Impact Of Competence On Trading In India

This research project analyzes the impact of competence of individual investors on their trading behaviour in the stock market. Individual investors are seen trading too frequently. This impacts their returns from their investments, their belief in the stock markets, and also the functioning of financial markets to some extent. Investors with high level of competence tend to trade more frequently. While some factors affect individual’s perception towards external issues, some affect their belief in themselves, which in turn, influences their confidence and belief in their own judgement and decision making. This holds true in the context of investors in general and individual investors in particular. Individual investors take trading decisions based on their self-perceived competence that is influenced by several factors. The present study identifies the factors that determine individual investor’s competence. The study examines the trading behaviour of individual investors by using a modified questionnaire.

RESEARCH AIM:

The study aims to examine the factors that determine the competence level of individual investors. The study also explores whether the competence level of individual investors affects their trading behaviour.

LITERATURE REVIEW:

A number of psychological biases, that affect investors behaviour and subsequently their decisions, have been dealt with in several previous studies across the world. Such biases include: overconfidence, home bias, sensation seeking attitude, competence effect, herding, anchoring, heuristics, etc. This study attempts to address the issue of competence effect.

Odean (1998) attributes the high volume of trading to investors overconfidence. Overconfidence can be termed as the tendency of investors to perceive themselves as skillful. In the process, they may forget the concept of “a rising tide lifts all the boats? at the time when their investment decisions prove to be sound. Glaser and Weber (2003) argued that there are three aspects of overconfidence, viz., miscalibration, the ‘better-than-average’ effect (i.e., people tend to think that they have higher than average skills), and illusion-of-control (i.e., the tendency to believe that one’s personal probability of success is higher than what objective probability would warrant). They establish that all but miscalibration lead to higher trading activities.

Barber and Odean (2001) argued that the relationship between gender and trading activity is due to the greater overconfidence of men. The evidence from their study suggests that single, young male investors tend to trade most frequently. They also found that the turnover of males exceeded that of females, which they attributed to the greater overconfidence of males.

Malmendier and Shantikumar (2003), in their study of small investors, found that, while large investors adjust their reaction to hold and buy recommendations downward, small investors take recommendations literally. Small investors also fail to account for the additional distortion due to underwriter affiliation. Potential reasons for their trading behaviour are: (1) higher costs of information; and (2) naivete about analysts distortions. Small investors may be naive about the distortions and trust analysts too much.

Graham et al. (2004) found that home bias, coupled with the competence effect plays a major role in high trading frequency. They came up with the idea that investors who feel more competent tend to trade more frequently than those who feel less competent. The competent effect also contributes to home bias. When an investor feels more competent about investing in foreign assets, he is more willing to shift a portion of his assets overseas. Their study indicated that investors with higher competence are more likely to invest in international assets.

The role of two psychological attributes in the trading tendency of investors has been studied by Grinblatt and Keloharju (2006). They analyzed the role played by sensation seeking and overconfidence in the tendency of investors to trade stocks. They found that overconfident investors and those investors more prone to sensation seeking, trade more frequently. Thus, for most investors, trading is driven by behavioural attributes.

Cohn-Urbach and Westerholm (2006) attempted to determine whether the frequency of trading on the part of household and institutional investors had an effect on the returns they achieved. They found strong evidence that investors with high trading frequency earned substantially lower returns than those investors in the same demographic group who traded less frequently. It was shown that investors with larger portfolios tended to trade more frequently than those with smaller portfolios. Further, it was demonstrated that those investors with larger portfolios tended to trade actively for a longer period of time than those who held smaller portfolios. They also found that a similar relation exists for institutional investors. This indicates that institutional investors are prone to some biases which are also apparent in household investors. Trading is, however, not as hazardous for institutional investors as it is for household investors; institutional investors earn superior returns even if they trade more frequently than household investors Danial (1961).

METHODOLOGY:

The traditional finance theory assumes investors as rational beings and predicts that each and every activity of an investor is aimed at maximizing his/her expected utility. The literature available in economics also predicts that human activities are aimed at utility maximization. So far as stock trading frequency is concerned, it is obvious from the assumptions of traditional finance theory, as well as the concept of rational human being, that investors would trade only when they think the trade will result in an increase in expected utility, i.e., trade will add some expected utility to their portfolio. More frequent trading would lead to higher return from the investments. But, the actual scenario is quite different. Investors are usually influenced by psychological biases, such as overconfidence and the competence effect, and this frequent trading result in reduced returns because of more transaction costs, etc.

Therefore, this study explores the following questions:

• How comfortable do investors feel in handling financial products, investment alternatives and subsequent investment decisions.

• What factors influence the trading behaviour of investors and do they trade frequently on the basis of their competence.

Harris (2003) an attempt is made here to find whether the feeling of competence in individual investors influences their trading decisions. It implies that individual investors make their trading decisions based on the classical finance theory of risk-return fundamentals, rather than being influenced by behavioural biases. Based on the above research questions and the already stated purpose of the study, the following hypotheses are formulated:

Overconfidence caused by a number of factors, affects the feeling of competence of

investors and thereby their willingness to act on their judgments.

