PSYCHOLOGICAL TRAITS AND DEMOGRAPHIC FACTORS DO THEY AFFECT INVESTOR S BEHAVIOR?

Transcription

1 46 PSYCHOLOGICAL TRAITS AND DEMOGRAPHIC FACTORS DO THEY AFFECT INVESTOR S BEHAVIOR? Prof. Paramjeet Kaur, Assistant Professor, Symbiosis Centre for Management Studies, Pune, India. Dr. Shreya Virani, Assistant Professor, Symbiosis Centre for Management Studies, Pune, India. Prof. Sabiha Fazalbhoy, Teaching Associate, Symbiosis Centre for Management Studies, Pune, India. ABSTRACT Behavioral finance is a relatively contemporary phenomenon. It is based on the assumption that information structure and the characteristics of market participants systematically influence individuals investment decisions as well as market outcomes. As per the discipline of behavioral finance, the behavior of an investor in the financial market is determined by drives from psychological principles of decision making to explain why people invest in financial market. When it comes to investing in the financial markets an individual is not always as rational as he thinks he is. Emotional and cognitive prejudice such as loss aversion (expecting to get high returns with low risk), herding (imitating others decisions), media response (overreacting to headlines), and timing the market, etc. impact the overall performance of one s investments. Keywords: Behavioral finance, Investment decisions, Financial Market, Financial Instruments.

2 47 Introduction: Behavioral finance is a field of finance which refers to psychology-based theories to explain stock market anomalies. Within behavioral finance, it is assumed that the characteristics of market participants systematically influence individuals' investment decisions. Moreover, Hunton et al. stated that behavioral finance introduces many aspects of human behavior into traditional finance to improve our understanding of analysts and investors. It refers to the study of the markets that draws on psychology, throwing more light on why people buy or sell the stocks and even why they do not buy stocks at all. According to Glaser et al. (2004, p. 527): Behavioral finance as a subdiscipline of behavioral economics is finance incorporating findings from psychology and sociology into its theories. Behavioral finance models are usually developed to explain investor behavior. Some of the worthy reviews on the development of the field of behavioural finance include those by De Bondt et al. (2008), Daniel et al. (2002), Glaser et al. (2004) and Garling et al. (2009). These reviews indicate that much behavioural finance uses the corpus of work that demonstrates biases in human judgment and decision making (Kahneman et al., 1982) to explain investor behaviour and market anomalies. There is, however, increasing recognition that we need to move towards a theoretical framework that accounts not just for the circumstances that produce inefficient information processing but also for those that produce efficient information processing (Shefrin, 2005). General Background of Indian Financial System: The financial system in any country plays a critical role. India has various financial institutions specialized and non-specialized, organized and unorganized financial markets with wide range of financial instruments. The existence of a well-recognized financial system facilitates transfer and apportionment of funds efficiently as well as effectively. The sustainability of the financial system mainly depends upon the accumulating funds and the best distribution of the funds across the various segments. The participants in the stock market play a vital role as they are the fund providers. The active market participants play a vibrant role because they are the major source of funds. Selection and construction of portfolio plays a crucial role when an investor decides to invest. By constructing an investment portfolio with a combination of investment avenues, will entitle the investor to diversify his risk and to optimize the returns. There are three kinds of investors: an investor who wishes to have more return and least risk, more return with comparatively higher risk and high return with a high risk. Behavioral finance is a relatively new field that seeks to combine behavioral and cognitive psychological theory with conventional economics and finance to provide explanations for why people make irrational financial decisions. This paper surveys research in demographic factors and psychological traits of the investors and also attempts to find out the how do they affect investor s behaviour. The purpose of this article is to offer a brief survey of prior research and look at the behavior of the investors and their psychological traits which will in turn attempts to find out whether investors are rational in their decision making or their decisions are based on their sentiments or psychological factors. Objectives: 1. To find out relationship between demographic factors such as age, gender and income of the respondents and their risk taking abilities. 2. To study relationship between psychological traits and investment behavior of an investor. Hypotheses of the Study: H0: Demographic factors have an impact on investors investment decisions. H1: Demographic factors do not have any impact on investors investment decisions. H0: psychological factors do not have a significant influence on the investor s decision making: H2: psychological factors do have a significant influence on the investor s decision making

