A search of investors' trading practices in the Bangladesh capital market

Abstract

Purpose

This research mainly intends to ascertain the stimulus of investor investment tendencies on the amount of capital investment in the share market.

Design/methodology/approach

Utilizing a sample of 477 individual investors who actively trade on the Bangladesh capital market, this empirical study was conducted. The objective of this examination is to ascertain the investment trading behavior of retail investors in the Bangladesh capital market using multiple regression, hypothesis testing and correlation analysis.

Findings

The coefficients of market categories, preferred share price ranges and investment source reveal negative predictor correlations; all predictors are statistically significant, with the exception of investment source. Positive predictive correlations exist between investor category, financial literacy degree, investment duration, emotional tolerance level, risk consideration, investment monitoring activities, internal sentiment and correct investment selection. Except for risk consideration and investment monitoring activities, all components have statistically significant predictions. The quantity of capital invested in the stock market is heavily influenced by the investment duration, preferred share price ranges, investor type, emotional toleration level and decision-making accuracy level.

Research limitations/implications

This investigation was conducted exclusively with Bangladeshi individual stockholders. Therefore, the existing study can be extended to institutional investors and conceivably to other divisions. It is possible to conduct this similar study internationally. And the query can enlarge with more sample size and use a more sophisticated econometric model. Despite that the outcomes of this study help the regulatory authorities to arrange more informative seminars and consciousness programs.

Practical implications

The conclusions have practical implications since they empower investors to modify their portfolios based on elements including share price ranges, investment horizons and emotional stability. To improve chances of success and reach financial objectives, they stress the significance of bettering financial understanding, active monitoring and risk analysis. Results can also be enhanced by distributing ownership over a number of market sectors and price points. The results highlight the value of patience and giving potential returns enough time.

Originality/value

This study on the trading behavior of investors in Bangladesh is unique and based on field study, and the findings of this study will deliver information to the stakeholders of the capital market regarding the investors’ trading behavior belonging to different categories, financial literacy level, investment duration, emotional tolerance level and internal feeling.

Citation

Ghosh, S.K. (2023), "A search of investors' trading practices in the Bangladesh capital market", LBS Journal of Management & Research, Vol. 21 No. 2, pp. 250-265. https://doi.org/10.1108/LBSJMR-04-2023-0015

Introduction

The market for stocks serves as the pulse for a nation's economy (Ullah, Kabir, & Ahmmed, 2012) which circulates and transfers funds to deficit units from the surplus units of an economy. Without an efficient and sound stock market, a country cannot achieve rapid economic growth. The stock exchange acts as a barometer of a nation's economic progress (Vijaya, 2016). We know that in the economy, there are usually two sectors. Between them, the business organizations issue their shares at the market and collect capital from the households. Share is a part of the ownership, and the individual shareholders will become a member of and are entitled to receive paybacks from the corporate. Stocks’ trading in the market is inaudible simple that requires some elementary acquaintance of the security transaction. Individual investors’ trading behavior denotes the regular course of actions used by an investor to create the desired portfolios. With the view of making an informed investment decision, whether buying or selling stocks, it is crucial to comprehend the investing strategy of retail investors. Usually, investors’ attitude has been changing due to changing the stock market environment. When the stockholders gain precise and dependable information, then they can undergo the palate of victory from the stock market, which is entirely dependent on the investor’s understanding regarding the stock transaction. When the stockholder finds new and further news concerning the fluctuations in the investment atmosphere, he/she can make up the correct investment choice at the appropriate moment in time. In the modern competitive world, business firms require more capital to cope with the dynamic business environment. For collecting these amounts, business firms issue more securities of their business to the market and accumulate the deficit funds from the households. Investing in the share market emerged as a lucrative investment source for individual investors who expect higher returns and will to get the associated risks. For trading on the stock market to be effective, one must be aware of investor trading habits. Other researchers also acknowledged it.

Bangladesh capital market

The concept of the Capital market emerged at Wall Street in the USA in 1653. And it started in 1890 in South Asia. Two stock exchanges operate in Bangladesh. One is Dhaka Stock Exchange (DSE), situated at Motijheel, Dhaka and the other is Chittagong Stock Exchange (CSE). The Bangladesh capital market is governed and run in accordance with its bylaws, rules and articles of association. The Securities & Exchange Commission Act of 1993, the Companies Act of 1994, and the Securities and Exchange Ordinance of 1969 are further regulations that governed the capital market in Bangladesh. Between the two Bangladeshi stock markets, DSE first came into existence between 1954-56 as East Pakistan Stock Market and was renamed Dacca Stock Exchange Ltd. in 1964. Now it is registered as a public limited company, but in the beginning, it was a shared organization that is; cooperative body. The operations of the Bangladesh capital market stayed deferred for the liberation war in 1971 till August 1976. The transactions in the stock market started again with only 14 listed firms at that time. The market worth was Tk. 90 million. During the 1980s, different initiatives took to enhance the trade volume, but authority failed to attract investors. First Time, the total trades daily surpassed Tk. 1 crore in April 1992. In 1993 security and Exchange Commission was made for regulating and supervening the stock market. The second stock market was founded and organized in 1995 and is known as the Chittagong Stock market (CSE). Since 1998, both stock exchanges have begun offering online trading services (Ullah et al., 2012). Bangladesh is one of the next eleven rising market middle-income nations, and its two main stock exchanges are the Dhaka Stock Exchange and the Chittagong Stock Exchange (en.m.wikipedia.org/wiki/Economy of Bangladesh, 2019). It has ample opportunities for industrial growth, which could ultimately accelerate economic development. For accelerating economic development, long-term funds are essential, and the capital market has a vital role in any economy as a long-term financing source (Bangladesh Bank Annual report, 2010). So a sound, unwavering and efficient capital market as the heart of any economy is required. Since their establishment, these two markets had experienced two big crashes in 1996 and 2011. The government took different steps to wear out the impact of those crashes on the share market. But still, it is beyond the control of the government. Brokerage companies are currently assisting investors in making wise stock investments. The major products of Bangladesh Capital Market are Shares and bond.

Review of literatures

Mishra, Bansal, Maurya, Kar, and Bakshi (2023) found out that attitude, knowledge and participation in investment decisions were revealed to be the most influential factors in determining investment intent, followed by self-efficacy, perceived usefulness, subjective norms, felt emergency, as well as perceived risk. Zahera and Bansal (2019) found out that the disposition effect is typically observed among private investors, and its prevalence can be affected by demographic variables including age, gender, experience and financial sophistication. Managers of mutual funds and institutional investors could be affected by the disposition effect. Researchers discovered that investors had sufficient control over their investments to minimize risk and maximize return. The disposition effect is studied predominantly in the United Kingdom, the United States, China, as well as the European Union, with less consideration given to developing nations. According to what Sarbabidya and Saha (2018) discovered in their article, decisions about investment in the Bangladeshi stock market were influenced by risk considerations as well as the impulsive viewpoint of stockholders. Zahera and Bansal (2018) revealed that investors are susceptible to cognitive fallacies when making financial decisions, highlighting the significance of understanding and implementing finance theories in order to generate profitable investments. According to the study, corporations, legislators and security issuers can safeguard the best interests of investors by acting in advance. By becoming aware of their own behavioral biases, investors may be able to make better judgments and reduce their risk exposure, according to the research. Utilizing the Chi-square test, Khanam (2017) found in an article that there was a substantial association that existed between investors' investment decisions and their degree of education, trading experience, occupation and income level. She made this discovery utilizing the article. A study on the factors that are persuasive to investors was directed by Ahmad (2017). An empirical work on Pakistan's financial marketplaces showed that the most significant issues affecting individual behavior were the dividends paid, predictable corporate incomes, stock marketability, financial reports condition, indicators of the existing economy, historical performance of a firm's stock, recommendations from brokers, firms' status within the industry and the desire to become wealthy quickly. The findings of Sarkar and Sahu (2017) showed that Individual investors' imagined risk aversion was in an acceptable position. Their apparent risk outlooks were not founded on an emotional component; rather, they were dependent on the cognitive processes that are involved in the acquisition of new information. These processes include remembering, knowing, reasoning, judging and problem-solving. It is the heuristics dimension and the prospect dimension, and it represents a person's perspective of something or someone else. The stock market displayed solid market behavior for investors to take advantage of. Both an individual's demographic characteristics and their level of risk tolerance affect their stock market activity. Overconfidence, anchoring, representativeness, disposition effect, mental accounting, herding behavior, regret aversion, loss aversion and market concerns were revealed to have influenced investment decisions by Vijaya (2016). The findings of Akbar, Salman, Mehmood, and Makarevic (2016) showed that individual investors' decisions regarding investment are strongly persuaded by the availability of unbiased information, advice from supporters, the investor's own self-image and the company's public image. However, there was no correlation between accounting information, traditional methods of wealth accumulation and the specific financial requirements of individuals. Researchers Grover and Singh (2015) conducted a study titled “Behavioural Determinants Inducing Investment Decision in Real State: A Case Study of Udham Singh Nagar (Uttrakhand)” and found that investors in Udham Singh Nagar were affected by cognitive biases such cognitive dissonance, Mental Accounting, Regret Aversion, as well as Loss Aversion, as well as biases like Gambler's fallacy, Representativeness, Overconfidence, Anchoring, Herding, as well as Availability. A study by Purohit, Satija, as well as Saxen (2014) titled Investor Psychology: An Empirical Analysis found that retail investors' decision-making behavior differs depending on their demographic traits. As what they referred to as “rational investors,” they utilized behavioral and cognitive psychology in the process of making financial decisions. Jayaraj (2013) did research to find out what aspects that are significant in deciding the actions of individual investors in India. The most important characteristics were restraint, diligence and discretion, the ability to repudiate regret, perception, judiciousness and vigilance. Akhter and Ahmed (2013) investigated what influences the amount of money invested in the Bangladeshi stock market, and they conclude that the firms' reputations, standings, feelings about any firm's products as well as services, and involvement in the procedure of discovery results to matters prevalent in the local community are the most important factors. According to the findings of Hossain and Nasrin (2012), the utmost significant considerations for retail investors in Bangladesh are the characteristics of the companies in which they invest their personal financial needs, their level of education and their level of expertise. According to Islam (2012), the supreme influential aspect inducing decision-making in the stock market is the psychological component. Other elements influencing investment security selection included the microeconomic and societal considerations. In their research, Rashid and Nishat (2009) found that the influences that investors considered to be the most influential were the company's efficiency, the ease and speed with which transactions could be completed, the rate of inflation, the transaction charge, the investor's ability to enter the company, as well as facts about the industry, the informational quality and their preceding acquaintance of securities. In India, Kabra, Mishra, and Dash (2010) directed a research with the goal of determining the elements that influence people's decisions to invest. The factors that had an effect were security, the expertise of financial professionals, share brokers and patricians; the attentiveness of investment plan and financial scheduling; the length of time, hedging and paybacks.

Rationale of the study or research GAP

Investors’ behavior is a hot topic in numerous investment theories, including Modern Portfolio Theory (1952), Contemporary Investment Theories (1953), Capital Assets Pricing Model, Arbitrage Pricing Model (1976) and the Efficient Market Hypothesis (1965). Modern investment theories evolved from Neumann and Morgenstern's expected utility model, which stated in 1953 that shareholders’ decision-making is governed by the trade-off between return and risk. Investors' decisions are primarily influenced by their risk tolerance. A rational investor seeks to maximize utility; therefore it is natural for them to choose the investment with the best return. According to Statman (1999), modern investment theories are built on the arbitrage philosophies proposed by Miller and Modigliani. Notable philosophies that have added to the advance of modern portfolio theory include Markowitz's portfolio theory, Sharpe, capital asset pricing models of Linter, and Black, as well as Black Scholes' concept of option pricing. These ideas are classified as Standard Finance, also known as Traditional Finance and assume that investors are logical, intelligent and competent. The Modern Portfolio Theory, developed byHarry Markowitz, examines investment portfolios and emphasizes portfolio building by taking into account the probable return and risk of individual equities. According to Omisore, Yusuf, and Christopher (2011), the Modern Portfolio Concept as well as the Efficient Market Hypothesis have identical philosophies since both theories believe that investors make rational investment decisions and that the market is entirely efficient. Investors are risk-averse, according to the Modern Portfolio Philosophy, and if two assets offer comparable yields, investors are more inclined to choose the asset with the lowest risk level. Investors are primarily compensated for receiving systematic risk in the Capital Asset Pricing Model. Diversification, according to the Modern Portfolio Philosophy, can help eliminate unsystematic risk. Arbitrage is the process of generating risk-free returns by capitalizing on the advantages of varied prices for the same assets in multiple marketplaces. Although utility-based theories of finance presume that people will act in ways that maximize their happiness by adhering to the traditional wealth criteria, in practice, decisions made on the basis of these theories rarely address individual investor behavior. In contrast, in 1979, Kahneman and Tversky presented a new concept that departs significantly from the standard utility theory and is instead motivated by affective and cognitive components. As a result, it had a significant influence on the development of behavioral finance. It's an analysis of people's actions under a controlled monetary environment. According to the prescriptions of Based on the work of Kahneman and Tversky, the authors of the prospect and heuristics theories, this investigation highlights the impact of behavioral factors on stock market investment decisions. According to the prospect hypothesis, investors are not risk-averse by nature but are more risk-averse while gaining than when losing (known as the certainty effect; Kishore, 2004). Sometimes, investors make choices based on the general trend of the market. Investor behavior that is slow to accept failure and fast to sell success. Price fluctuations, market knowledge, historic stock patterns, consumer preference, overreaction to price variations, as well as the basics of underlying equities are all factors that influence investors' decisions, as outlined by Waweru, Munyoki, and Uliana (2008). People tend to place more weight on recent events and less on the average throughout time (Ritter, 2003). It has been clear from this conversation that investor conduct is dynamic and constantly shifting. Individual investors' trading habits significantly impact the total amount of capital allocated to the stock market. The behavioral finance theory posits that an investor's actions within the capital market are contingent upon the sentiments, cognitions and propensities toward risk-taking of their counterparts. Eminent scholars such as Gruber (1996) and Hallahan, Faff, and McKenzie (2004) have demonstrated that the trading patterns of investors are influenced by a diverse array of individual and contextual factors. Sabir et al. (2021) found that financial literacy acted as a check on the risk-taking behavior of individual stock market investors. Conservativeness, diligence, discretion, regret aversion, belief, thoughtfulness and prudence have all been shown by Jayaraj (2013) to influence the trading behavior of individual investors. Investors are generally less cautious than previously thought, as Mistry (2015) found. Tanvir, Sufyan, and Ahsan (2016) have also revealed the value of emotional acumen when making financial decisions, highlighting the crucial part it plays in the selection of appropriate assets. The emotional impact on decision-making has been further revealed by Seo and Barrett (2007), who establish a connection between this phenomenon and the authors' own experience as investors. Markowitz (1952) expanded on this idea by recommending that private investors think in terms of the long term when making investment decisions. In addition, Wood and Zaichkowsky (2004) studied the mindset and trading patterns of investors, classifying them into four groups: the risk-averse, the confident, the young and less risk-averse and the conservative long-term. Furthermore, Lodhi (2014) has established that a person's financial literacy degree boosts their risk-bearing capacity by discussing the positive link between investors' financial literacy and their risk-taking capacity. According to research by Rehman and Arif (2015), traders on the Karachi shares Exchange are more likely to make speculative purchases of shares with a short-term horizon. According to Al-Tamimi (2006), the organization of financial markets is a significant element affecting the actions of investors in the United Arab Emirates. The psychology of risk also has a big effect in how people invest, as discovered by Phan and Zhou (2014). Although investor behavior varies from country to country, most research have found that retail investors make investing choices built more on sentiment than logic (Islam, 2012). There is notably little study on the investing habits of Bangladeshi citizens in the stock market. In general, the subsequent are some of the research questions that are being asked:

RQ1.

Does the investor's trading activity affect the amount of capital invested in the capital market?

RQ2.

What are the most influential in explaining the variation in the amount of capital invested by investors in the capital market?

Objectives of the study

To be more precise, the study proceeded with the subsequent objectives:

1. To evaluate the statistical significance of the correlation between the trading practices of investors and the degree of capital investment in the stock market, in order to determine the extent to which these variables are interrelated.

2. To rank the most influential in explaining the variation in the investors' capital investment in Bangladesh by utilizing higher squared semi-partial correlations and rank orders.

3. To provide suitable recommendations to individual retail investors to formulate their investment choices effectually.

Research hypotheses

1. H1 = The relationship between the trading habits of investors and their investments in the stock market bears great significance and depth.

2. H2 = The categories of markets, the origin of investment and the price intervals of stocks which investors choose to put their money in, all exhibit a negative relationship with the quantity of investments made.

3. H3 = The predictors including the category of investors, their level of financial literacy, investment duration, emotional tolerance level, consideration of risk, investment monitoring activities, internal feeling and the ability to make correct investment decisions have a direct and positive influence on the amount of capital invested.

Methodology of the study

This segment is into the following parts:

Nature and approach of the study: This study is conducted based on an extensive survey carried out in the field. The fundamental basis for this examination is the qualitative method. The method involves the collection of quantifiable information from individual investors through in-person interviews and a questionnaire-based survey conducted via electronic mail. The data collected through qualitative means will be analyzed using quantitative techniques. The final stage of this research will entail drawing conclusions from the stock trading movement of investors, with the aid of the information garnered from the inquiry. This will help to shed more light on the behavior of private investors in the stock market and assist in identifying the key factors that influence their trading decisions. The outcome of this study will be a valuable resource for those seeking to gain a better understanding of the stock market and its participants. The data gathered will be useful for future research and a necessary reference point for anyone interested in the topic.

Variables selection: The present investigation utilizes previous academic papers to illustrate the investment habits of Bangladesh's capital market investors. This study scrutinizes a range of variables including investment amount, decision-making procedures, market types, investor groups, favored price ranges, risk evaluation, investment monitoring activities, investment origins, investment duration, emotional resistance, financial knowledge and inner feelings. The above-mentioned variables have been investigated in prior research (Mistry, 2015; Tanvir et al., 2016; Gnani Dharmaja, Ganesh, & Santhi, 2012; Sarkar & Sahu, 2017; Parameswaran & Balagobei, 2014; Rehman & Arif, 2015; Lodhi, 2014; Wood & Zaichkowsky, 2004; Phan & Zhou, 2014; Markowitz, 1952; Jain & Mandot, 2012; Arif & Bhuiya, 2016; Khanam, 2017; Sochi, 2018) and are believed to have a significant impact on shaping the trading practices of investors in Bangladesh's capital market. Through this research, the researcher hopes to gain a deeper understanding of the unique and complex investment patterns of these investors, which could potentially aid in the development of better investment strategies and policies that will promote the growth of Bangladesh's capital market.

Questionnaire development: The research conducted had a descriptive focus, which involved collecting information to answer questions about the subjects' situation. This type of research is based on closed-ended questions that have been developed after a thorough review of relevant prior works. The questions used in this research were derived from various sources, including Sochi (2018), Sarkar and Sahu (2017), Khanam (2017), Tanvir et al. (2016), Arif and Bhuiya (2016), Mistry (2015), Rehman and Arif (2015), Lodhi (2014), Phan and Zhou (2014), Jain and Mandot (2012), Gnani Dharmaja, Ganesh, and Santhi (2012) and Markowitz (1952). The reliability and validity of this study were confirmed through a pilot analysis and an evaluation of the responses by experts in the field. The descriptive nature of this research allowed for a comprehensive understanding of the subjects' situation, which can be used to inform further studies or interventions in the field. The utilization of closed-ended questions ensured a standardized approach to data collection, which is essential for accurate analysis. Overall, this research provided valuable insights into the subjects' situation and can serve as a foundation for future research in the field.

Sampling and data collection: In this particular investigation, the primary data have been utilized. The study comprises participants hailing from three prominent divisions of Bangladesh: Khulna, Dhaka and Rajshahi. All the retail investors have been included as a part of our sample for the purpose of our analysis. The study’s presumption is that the population is infinite for statistical purposes, considering the fact that the number of investors keeps fluctuating from time to time. Furthermore, according to the Krejcie and Morgan Table, it has been required to collect a minimum of 384 samples for a population of at least one million, as suggested by Rahman in 2023. However, for the study, the researcher has managed to gather 477 individuals from a wide range of brokerage houses in the aforementioned divisions who have provided us with the necessary information. These individuals were selected entirely at random, with the scheduling technique and random sampling being implemented to ensure that an unbiased approach has been maintained throughout the study. The researcher has interviewed a diverse group of respondents, including company executives, stockbrokers, auditors, cost and management accountants and so on. The reason the researcher has chosen such a varied group is that we want to ensure that we have a well-rounded perspective of the market and its players. The researcher believes that by doing this, he can analyze the market from multiple perspectives and provide a more comprehensive and accurate analysis of the situation.

In addition to primary data, the researcher has made use of secondary data that he acquired through various sources. He thoroughly researched journals, manuals, various published and unpublished records, bulletins, annual reports, magazines, etc. to obtain the necessary information. The researcher has ensured that the secondary data are just as thorough and comprehensive as the primary data, so that informed and accurate conclusions can be drawn based on the research.

Overall, it has been believed that the study will provide a unique and valuable insight into the market and the investors that make it what it is. By using a combination of primary and secondary data, a well-rounded approach has been developed that will allow investors to draw informed and accurate conclusions based on the research.

Data analysis: By employing a range of statistical techniques, such as multiple regression, hypothesis testing, regression equations and rank-order analysis, the objectives of the study will be fulfilled. The study has utilized multiple regression and rank-order analysis to evaluate and assess the impact of investors' trading behavior on the amount of capital invested in the market. In addition, hypothesis testing, regression equations and correlation analysis have been used to establish connections between the various trading strategies adopted by investors in Bangladesh's capital market. The utilization of these statistical methods has enabled a comprehensive examination of the data, providing valuable insights into the behavior of investors in the capital market. The study's findings will have far-reaching implications for future investment decisions and market operations. The use of these techniques has contributed to a more nuanced understanding of the complexities of the market and investors' reactions to it, providing valuable insights into the dynamics of the capital market.

Analysis and discussion

Multiple regression analysis:

Table 1 shows the result of the multiple regression investigation. The R column denotes the value of the multiple correlation coefficient. It uses to measure the quality of prediction of the dependent variable. In this analysis, the correlation coefficient (R) represents the strength and direction of the linear relationship between the dependent variable and the combination of all predictor variables. In this table, R is approximately 0.731. This value indicates a moderate to strong positive linear relationship between the predictors and the dependent variable. The coefficient of determination (R²) measures the proportion of the variance in the dependent variable that is explained by the predictor variables in the model. In this case, R² is approximately 0.534, which means that about 53.4% of the variance in the dependent variable is accounted for by the predictor variables in the model. This value indicates a moderate amount of variation explained by the predictors. The adjusted R² value (approximately 0.523) is slightly lower than the R² value, suggesting that some of the predictors may not contribute significantly to the model's explanatory power. This value (0.674) represents the standard deviation of the residuals (the differences between the actual observed values and the predicted values from the model). It provides a measure of how well the predicted values match the actual data points. A lower value indicates a better fit of the model to the data. In summary, the model explains a moderate proportion of the variance in the dependent variable (R²) and the adjusted R² suggests that the model is reasonably well-fitted while considering the complexity of the predictor variables. The correlation coefficient (R) suggests a moderate to strong positive linear relationship between the predictors and the dependent variable. The standard error of the estimate indicates the average amount of error in the predictions of the model. The list of predictors provides insight into the variables that were considered in the model to explain the variation in the dependent variable.

The variable under investigation in this study is the level of capital investment in the stock market. Table 2, titled “ANOVA Table” (Analysis of Variance), displays the various factors that contribute to the variability of the model, hence facilitating the creation of predictions. The evaluation of the significance of the regression model and its individual components can be conducted through the utilization of ANOVA. The column displays the sum of squared deviations from the mean for each source of variance. The categorization consists of three components, namely “regression,” “residual” and “total.” The Sum of Squares (SS) for the regression model is calculated to be 241.925. This is the extent to which the regression model can accommodate uncertainty. The residual's sum of squares (SS) is calculated to be 211.274. The term “unexplained variance” refers to the portion of variance or error that is unaccounted for by the regression model. There are a total of 453,199 squares. This represents the magnitude of dispersion exhibited by the dependent variable. The number of predictor variables in the “regression” model is 11, resulting in a matching value of 11 for the degrees of freedom (df). The degrees of freedom (df) for the “residual” may be calculated by subtracting the number of independent variables (11) from the total number of observations (476), resulting in a value of 465.0. The degrees of freedom (df) for the variable “total” is equal to 476, which represents the total number of observations. The observed value of F in this particular sample is 48.505. The importance of a regression model is demonstrated by an augmentation in the F-statistic. The p-value associated with the F-statistic is provided in this document. The assessment determines the statistical validity of the complete regression model. The p-value, which is significantly small (0.000), suggests that the regression model possesses a high level of statistical significance.

Table 3 displays the results of a linear regression study, in which the amount of capital invested in the stock market was the dependent variable and numerous criteria were used to generate predictions about the amount of each. Coefficients, standard errors, standardized coefficients (betas), t-values and p-values are all displayed in the appropriate table cells alongside other relevant information for each predictor variable. The dependent variable here is the total amount of capital invested, and the coefficients in question show how much that variable would shift if the predictor variable were to shift by one unit (all other factors being held constant). Predictor variables including “market types,” “the investment source” and “price ranges of shares investors prefer to invest in” are all inversely correlated with investment volume. Decreases of 0.232, 0.067 and 0.322 units in these predictor variables are associated, respectively, with falling capital investment levels. Increases of 0.305, 0.188, 0.518, 0.264, 0.015, 0.017, 0.211 and 0.254 units in “investors' category,” “financial literacy level,” “investment duration,” “emotional tolerance level,” “risk consideration,” “investment monitoring activities,” “internal feeling” and “correct investment decision,” respectively, are positively correlated with increases in the amount of capital invested. Comparisons of different predictors can be made using standardized coefficients. For “market types,” “the investment source” and “price ranges of shares investors prefer to invest in,” the standard deviation of the predictor is inversely related to the amount of capital invested, falling by 0.069, 0.064 and 0.210, respectively. Standard deviations of “investors' category,” “financial literacy level,” “investment duration,” “emotional tolerance level,” “risk consideration,” “investment monitoring activities,” “internal feeling” and “correct investment decision” all increase in direct correlation with the amount of money put into investments (0.229, 0.095, 0.305, 0.171, 0.012, 0.009, 0.125 and 0.130, respectively). Table 3's final column displays the significance level for each predictor variable. For each predictor, it shows if its coefficient is statistically significant. If the p-value is small (usually less than 0.05), then the predictor has a substantial impact on the outcome. It is determined that the coefficients of market categories, the preferred share price ranges and the investment source represent negative predictor relationships. Other than the investment source, however, each predictor is statistically significant. This indicates that the aforementioned factors have a negative impact on capital investment in the stock market. Positive predictor relationships exist between investor stock trading behavior factors such as investor category, financial literacy level, investment duration, emotional tolerance level, risk consideration, investment monitoring activities, internal sentiment and correct investment decision (Similar findings found by Wood & Zaichkowsky, 2004; Lodhi, 2014; Seraj et al., 2022, Hilgert, Hogarth & Beverly, 2003; Markowitz, 1952; Riley & Chow, 1992; Tanvir et al., 2016; Akhter & Ahmed, 2013; Seo & Barrett, 2007, Al-Tamimi, 2006; Phan & Zhou, 2014). Statistically significant predictors exist for all variables other than risk consideration and investment monitoring activities. So the estimated equation is:

Y =0.265 −0.232X1+0.305X2+0.188X3−0.067X4+0.518X5−0.322X6+0.264X7+0.015X8+0.017X9+0.211X10+0.254X11 +E

Here,

• Y = The amount of capital investment in the share market.

• X1 = Market types

• X2 = Investors’ category

• X3 = Financial literacy level

• X4 = The investment source

• X5 = Investment duration

• X6 = Price ranges of shares investors prefer to invest in

• X7 = Emotional tolerance level

• X8 = Risk consideration

• X9 = Investment monitoring activities

• X10 = Internal feeling

• X11 = Correct investment decision

• E = Error term

The current study has presented the coefficients and rank order of various predictors based on squared semi-partial correlation in Table 4. Specifically, the semi-partial correlation for market types is found to be −0.036, with a squared semi-partial correlation of 0.0013097 and a rank order of 9. This implies that market types have a relatively weak impact on the dependent variable, as indicated by the low semi-partial correlation and rank order. On the other hand, the semi-partial correlation for investors' category is 0.191, with a squared semi-partial correlation of 0.0365784 and a rank order of 3, suggesting a moderate positive impact on the dependent variable. Similarly, financial literacy level has a semi-partial correlation of 0.096, with a squared semi-partial correlation of 0.0091420 and a rank order of 7, indicating a moderate positive impact, though less than some other predictors. Conversely, the investment source has a semi-partial correlation of −0.098, with a squared semi-partial correlation of 0.0097007 and a rank order of 6, suggesting a moderate negative impact. The strongest predictor is investment duration, with a semi-partial correlation of 0.244, a squared semi-partial correlation of 0.0596770 and the highest rank order of 1. The price ranges of shares also have a strong negative impact, with a semi-partial correlation of −0.197, a squared semi-partial correlation of 0.0389327 and a rank order of 2. Emotional tolerance level has a semi-partial correlation of 0.162, a squared semi-partial correlation of 0.0263396 and a rank order of 4, indicating a moderately strong predictor. Conversely, risk consideration and investment monitoring activities have the lowest rank order of importance, with semi-partial correlations of 0.025 and 0.010 and squared semi-partial correlations of 0.0006438 and 0.0000946, respectively. Finally, internal feeling has a semi-partial correlation of 0.092, a squared semi-partial correlation of 0.0084972 and a rank order of 8, indicating a moderate predictor, while accuracy level in decision-making has a semi-partial correlation of 0.122, a squared semi-partial correlation of 0.0149927 and a rank order of 5, suggesting moderately influential. In conclusion, the table provides insights into the relative importance of various predictors on the dependent variable, with predictors having higher squared semi-partial correlations and rank orders generally being more influential in explaining the variation in the dependent variable. Based on the information provided, it appears that the most crucial predictors are the investment duration, the preferred price ranges of shares, the category of investors, their emotional tolerance level, and their accuracy level in decision-making.

Conclusion

Through careful observation, it has been determined that investors' trading behaviors and their participation in the stock market hold immense importance and a profound connection. The data in Table 2 demonstrate a statistically significant fit with F (11, 465) = 48.405 and p = 0.00, indicating that the independent factors successfully predict the dependent variable. The coefficients of market categories, the preferred share price ranges and the investment source represent negative predictor relationships, with each predictor being statistically significant except for the investment source. This suggests that the aforementioned factors have a negative impact on capital investment in the stock market.

On the other hand, positive predictor relationships exist between investor stock trading behavior factors such as investor category, financial literacy level, investment duration, emotional tolerance level, risk consideration, investment monitoring activities, internal sentiment and correct investment decision. Statistically significant predictors exist for all variables other than risk consideration and investment monitoring activities. This indicates that these factors have a positive impact on capital investment in the stock market.

Moreover, it has been observed that the critical predictors of the amount of capital investment in the share market are the investment duration, the preferred price ranges of shares, the category of investors, their emotional tolerance level and their accuracy level in decision-making. These factors play a vital role in shaping investors' trading behaviors and determining their level of participation in the stock market. Thus, it is imperative for investors to meticulously consider these factors before making any investment decisions.

Practical implication

The conclusions have practical implications since they empower investors to modify their portfolios based on elements including share price ranges, investment horizons and emotional stability. To improve chances of success and reach financial objectives, they stress the significance of bettering financial understanding, active monitoring and risk analysis. Results can also be enhanced by distributing ownership over a number of market sectors and price points. The results highlight the value of patience and giving potential returns enough time.

Managerial implications of the study

The following are possible managerial ramifications of this study:

1. The findings of this study are vital for identifying the trading behaviors of investors. These results support the formulation of an effective investment strategy in a challenging and changing market environment.

2. This research will also help policymakers to create different profitable investable paths in the capital market.

3. Investment strategies and services that are tailored to particular investor categories may increase stock market involvement and participation.

4. By taking into account the determined predictors, advisors can provide suggestions that are in line with the unique characteristics and goals of investors.

5. With the help of these findings, legislators and regulators can create more effective regulations that promote ethical and knowledgeable investing. A better stock market ecosystem can be achieved by fostering favorable conditions and minimizing unfavorable effects.

6. The findings of this study will give other researchers more precise evidence from which to draw conclusions.

Table 1

Model summary

Model	R	R square	Adjusted R square	Std. Error of the estimate
1	0.731a	0.534	0.523	0.674

Note(s): a. Predictors: (constant), correct investment decision, market types, investors’ category, price ranges of shares investors prefer to invest in, risk consideration, investment monitoring activities, the source of investment, investment duration, emotional tolerance level, financial literacy level, internal feeling

Source(s): