choice outcome turned out to be bad. Bell, Loomes \& Sugden, (1982) {\ref Zeelenberg (1999)} said that investor psychology is the pre-choice decision process. The results told that increasing anticipatory regret can, in some circumstances, lead to better, more heedful decision making.\par Larrick \& Boles (1995) suggested that decision makers' tendency to seek feedback is actually much stronger than the tendency to avoid feedback when both options are equally effortless and costless to implement and regret is not particularly salient. However, once regret is more salient, feedback avoidance increases substantially and bad decision making increases as well.\par Subash (2011/2012) founds investors who are participating in the Indian Stock Market is rational at all times. The work focuses on nine identified behavioral biases, namely: Overconfidence, Representativeness, Herding, Anchoring, Cognitive Dissonance, Regret Aversion, Gamblers' Fallacy, Mental Accounting and Hindsight Bias. Effects of these nine factors on the decision making process of portfolio investors in Kerala, India has been analyzed in this study. The influence has primarily been analyzed in terms of whether behavioral factors affect the investors' decision to buy sell or hold stocks.\par Barber and Odean (2001) partitioned investors based on gender and, based on the previous psychological research fact that men are more overconfident than women, tested the theory that overconfident investors trade excessively. They document that men trade 45\% more than women, and find that men's net returns were cut by 2.5\% a year while it was 1.72\% for women, in data gathered from 1991 through 1997. Samuelson and Zeckhauser (1988) said regret aversion is closely linked to the theory of omission bias, which holds that people perceive harmful commissions as worse than corresponding omissions and, therefore, prefer omission to commission.\par Ritov and Baron (1992) said selection of an alternative also means commitment to the alternative. Psychological commitment claims behavior on behalf of a position, as a change may damage self-esteem. When a poor decision is undeniable to ourselves, the natural survival instinct is to downplay the importance of the event or change the way we think about the outcome altogether. That is, we change the reference point from which the outcome is evaluated.\par Wang, Zhoa, Chan, and Chau (2000) demonstrated that developers become over-confident and that their over-confidence leads to over-building. These actions are found to cause excessive volatility in the real estate sector and even affect real estate cycles.\par Hirshleifer, Subrahmanyam, \& Titman (1994) experimental and empirical evidence show individual in groups abides the group decision, even when they perceive the group to be wrong. Individual suppresses their own beliefs and relies on their investment decision solely on the collective action, even though they disagree with the prediction. \section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par Volume XV Issue II Version I Year ( ) C \hyperref[b25]{Savage's (1951)} told that regret rule for decision making under ignorance. The absence of any knowledge about the probabilities with which different states of the world occur and that was perhaps the first formulation of a decision rule that seeks to minimize the regret for having chosen the relatively worse option. \hyperref[b35]{Zeelenberg (2002)} found further direct evidence for the role of having good reasons for one's choice.\par They studied regret after consumer decisions based on more or less convincing reasons and found that regret was more intense after unreasonable choices such as switching to a different product when the product performed well in the past, or not switching when it performed badly. \hyperref[b21]{Reb and Connolly (2005)} justified of the decision process may be of even stronger importance for the experience of regret. In the series of scenariobased studies, tested the effect of decision process quality on anticipated regret.\par Based on the above extensive review of literature the objectives of the study were formulated to carry out a study on Investor Psychology and Regret Aversion in Indian context. The review was used as base for questionnaire preparation too.\par VII. Objectives 1. To design, develop and standardize a measure to evaluate Investor Psychology. 