3 48 Review of Literature: Manish Mittal, (2008), classified the Indian investors into different personality types and explored the relationship between various demographic factors and the investment personality exhibited by the investors. The results of this study supported the argument that there are behavioral linkages to the choice of investments. The findings found to be in consistent with the notion that individuals tend to act normal rather than rational when making investment decisions. The results of this study revealed that the Indian investors can be classified into four dominant investment personalities casual, technical, informed and cautious. Meenu Verma, (2008), aimed to investigate the effect of demographics and personality type on investment choice. The study is based on the primary data collection from 40 respondents through structured questionnaire. According to this study the investment preferences seem to be dynamic due to the changes in social, economic and political atmosphere, as well as introduction of new investment avenues. Bruno Biais et al, (2004), measured the degree of overconfidence in judgment in the form of miscalibration and self- monitoring of 245 participants and also observed their behaviour in an experimental financial market under asymmetric information. The miscalibrated traders are expected to be especially vulnerable to losses by underestimating the conditional uncertainty about the asset value and the high self-monitors are expected to behave strategically and achieve superior results. Their empirical results showed that miscalibration would reduce and selfmonitoring would enhance the trading performance. The effect of the psychological variables is strong for men but it non-existent for women. Ramesh Krishnan and Fatima Beena, (2009) aimed to examine whether cognitive biases heuristics and frame dependency would coalesce to form two major factors. The scale was linked to personality dimension. By using the behavioural finance concepts, the research validated that personality factors do affect individual investors decisions and that the individual investors acts normal and usual and not always objective and rational. The cognitive biases the heuristics and frame dependency are not independent according to the research work. According to the research, the extraversion scores have a positive relationship, and openness scores have negative relationship with tendency to comply with behavioural finance concepts. Malena Johnsson, Henrik Lindblom and Peter Platan, (2002), focus on how private and the institutional investors have changed their investment behaviour with the consequence of the speculative bubble during the period from fall 1998 to March The various factors for the speculative bubble were also investigated. The research found that the majority of the investors, in spite of the speculative bubble, continued with their investment activities. They were confident that the collapse will be corrected soon and their investments would not be in a risky situation. The Behavior of Investors: According to Kent, et al. (2001), the most common behavior observed among the most investors when making investment decision are (1) Investors often do not participate in all asset and security categories, (2) Individual investors demonstrate loss-averse behavior, (3) Investors use past performance as an indicator of future performance while making investment decisions pertaining to stock purchases. (4) Investors trade too aggressively, (5) Investors behave on status quo, (6) Investors do not always form efficient portfolios, (7) Investors behave parallel to each other, and (8) Investors are influenced by historical high or low trading stocks. Investors use their past performance of the stocks as an indicator to take their future stock purchase decisions. Investors frequently based their decisions on historical performance of stock prices using so call technical analysis. This relates to a tendency to judge likelihood based upon naive comparison of characteristics of the event being predicted with characteristics of the observed sample (Representativeness). This suggests that investors will sometimes extrapolate past price trends naively. In a 1995 paper on Aspects of Investor Psychology, Kahneman and Mark W Riepe bring forth the beliefs, preferences and biases that humans have which influence their investment decision making. In a paper on Aspects of Investor Psychology, Kahneman and Mark W Riepe bring forth the beliefs, preferences and biases that humans have which influence their investment decision making. On the basis of a questionnaire based study of 140 small investors and 175 professional investors/traders, Ira Epstein, a stockbroker and David Garfield, a psychologist, published a book in 1992, entitled The Psychology of Smart Investing. In this book they presented the analysis of their survey, in which they identified six clusters or types of investors which they named as overly cautious/paranoid investors, conflicted investors, masked investors, revenging/consumed investors, fussy investors and depressed investors. Interestingly, these investor types closely resemble the mental disorder categories described by American Psychiatric Association. (Bernstein, 1996) In a

4 research paper, published in The Journal of Behavioural Finance, entitled Aversion and Personality Types Behavioral finance argues that some financial phenomena can plausibly be understood using models in which some agents are not fully rational. The field has two building blocks: limits to arbitrage, which argues that it can be difficult for rational traders to undo the dislocations caused by less rational traders; and psychology, which catalogues the kinds of deviations from full rationality we might expect to see. (Barberis and Thaler, 2001). The finance field was reluctant to accept the view of psychologists who proposed the behavioral finance model. Indeed, the early proponents of behavioral finance were regarded as heretics. As the evidence of the influence of psychology and emotions on decisions became more convincing, behavioural finance then received greater acceptance. Behavioral Finance and Investment Decisions: Behavioral finance seeks to find how investor s emotions and psychology affect investment decisions. It is the study of how people in general and investors in particular make common errors in their financial decision due to their emotions. It is nothing but the studies of why otherwise rational people take some really thumb investment decisions. Decision making is a process of choosing best alternatives among a number of available alternatives. This decision has to come out after a proper evaluation of all the alternatives. Decision making is the most complex and challenging activity of investors. Every investor differs from the others in all aspects due to various factors like demographic factor, socioeconomic background, educational level, sex, age and race. An optimum investment decision plays an active role and is a significant consideration. Investor is a rational being who will always act to maximize his financial gain. (Amar Kumar 2013). In the light of the above literature it is evident that there is no research work existing pertaining to behavioural finance in Pune region. Hence we researcher felt that behavioural finance can be further taken up to study the investment behaviour / finance behaviour of investors around Pune region. Research Methodology: The present study is an attempt to understand investors financial behavior with respect to their demographic relationships and their psychological traits which influence investment decision making. In order to fulfill the research objectives stated above, the participation of investors across Pune region has been invited. Method of data collection: The research study has employed both secondary and primary data. Primary Data: Primary data has been collected from 200 salaried investors (the respondents) with the help of a well-structured questionnaire. Sampling Method: The study employed convenient sampling method in order to obtain first-hand information from the respondents. The sample was collected during September- October 2015, from the various parts of Pune region. Chi - Square Test: It is a statistical test which is commonly used to compare observed data with data we would expect to obtain according to a specific hypothesis framed earlier. The impact of various demographic factors on an investors risk taking ability has been studied and analyzed separately, the results of which are as under Chi-Square and Correlation analysis were used to test whether there was a significant relationship between the demographic factors and the level of risk taking ability of the investors. as a dependent variable was considered while making investment in the financial markets, on the basis of which sub hypotheses were developed and cross analysis was carried out. Secondary Data: The present study has extracted secondary data from the various sources such as journals, books, internet and certain published sources. H0 - There is no relationship between the investors Level of Income and the Level of Taking Ability. H1 - There is a relationship between the investors Level of Income and the Level of Taking Ability

5 50 Table 1: Degree of relationship between investors level of income with their level of risk taking ability R I S K Less than Rs. 1,00,000 Rs. 1,00,000-2,00,000 Annual Income Rs.2,00,000 3,50,000 Rs.3,50,000- Rs,5,00,000 Above Rs. 5,00,000 Low Count Expected count Moderate Count Expected count High Count Expected count Very high Count Expected count Total Count Expected count Table 2: Chi-square test Value Df Asymp. Sig. (2-sided) Pearson Chi-Square a N of Valid Cases 200 a. 12 cells (60.0%) have expected count less than 5. The minimum expected count is.50. Calculated value of Chi-square is Chi-square value at 5% Significance Level and 12 Degree of Freedom is As the calculated value of Chi-square is more than the critical value, Null hypothesis is rejected and alternative hypothesis is accepted, revealing that there is a relation between the investors income and the level of risk taken by him/her. Table 3: Correlation analysis between level of income and the level of risk taking ability Income Income Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) The above Correlation analysis between Income and the level of risk taken by investors shows that there is a positive correlation between these two variables. An increase in Income by one point leads to positive change of points in the level of risk taken by the investors. R I S K Table 4: Degree of relationship between investors age with their level of risk taking ability Low Moderate High Very high Age (in years) Less than Above 55 Count Expected count Count Expected count Count Expected count Count Expected count

6 51 Table 5: Chi-square test Value Df Asymp. Sig. (2-sided) Pearson Chi-Square a N of Valid Cases 200 a. 12 cells (60.0%) have expected count less than 5. The minimum expected count is.33 Calculated value of Chi-square is Chi-square value at 5% Significance Level and 12 Degree of Freedom is As the calculated value of Chi-square is more than the critical value, Null hypothesis is rejected and alternative hypothesis is accepted, revealing that there is a relation between the investors age and the level of risk taken by him/her. Table 6: Correlation analysis between age and the level of risk taking ability Age Age Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) The above Correlation analysis between age and the level of risk taken by investors shows that there is a negative correlation between these two variables. An increase in age by one point leads to negative change of points in the level of risk taken by the investors. H0 - There is no relationship between the investors Gender and the Level of Taking Ability. H1 - There is a relationship between the investors Gender and the Level of Taking Ability. Table 7: Extent of Relationship between Investors Gender and Level of Taking Ability R I S K Low Moderate High Very high Gender Male Female Count Expected count Count Expected count Count 32 5 Expected count Count 11 0 Expected count Table 8: Chi-square test Value Df Asymp. Sig. (2-sided) Pearson Chi-Square N of Valid Cases 200 a 1 cells (12.5%) have expected count less than 5. The minimum expected count is Calculated value of Chi-square is Chi-square value at 5% Significance Level and 3 Degree of Freedom is As the calculated value of Chi-square is less than the critical value, Null hypothesis is accepted and alternative hypothesis is rejected, revealing that there is no relation between the investors gender and the level of risk taken by him/her.

7 52 Table 9: Correlation analysis between gender Age Pearson Correlation * Sig. (2-tailed) Pearson Correlation -.147* Gender Sig. (2-tailed) *. Correlation is significant at the 0.05 level (2-tailed) The above Correlation analysis between gender and the level of risk taken by investors shows that there is a negative correlation between these two variables. An increase in gender by one point leads to negative change of points in the level of risk taken by the investors. H0: psychological factors do not have a significant influence on the investor s decision making: H2: psychological factors do have a significant influence on the investor s decision making Table 10: Regression model identifying the investor behavior with respect to psychological traits Model Unstandardized Coefficients Standardized Coefficients T Sig. B Std. Error Beta (Constant) Constructive Self -reliance Allusion Aversion Regretful Reluctant Belief Rational Choice The above table no. 10 depicts the Regression model that identifies eight broad dimensions of investor behavior with respect to psychological traits, which is most closely related to and has impact on the investment decisions of the investors. The model revealed that the psychological factors such as Allusion, Self Reliance and Aversion are significantly associated with the investment decision making process as the p values are 0.043, and are less than the alpha value(0.05). Hence, here the null hypothesis is rejected. Behavioural factors such as Regretful (0.245), Reluctant (0.354), Belief (0,891), Rational choice (0.837) and Constructive (0.211) are not statistically significant. The values of R square and adjusted R square states that investor behaviour cast an impact of 68 to 73 percent on the investment decision making. Major Findings & Suggestions: Based upon the primary data analyzed and interpreted the major findings of the study are enumerated as below: - It is being found that the financial behavior of the respondents is influenced by their psychological traits namely risk aversion, self-reliance and belief etc. - taking ability of an investor is predominantly dependent on the demographic factors i.e. Income. There exists a positive correlation between these two variables. - There is no relation between the investors gender and the level of risk taken by him/her. Correlation analysis between gender and the level of risk taken by investors shows that there is a negative correlation between these two variables. Conclusion: Investor s behaviour is influenced by many factors during investment decision making. Demographic profile of

8 53 investors is also one of the factors influencing the investor s decision among the others. The above study is based on the data analyzed and interpreted from the investors around Pune region only. This study concludes that the demographic factors like income has significant impact on the investor s behaviour affecting his/her risk taking ability. The other demographic factors such as gender have no impact on investment behaviour of the investors. The psychological factors such as Allusion, Self-Reliance and Aversion are significantly associated with the investment decision making process References: [1] Amar Kumar Choudhury (2013). Impact of behavioral finance in investment decisions and strategies a fresh approach, International Journal of Management Research and Business Strategy, Vol.2, No.2, pp [2] Barberis, N., Shleifer, A., and Vishny R. (1996). A Model of Investor Sentiment Mc Graw Hill. [3] Bennet E, Selvam M (2011). Factors Influencing Retail Investors Attitude towards Investing In Equity Stocks: A Study in Tamil Nadu, J. Modern Account. Auditing, 7(3): [4] Bernstein Peter L., Against the Gods The Remarkable Story of, John Wiley & Sons [5] Daniel, K., Hirshleifer, D., & Teoh, S. (2002). Investor psychology in capital markets: Evidence and Policy Implications. Journal of Monetary Economics, 49, [6] De Bondt, W., H. Shefrin, G. Muradoglu, and S. Staikouras (2008), Behavioral finance: Quo vadis? Journal of Applied Finance 18(2), 7 21 [7] Epstein Ira and Garfield David., The Psychology of Smart Investing, [8] Gärling, T., Kirchler, E., Lewis, A., & van Raaij, F. (2009). Psychology, financial decision making, and financial crises. Psychological Science in the Public Interest, 10(1), [9] Glaser, M., Nöth, M., and Weber, M. (2004). Behavioral Finance, in Koehler, D. J. and Harvey N. (Eds.), Blackwell Handbook of Judgment and Decision Making, Wiley-Blackwell, Oxford, Malden, pp [10] Hunton, J., McEwen, R., Bhattacharjee, S. (2001). Toward an Understanding of the y Choice Behavior of Professional Financial Analysts. The Journal of Psychology and Financial Markets. Vol. 2, No. 4, [11] Kahneman, Daniel, and Mark W. Riepe. Aspects of Investor Psychology (1998). Journal of Portfolio Management 24, no. 4 [12] Kahneman, Daniel, Paul Slovic, and Amos Tversky, eds., Judgment Under Uncertainty: Heuristics and Biases. Cambridge: Cambridge University Press [13] Kent D. Daniel, David Hirshleifer and Avanidhar Subrahmanyam (2001). The Journal of Finance, Vol. 56, No. 3), pp [14] Malena Johnsson, Malena; Lindblom, Henrik and Platan, Peter (2002). Behavioral Finance - And the Change of Investor Behavior during and After the Speculative Bubble At the End of the 1990s, Master s thesis in finance, School of Economics and Management, Lund University [15] Manish Mittal and R K Vyas. (2007). Demographics and Investment Choice Among Indian Investors. ICFAI Journal of Behavioral Finance, Vol. IV No.4 Pg [16] Martin Hilbert (2012) "Toward a synthesis of cognitive biases: How noisy information processing can bias human Decision-making". Psychological Bulletin, 138(2), [17] Meenu Verma. (2008). Wealth Management and Behavioral Finance: The Effect of Demographics and Personality on Investment Choice Among Indian Investors. ICFAI Journal of Behavioral Finance, Vol. V No.4 Pg [18] Ramesh Krishnan and Fatima Beena (2009). Measurement of Conformity to Behavior Finance Concepts and Association with Individual Personality: The IUP Journal of Behavioral Finance, Vol. VI, Nos. 3 & 4, pp [19] Shefrin, Hersh, A Behavioral Approach to Asset Pricing. Boston: Elsevier Academic Press. ****