Overconfidence in an individual investor may be concerned with his/her own perception of his/her ability and knowledge. If he/she feels more confident in any context, he/she is likely to act more frequently on his/her decisions. The next step would be to study the effects of overconfidence on investors’ willingness to act on his/her own judgments on investment-related issues.

Individual investors, who perceive themselves as more competent, tend to trade more frequently.

Finally, an attempt is now made to identify the competence effect in trading frequency. The high trading activity is usually attributed to the investor’s overconfidence. Overconfidence is distinct from the competence effect to a great extent. It is proposed here that high competence among investors motivates them to trade frequently. They are prompted to act on their judgments once they feel more skilful and knowledgeable. Therefore, how much individual investor’s trading frequency is influenced by the competence effect is now examined.

In order to examine the behaviour of individual investors, this study used a modified questionnaire. To achieve the objective of the study, the investor competence and trading frequency needed to be measured. The questionnaire used in the study included questions related to competence and trading frequency. The respondents were asked to give their choices for each question in the questionnaire on a five-point Likert scale. Respondents were either asked survey questions in person or they were mailed the questionnaire with a request to send the same back after completion.

To measure investor competence, a hypothetical model is proposed. This model assumes that an investor’s competence is a combined function of his/her sex, education, age, and income. The determinants of investor competence have been investigated using the empirical model proposed by Graham et al (2004). This study models competence as a combined function of investor characteristics such as gender, age, education, and income. The study also uses the estimated coefficients from regressing competence on the characteristics to construct predicted competence for each investor included in the survey. The term ‘competence’ used here includes skill as well as knowledge or understanding Heath and Tversky (1991). The feeling of competence in individual investors is determined by what they know, relative to what can be known. Thus, it can be enhanced by obtaining knowledge of stock market functioning, familiarity with investment-related issues and experience, and diminished, for example, by calling attention to relevant information that is not available to the individual investor as decision maker, especially when it is available to others. Competence can be defined as the subjective skill or knowledge level in a particular area, and as far as this study is concerned, competency means an investor’s perceived skill and knowledge in the area of finance and allied issues. It is widely seen that higher level of education and income make an individual feel more competent in almost all the areas including finance. It remains to be established whether any relationship exists between the feeling of competency of the investors and their trading frequency.

TARGET POPULATION:

The target population on which this research is conducted on are the individual investors who frequently visit the BSE (Bombay Stock Exchange) and NSE (National Stock Exchange). Investors selected for this study have their investments in shares and other investment vehicles available for trading on the Indian stock markets, both on the Bombay Stock Exchange (BSE) and the National Stock Exchange (NSE). Investors whose investment in stock market is between Rs. 3,00000 and Rs. 10,000,00 were included in the study. This helps Individual Investors Trading Behaviour and the Competence Effect make the study more reliable because the sample selected for the study is taken from different strata/class of individual investors. The data collected, hence, has the advantages of covering a wide range of investor classes and account types. Proper care was taken to ensure that respondents, i.e., investors, understand all the questions asked during the survey, and answer them truthfully. As we do not have the detailed investments of the individuals, we do not know how their portfolios of investment actually perform. We are, however, not concerned with the portfolio performance in this study.

RESEARCH APPROACH:

Saunders (2003) opined about two types of research approach. Deductive approach and inductive approach:

DEDUCTIVE APPROACH:

A theory or hypothesis is being developed and a research strategy is designed to test the hypothesis. It begins with theoretical conceptualization and then moves on to testing through the application theory so as to create new experiences or observations . In this research a research question is being developed and the dissertation aims to answer the question by means of the general principle and established facts. According to Saunders (2003) a deductive approach owes more to positivism. As the researcher’s study deals with more positivism a deductive approach can be adopted in this research.

A deductive study should have,

A hypothesis that overconfidence caused by a number of factors, affects the feeling of competence of investors and thereby their willingness to act on their judgments.

To decide the research population in which the researcher could find the customer’s perception on the competence of investors.

To administer the questionnaire to a sample of regular investors.

To be particularly careful about defining service quality and customer satisfaction

To standardise the response of the sample selected.

RESEARCH STRATEGY:

The research strategy undertaken depends on how the problem looks, what questions the problem leads to and what end result is desirable (Merriam, 1994). The research strategy is a common plan for how the researcher is getting the answers for the research questions. Here the topic gives the researcher a chance to employ both qualitative and quantitative methods for research. Krueger (1998) opined Combining both qualitative and quantitative methods gives a greater methodological mix that would strengthen the research. This approach will allow the author to facilitate ability and dependability in what is found.

QUANTITATIVE DATA:

Quantitative data could be measurable and identified on a numerical scale. Moreover these quantitative data will be used to pass on information to management team in the simple ways like graphs and charts following analysis using the SPSS (Statistical Package for Social Sciences). These data can be used for the assessment and tracking of the performance of the organisation in the service sector and their competitive positioning in the market.

Standardised questionnaires will give to the customers after they were carefully planned, piloted and collected in order to give the researcher important statistical and factual data straight from the customers.

