The paradigm of Efficient Markets was advanced by Eugene Fama in the 1960’s which asserts that it is impossible to beat the markets as all available information is reflecting in the prices of the securities. As harmonizing with this hypothesis, it is stated that all the securities are right there with fair prices, eliminating the concept of underpriced and overpriced security, thus there is no chance for earning the abnormal returns (investopedia.com).

In 1970’s Eugene Fama published a review for the hypothesis. This includes three forms of the market-Weak, Semi-Strong and Strong. Weak Form asserts that past information about stocks reflects in present stock prices. Semi-Strong Form asserts that prices reflect past information very quickly and thus not generate any abnormal return and Strong form asserts that markets are full of information and because of that an investor cannot earn the return excess from market regularly as stock market discounts every bit and bytes of information.

Contrary to this, if securities would have properly priced then there will not be any chance for earning the returns. But in general, investors are not rational, but quasi-rational or irrational. This notion was expressed by the field of behavioral finance as it comprehends the art of behavioral biases amongst the investors. The field of behavioral finance is debating from long that it is possible to beat the market layered with the fact of active investment strategy. The large body of researchers and academicians from so long is contradicting with the evidences that investors like Warren Buffet have been beating the market. The great volatility in markets substantiates that the securities are not fairly priced and they deviate from their intrinsic value.

Here intervene the cognitive and emotional biases which distort the investment decision making process. Cognitive biases are connecting with faulty reasoning and through education it can be corrected. Emotional biases on the other side of the coin are lacking the criterion of self control or overconfidence and are severe to correct (NAAIM, 2013).

REVIEW OF RELATED LITERATURE:

The roller coaster of cognition and emotions paves the way for active and passive investors and the riding cycle of investment moves accordingly. The dimensions for active and passive investor differ as active investors try to obtain the return from the market. They keep on updating themselves with the recent happenings in the market and they do not hold globally diversified portfolio. As these investors’ wishes to beat the market, they rely to outperform the market in the short term and believe in technical analysis rather than fundamental analysis (Stanley, 2012).

Passive investors work on daily price fluctuations, whereas the passive investors get good returns in a long while with a minimum of involvement by choosing those stocks which are having a decent track record and by diversifying the portfolio, so that risks can be eliminated (Harvey).

Behavioral biases are connected with the type of investor which ultimately distorts the investment decision making process. On the continuum of risk tolerance, the passive investors are near to zero, whereas the active investors are more towards the high risk exposure. The passive investors are more emotional for their hard earned money and keep their choice static for a long period of time for earning the returns, whereas active investors wish to time the market in the short run and want to earn the abnormal return in the near span of time. They endure themselves with the expressions of overconfidence and illusion of control which makes them behave in a faulty manner (Pompian, 2006)

The active and passive investors are distinct from each other and cognitive and emotional biases are defined for both of the types to a great extent in the work of Pompian, 2006. These emotional biases are unstable, which cannot be rectified but the cognitive biases are generally stable and can be eliminated by giving due thoughts to a certain situation.

Baker, 2010, supported that passive investment is consistent with the Efficient Market Hypothesis (EMH) but not in the line with behavioral perspective. (Thaler, 2005), propped up with a thought that, considering the heuristic not any individual can predict the movement of stocks. (Wärneryd, 2001), concluded that passive investors are more successful than active sophisticated investment. These investors maintain their financial security investment for a long while with a shorter margin in the short term time frame. In contrast with active investors, passive investors do not try to beat the market and stays passive with respect to volatility in the markets.

In contradiction with active investment, passive investment exemplified with heuristics and frugal decision making. Although this minimizes the effect of emotional drivers in decision making, but this might result in bubbles and price burst as people stop giving ear to the herding which at the point of saturation fractures in a severe way.

RESEARCH METHODOLOGY:

The study from the perspective of descriptive research used the questionnaire instrument for collecting the responses of investors. Statistical population of the study was the active equity investors of stock market of Jaipur city. The questionnaire included the dimensions of demographic factors such as financial literacy and years of experience in the equity investment and behavioral biases such as gambler’s fallacy, disposition effect, cognitive dissonance, herd behavior and hindsight bias. The questionnaire was self evaluated in which investor was given a certain situation and their responses were scored. For analysis, the administered points of each of the biases were taken. The objective of research is to explore the behavioral biases of active investors in association with two demographic factors.

Since this study applies primary data, the tool was designed and validated. The tool was tested on 20 investors of Jaipur city taken randomly. The reliability analysis was conducted for consistency and Chronbach alpha was found 0.787. After cleaning the data, the analysis was executed on 146 active equity investors of Jaipur City. Research variables were identified and defined and were examined for normality and it was found non-normal. Hence, we used the non-parametric methods for testing the statistical significance. Underneath were the variables in the study

Demographic Factors	Behavioral Biases
Financial Literacy	Herd Behavior
Years of Experience in Market	Hindsight Bias
	Cognitive Dissonance
	Disposition Bias
	Gambler’s Fallacy

Hypotheses of the study

H0₁There is no significant difference between the behavioral biases exhibited by financially-literate and non-literate active investors of Jaipur city

H0₂There is no significant difference between the behavioral biases exhibited by active investors of Jaipur city at different levels of years of experience in stock market.

Analysis and Interpretation

The analysis was conducted through SPSS-PASW-18 trial version. The results are underneath

The Man-Whitney U test was used to compare the behavioral biases of two groups of active investors on the basis of financial literacy.

Table 1: Mann Whitney-U test

Behavioral Biases	Financial Literacy
	Non-Financial-Literate		Financially Literate		P-Value
	Mean	S.D.	Mean	S.D.	P-Value
Herding Bias	5.98	1.833	4.53	1.769	.000
Hindsight Bias	5.53	1.840	5.12	2.628	.993
Cognitive Dissonance Bias	5.40	4.754	5.32	4.221	.302
Disposition Effect	4.63	3.469	5.33	4.269	.333
Gambler’s Fallacy Bias	6.83	2.500	4.87	3.008	.000

It was found that the average herd behavior is significantly different in both the groups (i.e. P Value < 0.05) and it was found more in non-financial literate group. Similarly, the difference was also observed in gambler’s fallacy and the visible impact was seen in non-financial literate group. This implies that herding and gambling tendency exists in non-financially literate group as these investors’ wishes to follow the crowd because of the limitation of their knowhow of stock market and they also involve themselves in gambling without understanding the tandem of movement of the stock market. There was no significant difference observed in the other three biases with the financial literacy. (Refer-Table 1)

On the other keen dimensions of hindsight and cognitive dissonance biases, the investors who are not financially literate were more prone, but it was quite of interest that disposition effect was more observed in financially literate investors. Resistance to panic is the crucial issue for an investor from many decades, so as in this survey, it is explored that investors generally sell the winners and hold the losers. Thus the first null hypothesis was rejected as it was observed that there is a significant difference exhibited by both financially literate and illiterate investors.

The Kruskal-Wallis test was used to test the difference in behavior biases as there were three groups in the years of experience in market and also post-hoc analysis was conducted for the variables which have the p-values of Kruskal-Wallis test significant.

It was found that the herding behavior and the gambler’s fallacy with years of experience in the market is significantly different in all the groups and it was found more in third experienced group and least in the first group. This implies that herding behavior is maximum in the group of >10 years and 3 to 5 years. The initial phase of herding and gambler’s fallacy and having an enough experience in equity markets both are full of herding and gambling tactic. It can be inferred that primary experience in the stock market have an obvious notion of the herd instinct and on the latter on stages when people imbibed themselves with enough experience they are influenced by the disposition effect too i.e. to sell the winners early and retain the losing stocks in the portfolio. This behavior sways that fear and loss aversion attitude of investors let them behave in that direction for following the crowd.

Table 2: Kruskal-Wallis Test

Behavioral Biases	Years of Experience in Stock Market
	3 to 5 Years		5 to 10 Years		> 10 Years		Total		p value
	Mean	S.D.	Mean	S.D.	Mean	S.D.	Mean	S.D.	p value
Herding Bias	5.00	1.864	4.33	1.534	6.22	2.728	4.92	1.894	.023
Hindsight Bias	5.23	2.532	4.82	2.214	6.78	1.481	5.23	2.438	.131
Cognitive Dissonance Bias	5.21	4.285	5.39	4.486	6.67	5.000	5.34	4.357	.186
Disposition Effect	5.58	4.021	4.85	4.048	1.11	2.205	5.14	4.066	.006
Gambler’s Fallacy Bias	5.41	2.945	6.21	3.049	2.33	1.000	5.40	3.000	.002

For gambler’s fallacy, the difference is lesser in the later stages of experience in the market. This entails that as investors’ starts understanding the basics of stock market, the behavior of gambling converts into the notion of cognition. There was no significant difference observed in the other two biases i.e hindsight bias and cognitive dissonance with years of experience in market. (Refer-Table 2). It also resulted in rejecting the second null hypothesis.

CONCLUSION:

It can be concluded that herding and gambling are prominent in the active equity investors of Jaipur city. This is to recommend that investors should understand the rationale of economic decisions and should understand the emotional and the cognitive tilt to better take the meticulous investment decisions.

REFERENCES:

Baker, H. K. (2010). Behavioral finance: investors, corporations, and markets (Vol. 6). John Wiley and Sons.

Harvey, I. (n.d.). Active and Passive Traders. Retrieved from investopedia.com: http://www.investopedia.com/university/introduction-stock-trader-types/active-and-passive-traders.asp

investopedia.com. (n.d.). Efficient Market Hypothesis-EMH. Retrieved from www.iinvestopedia.com: http://www.investopedia.com/ terms/e/efficientmarkethypothesis.asp

NAAIM. (2013). Three Fundamentals Using Active Management, Behavioral Finance and Planning to Reach Client Objectives . Littleton: National Association of Active Investment Managers.

Pompian, M. (2006). Behavioral finance and wealth management. How to Build Optimal Portfolios That Account for Investor Biases. New Jersey: Wiley and Sons Inc.

Pompian, M. M. (2006). Behavioral finance and wealth management. How to Build Optimal Portfolios That Account for Investor Biases. New Jersey: Wiley and Sons. .

Stanley, A. (2012, April 18). Efficient or Inefficient markets, passive or active management? Retrieved from http://stanleyadvisors.com/: http://stanleyadvisors.com/2012/04/18/efficient-or-inefficient-markets-passive-or-active-management/

Thaler, R. H. (2005). Advances in Behavioral Finance (Vol. 2).

Wärneryd, K. E. (2001). Stock-market psychology: How people value and trade stocks. Edward Elgar Publishing.

Received on 01.05.2015 Modified on 18.05.2015

Asian J. Management; 6(3): July-Sept., 2015 page 159-162

DOI: 10.5958/2321-5763.2015.00023.2