2. To design, develop and standardize a measure to evaluate Regret Aversion. \section[{To find out the underlying factors of Investor}]{To find out the underlying factors of Investor}\par Psychology and Regret Aversion. 4. To find out differences between male and female Investors on Psychology and Regret Aversion. 5. To find out the causal relationship between Investor Psychology and Regret Aversion. 6. To open new vistas for further study. \section[{VIII. Research Methodology}]{VIII. Research Methodology}\par The study was exploratory in nature and survey was used to complete it. Population subsumed the entire Investors of Gwalior region. Since there was no list of existing investors of Gwalior region, no sampling X. Tools used for Data Analysis \section[{IX. Tools used for Data Collection}]{IX. Tools used for Data Collection}\par For the purpose of data collection, a standardized questionnaire was used as a base \hyperref[b6]{(Marcatto and Ferrante, 2008)}. The same was restandardized again in Indian context. Responses were solicited on Likert-type scale 1 to 5, where 1stands for minimum agreement and 5stands for maximum agreement would be used. \section[{Reliability Statistics of Regret Aversion}]{Reliability Statistics of Regret Aversion} \section[{KMO and Bartlett's Test}]{KMO and Bartlett's Test}\par Further KMO Bartlett's test was used for sample adequacy. The results are discussed in table below.\par The Kaiser Meyer Olkin Measure of Sampling Adequacy value was 0.718 indicating that the sample was adequate to consider the data as normally distributed. The Bartlett's Test of Sphericity tests the null hypothesis that the item-to-item correlation matrix was an identity matrix. The hypothesis was tested through c) Chi-Square test; the value of Chi-square was found to be 1242.851, which is significant at 0\% level of significance. Therefore, null hypothesis is rejected; indicating that the item-to-item correlation matrix is not an identity matrix and is therefore suitable for factor analysis.\par Principle component factor analysis with Varimax rotation and Kaiser Normalization was applied. The factor analysis resulted in \hyperref[b5]{4} The Kaiser Meyer Olkin Measure of Sampling Adequacy value was 0.737 indicating that the sample was adequate to consider the data as normally distributed. The Bartlett's Test of Sphericity tests the null hypothesis that the item-to-item correlation matrix was an identity matrix. The hypothesis was tested through Chi-Square test; the value of Chi-square was found to be 283.761, which is significant at 0\% level of significance. Therefore, null hypothesis is rejected; indicating that the item-to-item correlation matrix is not an identity matrix and is therefore suitable for factor analysis. R-20. I am always prepared to take a gamble.\par . the assumption of homogeneity of covariance across the groups using p < .001 as a criterion. Here, we do not have a concern -as Box's M (84.79) was not significant, p (.072) > (.001) -indicating that there are no significant differences between the covariance matrices. Therefore, the assumption is not violated and Wilk's Lambda is an appropriate test to use.\par The following is the MANOVA using the Wilk's Lambda test.\par Using an alpha level of .00, we see that this test is significant, Wilk's = .014. This significant F indicates that there are significant differences among the age gender, income, groups on a linear combination of the investor psychology and regret aversion. We see that there are three functions age, gender, income; are significant in examining group differences. With our univariate F-tests, we identify the insignificant variables. When it comes to finding out differences among various sub categories of age, income and gender, we see the differences are insignificant. \section[{XII. Interpreting the Post hoc Test for Age}]{XII. Interpreting the Post hoc Test for Age}\par The MULTIPLE COMPARISONS table is showing the results for the Tukey HSD and the LSD follow-up tests. Since the assumption of homogeneity of variance was met in our example -we only need to review the Tukey HSD information. The information for the LSD can be ignored at this time.\par The Tukey HSD tests the null hypothesis that the two means are equal.\par At first glance, this table is rather intimidatinghowever, there is only certain pieces of data that we need to make our conclusion. We can see that the mean of age category (I) {\ref 25 -35} The MULTIPLE COMPARISONS table (in our example) is showing the results for the Tukey HSD and the LSD follow-up tests. Since the assumption of homogeneity of variance was met in our example -we only need to review the Tukey HSD information. The information for the LSD can be ignored at this time.\par We can see that this test indicates the differences in mean income levels amongst the groups.\par The first row indicates the difference in income level between those in group 1 (up to 2 lakh) versus those who are in group 2 (2-5 lakh) and group 3 (5-10 lakh) and group 4(55 lakh above). We can determine that the mean difference by examining the second column of the As we can see, there is not much difference between the two Mean Squares for investor psychology {\ref (25.207, 22}.766 and regret aversion 16.245, 14.864), resulting in a no significant difference (F = 1.107 investor psychology and 1.093 regret aversion; Sig. = 0.294 investor psychology 0.297 regret aversion). This means that H0 must not be rejected. Thus: the average age of people who find regret aversion, investor psychology, or Exciting are all equal. \section[{XV. Conclusion}]{XV. Conclusion}\par The casual study was based on a survey of 200 males and females investors belonging in different location of the Gwalior region. The variables of the study were the Investor Psychology, Regret Aversion. The objectives of the study were to identify the Factors affecting Investor Psychology and Regret Aversion \& further to find relationship between Investor Psychology and Regret Aversion. The study resulted in four factors for Investor Pshycology viz Curezious and fearless, Distressed, Balance Decision making and Heuristic. Three factors were found for Regret aversion: Risk Averse, Risk Neutral and Risk Taking.\par The result reveals that there is significant difference between investor psychology for age group category (I) 25 -35 and (IV) 55 -65 years. We can see here that there is a gradual change in the value system of people in India and people are now more concerned with quality life rather than economic achievement.\par Previous research has shown differences in financial satisfaction by gender, though there were differences depending on what aspects of personal finance were measured {\ref (Hira \& Mugenda, 2000)}. As quoted by Woodyard and Robb (2012), Previous research {\ref (Hilgert et al., 2003} {\ref : Lusardi \& Mitchell, 2006}\hyperref[b27]{, 2007)} has shown that objective knowledge influences financial behavior, and the general assumption has been that there is a subsequent impact on financial satisfaction as well. Financial decisions are taken in situations of high complexity and uncertainty which compels the decision maker to rely on institution.\par Several factors influence decision making. The conclusion drawn from this research lead to recommendations for a series of action which if adopted would help to establish the investor psychology which 1982; {\ref Zeelenberg, 1999a)} "The Influence of Investor Psychology on Regret Aversion" decision making. Therefore, investor must recognize this fact and try to practice some mechanisms to control his (her) irrational behavior Based on the prospect theory of \hyperref[b10]{Kahneman and Tversky (1979)}, \hyperref[b28]{Shefrin and Statman (1985)}. The psychology effect implies that investors, in trying to avoid regret, will have a greater tendency to sell winners than losers. Investors will tend to hold losers too long and sell winners too soon. Therefore, investor must try to practice some mechanisms to control his (her) irrational behavior.\begin{figure}[htbp] \noindent\textbf{2002}\includegraphics[]{image-2.png} \caption{\label{fig_0}Montier ( 2002 )}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{P{0.85\textwidth}} ,\\ de Vries (1996), negotiation behavior. Larrick \& Boles,\\ (1995), health-related decisions Connolly \& Reb, (2003),\\ lottery ticket purchases Zeelenberg \& Pieters, (2004),\\ and monetary gambles in the laboratory Zeelenberg,\\ Beattie, van der Pligt, \& de Vries, (1996), among others.\end{longtable} \par \caption{\label{tab_0}confirmed that regret is a common, if not universal, experience. Regret the persistence of the possible. Evidence for regret aversion has been documented in areas Richard, van der Pligt}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{P{0.1466604823747681\textwidth}P{0.449443413729128\textwidth}P{0.2538961038961039\textwidth}} \tabcellsep \multicolumn{2}{l}{"The Influence of Investor Psychology on Regret Aversion"}\\ 2015\tabcellsep \tabcellsep \\ Year\tabcellsep \tabcellsep \\ 58\tabcellsep \tabcellsep \\ Volume XV Issue II Version I\tabcellsep \tabcellsep \\ ( ) C\tabcellsep \tabcellsep Reliability Statistics of Investor Psychology\\ Global Journal of Management and Business Research\tabcellsep frame was used. Individual Respondent was the sampling element. 200 individuals including 100 male and 100 female investors were the respondents and Non probability judgmental sampling was used.\tabcellsep Reliability Statistics Cronbach's Alpha N of Items .728 12 Cronbach's Alpha N of Items .723 8 Reliability Statistics\\ \tabcellsep © 2015 Global Journals Inc. (US) 1\tabcellsep \end{longtable} \par \caption{\label{tab_1}}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{P{0.021742605915267783\textwidth}P{0.729283240074607\textwidth}P{0.06250999200639488\textwidth}P{0.004756195043964828\textwidth}P{0.009965361044497734\textwidth}P{0.021742605915267783\textwidth}} \tabcellsep \multicolumn{4}{l}{"The Influence of Investor Psychology on Regret Aversion" "The Influence of Investor Psychology on Regret Aversion"}\\ \tabcellsep 3. Balance Decision making: -This factor has included\tabcellsep \multicolumn{3}{l}{f) KMO test table for Regret Aversion}\\ \tabcellsep the most important determinant of research total\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep variance 13.881. Major elements of this factor include\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep "R-5. I would rather achieve balance than success in\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep my life. (0.537)" "R-6 I like to make decisions quickly\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep and instinctively (0.370)".\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep 4. Heuristic: -This factor has included the most\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep \multicolumn{2}{l}{KMO and Bartlett's Test important determinant of research total variance}\tabcellsep \tabcellsep \\ \tabcellsep 12.355. Major elements of this factor include. "R-2\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep \multicolumn{2}{l}{Kaiser-Meyer-Olkin Measure of Sampling When things go wrong at work it takes me a while to get over it. (0.145)". "R-3 High risk activities excite}\tabcellsep .718\tabcellsep \\ \tabcellsep Adequacy. me. (0.299)". "R-8 Before buying a quiet expensive\tabcellsep \tabcellsep \tabcellsep \\ 60 Year 2015\tabcellsep \multicolumn{2}{l}{Bartlett's Test of Bartlett's Test of Sphericity Df Sig. KMO and Bartlett's Test Approx. Chi-Square Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Sphericity Approx. Chi-Square item I do exhaustive research. (0.376)"}\tabcellsep 190 .000 1242.851\tabcellsep 283.761 .737\tabcellsep 59 Year 2015\\ C ( ) Volume XV Issue II Version I\tabcellsep \multicolumn{4}{l}{Factor analysis of Investor Psychology Factor name Total eigen values \% of variance 1.Curious and fearless 2.050 17.081 Factor name Total eigen values \% of variance Principle component factor analysis with Items converged R-1. My style is more spontaneous action then Cool deliberation. R-9. I like to gather data a lot on any new Opportunities that arise. R-10. I love taking chances. R-11. Success is all about that matters to me. Items converged Df 28 Sig. .000 Varimax rotation and Kaiser Normalization was applied. d) The factor analysis resulted in 3 factors for Investor Psychology. The details about factors, the factor name, Factors loads .268 .408 .491 Factors loads .383 Eigen value, Variables converged; Loadings, Variance\% and cumulative\% are shown follows Factor analysis of Regret Aversion g)}\tabcellsep ( ) C Volume XV Issue II Version I\\ Global Journal of Management and Business Research\tabcellsep \multicolumn{4}{l}{2. Distressed 3. Balance Decision making 4. Heuristic Description of Investor Psychology factors 1.929 16.076 1.666 13.881 1.483 12.355 1. Curezious and fearless: -This factor has included the R-4. I am someone who prefers routine to Uncertainty. R-7. I never upset people. R-12. Occasionally people make me angry. R-5. I would rather achieve balance than Success In my life. R-6. I like to make decisions quickly and Instinctively. R-2. When things go wrong at work it takes me A while to get over it. R-3. High risk activities excite me. R-8. Before buying a quiet expensive item I do Exhaustive research. e) 2. Distressed: -This factor has included the most .369 .464 .288 .537 .370 .145 .299 .376 1.Risk Averse 2.231 27.839 R-13. Whenever I make a choice, I'm curious about what would have happened if I had chosen Differently. .421 R-16. When I think about how I'm doing in life, I Often assess opportunities I have passed up. .470 R-19. I find that to adopt a careful, analytical Approach to making decision takes too long. .522}\tabcellsep Global Journal of Management and Business Research\\ \tabcellsep most important determinant of research total\tabcellsep \multicolumn{3}{l}{important determinant of research total variance}\\ \tabcellsep variance 17.081. Major elements of this factor include\tabcellsep \multicolumn{3}{l}{16.076. Major elements of this factor include "R-4. I}\\ \tabcellsep "R-1. My style is more spontaneous action then cool\tabcellsep \multicolumn{3}{l}{am someone who prefers routine to uncertainty}\\ \tabcellsep deliberation."(0.268). "R-9 I like to gather data a lot\tabcellsep \multicolumn{3}{l}{(0.369)." "R-7 I never upset people (0.464)." R-12}\\ \tabcellsep on any new opportunities that arise.''(0.408). "R-10 I\tabcellsep \multicolumn{3}{l}{Occasionally people make me angry (0.288)."}\\ \tabcellsep love taking chances. (0.383)" "R-11 Success is all\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep about that matters to me."(0.491).\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep © 2015 Global Journals Inc. (US) 1\tabcellsep \tabcellsep \tabcellsep © 2015 Global Journals Inc. (US)\end{longtable} \par \caption{\label{tab_2}}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{P{0.23862014274385407\textwidth}P{0.2456978588421887\textwidth}P{0.020896114195083266\textwidth}P{0.002022204599524187\textwidth}P{0.08257335448057097\textwidth}P{0.22817208564631244\textwidth}P{0.032018239492466294\textwidth}} \tabcellsep \tabcellsep \multicolumn{3}{l}{"The Influence of Investor Psychology on Regret Aversion"}\\ h)\tabcellsep \multicolumn{3}{l}{Description of Regret Aversion Factor}\tabcellsep home in situations where I am under in pressure to\\ \multicolumn{5}{l}{1. Risk Averse: -This factor has included the most}\tabcellsep make quick decision (0.277)"\\ \tabcellsep \multicolumn{4}{l}{important determinant of research total variance}\tabcellsep 3. Risk Taking: -This factor has included the most\\ \tabcellsep \multicolumn{4}{l}{27.889. . Major elements of this factor include. "R-13}\tabcellsep important determinant of research total variance\\ \tabcellsep \multicolumn{4}{l}{whenever I make a choice, I'm curious about what}\tabcellsep 16.560. Major elements of this factor include. "R-14\\ \tabcellsep \multicolumn{4}{l}{would have happened if I had chosen differently}\tabcellsep Whenever I make a choice, I try to get in-formation\\ \tabcellsep \multicolumn{4}{l}{(0.421)." "R-16 When I think about how I'm doing in}\tabcellsep how the other alternatives turned out. (0.217)" "R-17\\ \tabcellsep \multicolumn{4}{l}{life, I often assess opportunities I have passed up.}\tabcellsep Once I make a decision, I don't look back (0.224).\\ \tabcellsep \multicolumn{4}{l}{(0.470)" "R-19 I find that to adopt a careful, analytical}\tabcellsep Further to find out Relationship between\\ \tabcellsep \multicolumn{4}{l}{approach to making decision takes too long (0.522)"}\tabcellsep Investor Psychology and Regret aversion and different\\ \tabcellsep \multicolumn{4}{l}{"R-20 I am always prepared to take a gamble.}\tabcellsep demographic variables, generalized linear model were\\ \tabcellsep (0.352)."\tabcellsep \tabcellsep \tabcellsep applied to the data.\\ \multicolumn{5}{l}{2. Risk Neutral: -This factor has included the most}\tabcellsep i. Manova\tabcellsep 2015\\ \tabcellsep \multicolumn{4}{l}{important determinant of research total variance 17.390. Major elements of this factor include. "R-15 If I make a choice and it turns out well, I still feel like}\tabcellsep a. Descriptive statics Ideally, we would like to see a significant relationship between the investor psychology and the\tabcellsep Year\\ \tabcellsep \multicolumn{4}{l}{something of a failure if I find out that another choice}\tabcellsep regret aversion. Both these variables are dependent\tabcellsep 61\\ \multicolumn{5}{l}{2. Risk Neutral would have turned out better. (0.422)" "R-18 I feel at 1.391 17.390 R-15. If I make a choice and it turns out well, I still Feel like something of a failure if I find out that another choice would have turned out Better. R-18. I feel at home in situations where I am under In pressure to make quick decision. here. Box's Test of Equality of Covariance Matrices a Box's M F df1 df2 Sig. 84.794 1.298 54 2593.666 .072 a. Design: Intercept + gender + age + income + gender * age + gender * income + age * income + gender * age * income The Box's Test of Equality of Covariance Matrices checks}\tabcellsep 352 .422 .277\tabcellsep Volume XV Issue II Version I C ( ) Global Journal of Management and Business Research\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep R-14. Whenever I make a choice, I try to get in-\tabcellsep .217\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep formation how the other alternatives turned\\ \tabcellsep 3. Risk Taking\tabcellsep 1.325\tabcellsep 16.560\tabcellsep Out.\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep R-17. Once I make a decision, I don't look back.\tabcellsep .224\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep © 2015 Global Journals Inc. (US)\end{longtable} \par \caption{\label{tab_3}}\end{figure} \begin{figure}[htbp] \noindent\textbf{:} \par \begin{longtable}{P{0.040848670756646215\textwidth}P{0.1542689161554192\textwidth}P{0.29376278118609406\textwidth}P{0.036068507157464215\textwidth}P{0.05214723926380368\textwidth}P{0.2729038854805726\textwidth}} \tabcellsep \multicolumn{5}{l}{"The Influence of Investor Psychology on Regret Aversion"}\\ \tabcellsep Gender\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep \tabcellsep Hotelling's Trace\tabcellsep .002\tabcellsep .180 b\tabcellsep 2.000 168.000 .835\\ \tabcellsep \tabcellsep Roy's Largest Root\tabcellsep .002\tabcellsep .180 b\tabcellsep 2.000 168.000 .835\\ \tabcellsep \tabcellsep Pillai's Trace\tabcellsep .038\tabcellsep 1.080\tabcellsep 6.000 338.000 .374\\ \tabcellsep \tabcellsep Wilks' Lambda\tabcellsep .963\tabcellsep 1.077 b\tabcellsep 6.000 336.000 .376\\ \tabcellsep Age\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep \tabcellsep Hotelling's Trace\tabcellsep .039\tabcellsep 1.074\tabcellsep 6.000 334.000 .377\\ \tabcellsep \tabcellsep Roy's Largest Root\tabcellsep .031\tabcellsep 1.743 c\tabcellsep 3.000 169.000 .160\\ 2015\tabcellsep \tabcellsep Pillai's Trace\tabcellsep .037\tabcellsep 1.049\tabcellsep 6.000 338.000 .393\\ Year\tabcellsep Income\tabcellsep Wilks' Lambda\tabcellsep .964\tabcellsep 1.043 b\tabcellsep 6.000 336.000 .397\\ 62\tabcellsep \tabcellsep Hotelling's Trace\tabcellsep .037\tabcellsep 1.037\tabcellsep 6.000 334.000 .401\\ Volume XV Issue II Version I C ( )\tabcellsep gender * age gender * income\tabcellsep Roy's Largest Root Pillai's Trace Wilks' Lambda Hotelling's Trace Roy's Largest Root Pillai's Trace Wilks' Lambda Hotelling's Trace\tabcellsep .022 .079 .923 .082 .053 .036 .964 .037\tabcellsep 1.240 c 2.309 2.299 b 2.290 2.997 c 1.037 1.036 b 1.035\tabcellsep 3.000 169.000 .297 6.000 338.000 .034 6.000 336.000 .034 6.000 334.000 .035 3.000 169.000 .032 6.000 338.000 .401 6.000 336.000 .402 6.000 334.000 .402\\ Global Journal of Management and Business Research\tabcellsep Effect Intercept age * income gender * age * income\tabcellsep \multicolumn{3}{l}{Multivariate Tests a Value F .986 5827.452 b Wilks' Lambda Pillai's Trace .014 5827.452 b Hotelling's Trace 69.374 5827.452 b Roy's Largest Root .032 1.827 c Pillai's Trace .063 .610 Wilks' Lambda .938 .607 b Hotelling's Trace .065 .605 Roy's Largest Root .045 .838 c Pillai's Trace .061 .753 Wilks' Lambda .940 .750 b Hotelling's Trace .063 .746 Roy's Largest Root .039 .951 c}\tabcellsep Hypothesis df Error df Sig. 2.000 168.000 .000 2.000 168.000 .000 2.000 168.000 .000 3.000 169.000 .144 18.000 338.000 .892 18.000 336.000 .894 18.000 334.000 .895 9.000 169.000 .582 14.000 338.000 .720 14.000 336.000 .723 14.000 334.000 .727 7.000 169.000 .469\\ \tabcellsep \multicolumn{2}{l}{a. Design: Intercept + gender + age + income + gender *}\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep \multicolumn{4}{l}{Roy's Largest Root 69.374 5827.452 b age + gender * income + age * income + gender * age *}\tabcellsep 2.000 168.000 .000\\ \tabcellsep income b. Exact statistic\tabcellsep Pillai's Trace\tabcellsep .002\tabcellsep .180 b\tabcellsep 2.000 168.000 .835\\ \tabcellsep \tabcellsep Wilks' Lambda\tabcellsep .998\tabcellsep .180 b\tabcellsep 2.000 168.000 .835\\ \tabcellsep © 2015 Global Journals Inc. (US) 1\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par {\small\itshape [Note: c. The statistic is an upper bound on F that yields a lower bound on the significance level.]} \caption{\label{tab_4}Table :}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{P{0.03671361502347418\textwidth}P{0.1001643192488263\textwidth}P{0.0027934272300469483\textwidth}P{0.07342723004694836\textwidth}P{0.085\textwidth}P{0.12251173708920186\textwidth}P{0.17119718309859155\textwidth}P{0.16401408450704225\textwidth}P{0.057464788732394356\textwidth}P{0.03671361502347418\textwidth}} \tabcellsep \tabcellsep \tabcellsep \multicolumn{5}{l}{"The Influence of Investor Psychology on Regret Aversion" "The Influence of Investor Psychology on Regret Aversion"}\tabcellsep \tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep 3.00\tabcellsep 2.00\tabcellsep -.52\tabcellsep .916 .571\tabcellsep -2.33\tabcellsep 1.29\tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep 4.00\tabcellsep 2.24 *\tabcellsep .916 .016\tabcellsep .43\tabcellsep 4.05\tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1.00\tabcellsep -1.76\tabcellsep .921 .058\tabcellsep -3.57\tabcellsep .06\tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep 4.00\tabcellsep 2.00\tabcellsep -2.76 *\tabcellsep .916 .003\tabcellsep -4.57\tabcellsep -.95\tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep 3.00\tabcellsep -2.24 *\tabcellsep .916 .016\tabcellsep \multicolumn{2}{l}{differs significantly in income -4.05 -.43}\tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep 2.00\tabcellsep \multicolumn{4}{l}{from (IV) 55 -65 years of age category for Investor Psychology. .27 .761 .984 -1.70 2.25}\tabcellsep \\ 2015 Year\tabcellsep \multicolumn{6}{l}{1.00 Dependent Variable (I) age (J) age Mean Difference (I-J) Std. Error Sig. 3.00 .45 .761 .934 Multiple Comparisons 4.00 1.05 .761 .512 1.00 -.27 .761 .984}\tabcellsep \multicolumn{2}{l}{-1.52 95\% Confidence Interval 2.43 -.92 3.03 -2.25 1.70}\tabcellsep 2015 Year\\ Volume XV Issue II Version I\tabcellsep Tukey HSD\tabcellsep \tabcellsep 1.00 2.00 2.00 3.00\tabcellsep 2.00 3.00 4.00 1.00 3.00 3.00 4.00 1.00 2.00 4.00 1.00\tabcellsep -1.00 -.48 1.76 1.00 .52 .18 .78 -.45 -.18 .60 -1.05\tabcellsep .921 .696 .921 .953 .921 .229 .921 .696 .916 .942 .757 .995 .757 .732 .761 .934 .757 .995 .757 .858 .761 .512\tabcellsep \multicolumn{2}{l}{Lower Bound Upper Bound -3.39 1.39 -2.87 1.91 -.63 4.15 -1.39 3.39 -1.86 2.90 -1.78 2.14 -1.18 2.74 -2.43 1.52 -2.14 1.78 -1.36 2.56 -3.03 .92}\tabcellsep Volume XV Issue II Version I\\ ( ) C\tabcellsep Tukey HSD\tabcellsep \tabcellsep 4.00\tabcellsep 4.00 2.00\tabcellsep 2.76 * -.78\tabcellsep .916 .016 .757 .732\tabcellsep .38 -2.74\tabcellsep 5.14 1.18\tabcellsep ( ) C\\ Global Journal of Management and Business Research\tabcellsep Invphy\tabcellsep LSD LSD\tabcellsep 3.00 4.00 1.00 2.00 1.00 2.00 3.00\tabcellsep 1.00 2.00 4.00 1.00 2.00 3.00 2.00 3.00 4.00 1.00 3.00 3.00 2.00 3.00 4.00 1.00 3.00 4.00 1.00 2.00 4.00 1.00\tabcellsep .48 -.52 2.24 -1.76 -2.76 * -2.24 -1.00 -.48 1.76 1.00 .52 -.60 .27 .45 1.05 -.27 .18 .78 -.45 -.18 .60 -1.05\tabcellsep .921 .953 .916 .942 .916 .073 .921 .229 .916 .016 .916 .073 .921 .277 .921 .600 .921 .058 .921 .277 .916 .571 .757 .858 .761 .721 .761 .553 .761 .169 .761 .721 .757 .812 .757 .304 .761 .553 .757 .812 .757 .429 .761 .169\tabcellsep -1.91 -2.90 -.14 -4.15 -5.14 -4.62 -2.82 -2.30 -.06 -.81 -1.29 -2.56 -1.23 -1.05 -.45 -1.77 -1.31 -.71 -1.95 -1.67 -.89 -2.55\tabcellsep 2.87 1.86 4.62 .63 -.38 .14 .81 1.33 3.57 2.82 1.36 1.77 1.95 2.55 1.23 1.67 2.27 1.05 1.31 2.09 2.33 .45\tabcellsep Global Journal of Management and Business Research\\ \tabcellsep \tabcellsep \tabcellsep 4.00\tabcellsep 4.00 2.00\tabcellsep 2.76 * -.78\tabcellsep .916 .003 .757 .304\tabcellsep .95 -2.27\tabcellsep 4.57 .71\tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1.00\tabcellsep .48\tabcellsep .921 .600\tabcellsep -1.33\tabcellsep 2.30\tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep 3.00\tabcellsep -.60\tabcellsep .757 .429\tabcellsep -2.09\tabcellsep .89\tabcellsep \\ \tabcellsep \multicolumn{3}{l}{Based on observed means.}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep \multicolumn{4}{l}{The error term is Mean Square(Error) = 14.330.}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_5}}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{P{0.21081419624217118\textwidth}P{0.038329853862212944\textwidth}P{0.12066805845511482\textwidth}P{0.09050104384133612\textwidth}P{0.03407098121085595\textwidth}P{0.008162839248434237\textwidth}P{0.007807933194154488\textwidth}P{0.1959081419624217\textwidth}P{0.008162839248434237\textwidth}P{0.023068893528183716\textwidth}P{0.05430062630480167\textwidth}P{0.037265135699373696\textwidth}P{0.02093945720250522\textwidth}} \tabcellsep \multicolumn{7}{l}{"The Influence of Investor Psychology on Regret Aversion"}\tabcellsep \\ \multicolumn{10}{l}{1.00 XIV. Oneway Interpretation: for Gender as Categorical Variable 1.30 1.323 .327 -1.31}\tabcellsep 3.91\\ \tabcellsep 4.00\tabcellsep 2.00\tabcellsep \multicolumn{2}{l}{Descriptives}\tabcellsep -.26\tabcellsep \tabcellsep 1.178 .825\tabcellsep \tabcellsep -2.59\tabcellsep 2.06\\ \tabcellsep N Mean\tabcellsep 3.00 Std.\tabcellsep Std.\tabcellsep \multicolumn{4}{l}{.13 95\% Confidence Interval for 1.136 .909}\tabcellsep \tabcellsep -2.11 Minimum Maximum 2.37\\ \tabcellsep \tabcellsep 2.00 Deviation\tabcellsep Error\tabcellsep \tabcellsep -.58\tabcellsep \multicolumn{2}{l}{.842 .902 Mean}\tabcellsep \tabcellsep -2.76\tabcellsep 1.61\\ \tabcellsep 1.00\tabcellsep 3.00\tabcellsep \tabcellsep \multicolumn{3}{l}{-.20 Lower Bound}\tabcellsep \multicolumn{2}{l}{.801 .995 Upper Bound}\tabcellsep -2.28\tabcellsep 1.88\\ \tabcellsep \tabcellsep 4.00\tabcellsep \tabcellsep \tabcellsep 1.67\tabcellsep \tabcellsep 1.093 .425\tabcellsep \tabcellsep -1.17\tabcellsep 4.50\\ \multicolumn{2}{l}{1.00 100 49.3800}\tabcellsep 4.83627\tabcellsep .48363\tabcellsep \tabcellsep \multicolumn{2}{l}{48.4204}\tabcellsep \multicolumn{2}{l}{50.3396}\tabcellsep 32.00\tabcellsep 58.00\\ \multicolumn{2}{l}{Dependent Variable (I) income 2.00 Total 200 49.7350 Invphysco 2.00 100 50.0900}\tabcellsep (J) income 1.00 3.00 4.00 4.77270 4.70567\tabcellsep \multicolumn{7}{l}{Multiple Comparisons Mean Difference (I-J) .58 .38 2.25 .33748 49.0695 Std. Error .842 .902 Sig. 95\% Confidence Interval -1.61 2.76 .629 .930 -1.25 .973 .101 -.28 4.77 50.4005 32.00 58.00 2.01 .47057 49.1563 51.0237 32.00 58.00}\tabcellsep Year 2015\\ Tukey HSD\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Lower}\tabcellsep Upper\\ \multicolumn{2}{l}{Tukey HSD regaversion regaversion 1.00 100 32.9100 1.00 2.00 3.00 4.00 2.00 100 33.4800 Total 200 33.1950}\tabcellsep \multicolumn{5}{l}{2.00 3.00 4.00 1.00 3.00 4.00 1.00 2.00 4.00 1.00 2.00 3.00 3.96728 3.74025 3.85634 Test of Homogeneity of Variances -1.56 -1.17 -1.30 1.56 .39 .26 .20 -.38 1.86 -1.67 -2.25 -1.86 .39673 32.1228 .37403 32.7379 .27268 32.6573 Levene Statistic}\tabcellsep \multicolumn{3}{l}{Bound -4.21 -3.69 -4.73 -1.08 -1.58 -2.80 -1.88 -2.01 -.57 -4.50 -4.77 -4.30 33.6972 1.019 .421 .970 .624 1.323 .759 1.019 .421 .762 .956 1.178 .996 .801 .995 .629 .930 .939 .197 1.093 .425 .973 .101 .939 .197 23.00 34.2221 23.00 33.7327 23.00 df1 df2}\tabcellsep Bound 1.08 1.35 2.13 4.21 2.37 3.32 2.28 1.25 4.30 1.17 .28 .57 39.00 40.00 40.00 Sig.\tabcellsep Volume XV Issue II Version I\\ Invphysco\tabcellsep \tabcellsep 1.00\tabcellsep \tabcellsep \tabcellsep 1.17\tabcellsep .608\tabcellsep .970 .624 1\tabcellsep \tabcellsep -1.35 198\tabcellsep 3.69 .436\tabcellsep ( ) C\\ \multicolumn{7}{l}{3.00 4.00 1.00 2.00 In the table 'ANOVA 2.00 4.00 1.00 2.00 3.00 2.00 3.00 4.00 1.00 3.00 4.00 Invphy LSD Regaversion Sum of Squares Invphysco Between Groups 25.205 -.39 -.13 1.30 -.26 .13 -1.56 -1.17 -1.30 1.56 .39 .26 1.353 df 1 Within Groups 4507.750 198 Total 4532.955 199}\tabcellsep \multicolumn{3}{l}{.762 .956 1.136 .999 1.323 .759 1.178 .996 1.136 .999 1.019 .127 .970 .229 1.323 .327 1.019 .127 .762 .608 1.178 .825 1 Mean Square 25.205 -2.37 -3.08 -2.13 -3.32 -2.82 -3.57 -3.09 -3.91 -.45 -1.11 -2.06 198 22.766}\tabcellsep F 1.107\tabcellsep 1.58 2.82 4.73 2.80 3.08 .45 .75 1.31 3.57 1.89 2.59 .246 Sig. .294\tabcellsep Global Journal of Management and Business Research\\ \tabcellsep Between Groups\tabcellsep 1.00\tabcellsep \tabcellsep \multicolumn{2}{l}{1.17 16.245}\tabcellsep 1\tabcellsep .970 .229\tabcellsep \multicolumn{2}{l}{16.245}\tabcellsep -.75\tabcellsep 1.093\tabcellsep 3.09 .297\\ regaversion\tabcellsep 3.00 Within Groups\tabcellsep 2.00\tabcellsep \tabcellsep \multicolumn{2}{l}{-.39 2943.150}\tabcellsep 198\tabcellsep .762 .608\tabcellsep \multicolumn{2}{l}{-1.89 14.864}\tabcellsep 1.11\\ \tabcellsep Total\tabcellsep 4.00\tabcellsep \tabcellsep \multicolumn{2}{l}{-.13 2959.395}\tabcellsep \tabcellsep 1.136 .909\tabcellsep \tabcellsep -2.37\tabcellsep 2.11\end{longtable} \par \caption{\label{tab_6}}\end{figure} \footnote{© 2015 Global Journals Inc. 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