QUESTIONNAIRE:

Chisnall (1997) explained a questionnaire is a method of attaining specific information about a defined problem so that the data, after analysis and interpretation, result in a better appreciation of the problem. It is an important element of the total research design, and a considerable professional expertise is essential for its preparation and administration. Smith (1986) suggest that, in some respects ‘questionnaires’ are a whole methodology on their own: that is a class of methods rather than any single method. And therefore it is not surprising to find them covering a wide range on the dimension between full evaluator control and full informant control.

LIMITATIONS:

Smith (1986) claim that there are of course, many limitations to questionnaires:

they are more helpful for gathering superficial data than in depth data.

It is not easy by questionnaires to adapt changing circumstances and needs; and the response rate to questionnaires can be extremely low, particularly when they are mailed through the post Smith (1986).

TIME HORIZONS:

A mix of both cross sectional and exploratory study will be doing by the researcher. Cross sectional study helps to make comparative study with analysis of the data in relation with theoretical concepts, which helps for further research. Exploratory study has been chosen in order to explore the operation of the sector in detail and understand the operation of the sector which would help to proceed further with collections of data’s qualitatively (Saunders et al 2003).

DATA COLLECTION METHODS:

SAMPLING:

The study employed the random sampling technique for conducting the survey, since in this technique, every member of the pool of individual investors has an equal chance of being selected in the sample. Random sampling is the best technique for providing an unbiased representative sample of investors. The mass of the individual investors interviewed/contacted were selected randomly from across the BSE or NSE zone. The criterion used for selecting those individuals in the survey for the purpose of data collection is that they hold investment in shares and other exchange-traded market instruments of Rs. 300,000 or more. Researcher prefers to go for a Non probability Convenience sampling where the sampling will be randomly until it satisfies the requirements of the research (Saunders et al, 2003).

SECONDARY DATA:

The researcher has access to a wide range of facilities of the Learning Resource centres of the universities in Liverpool and also to the Central Library of the Liverpool city. So the researcher will be able to use various forms of secondary data’s, journals, books, websites which will enhance the critical review of the literature and a cross sectional and exploratory study in detail.

LIMITATIONS:

Secondary data may not be up to date, as they have been shaped in an earlier period.

Saunders et al (2003) identifies the limitations of secondary data as

It may be collected for a purpose that does not match the researcher need.

Sometimes it may be collected for a purpose that does not match the researcher need.

Sometimes the access for the data may be costly.

PRIMARY DATA:

The major source of primary data is through questionnaire survey. A structured questionnaire will be given to target people. Questionnaires will form the main basis of the research, this is due to the fact that this research study will require Opinions, attitudes, views, beliefs, preferences to be recorded and these can be investigated using questionnaires

PERSONAL SUITABILITY:

Currently I am persuing my Masters in Business Administration at Liverpool John Moores University with one my optional module as Corporate Finance & Envronment which helped me a lot to understand the basics of Trading and Inestment Banking. I have successfully finished all modules in my 1st semester. Presently I am waiting for the result of my second semester. My extra-curricular activities have improved my organisational and time management potential. Throughout my education and my career I had to do a lot of research and this has improved my analytical capabilities, which would help in deriving a valid conclusion.

RESEARCH ETHICS:

Research ethics involves the application of fundamental ethical principles to a variety of topics involving scientific research. These include the design and implementation of research involving human experimentation, animal experimentation, various aspects of academic scandal, including scientific misconduct etc Shaw et al (2009).

There are many ethical issues to be taken into serious consideration for research. Sociologists need to be aware of having the responsibility to secure the actual permission and interests of all those involved in the study Hubert (2007). They should not misuse any of the information discovered, and there should be a certain moral responsibility maintained towards the participants. There is a duty to protect the rights of people in the study as well as their privacy and sensitivity. The confidentiality of those involved in the observation must be carried out, keeping their anonymity and privacy secure. As pointed out in the BSA for Sociology, all of these ethics must be honoured unless there are other overriding reasons to do so - for example, any illegal or terrorist activity.

PROTOCOLS:

DATA INTEGRITY:

According to Davies (2004) Data integrity is data that has a complete or whole structure. All characteristics of the data including business rules, rules for how pieces of data relate, dates, definitions and lineage must be correct for data to be complete.

Per the discipline of data architecture, when functions are performed on the data the functions must ensure integrity. Examples of functions are transforming the data, storing the history, storing the definitions (Metadata) and storing the lineage of the data as it moves from one place to another. The most important aspect of data integrity per the data architecture discipline is to expose the data, the functions and the data's characteristics.

Data that has integrity is identically maintained during any operation. Put simply in business terms, data integrity is the assurance that data is consistent, certified and can be reconciled.

INTERVIEWER QUESTIONNAIRE CHECKLIST:

The checklist will be designed making sure the questionnaires are fully and accurately completed. The following will be assured:

The researcher will always ensure that the interviewer has investments in BSE or NSE and has the time available to complete the questionnaire.

The respondent will be free to work through the questionnaire

The researcher will make sure all responses are unambiguous.

A brief idea of the research will be included in the questionnaire.

On receipt of completed questionnaires they will be loaded to SPSS.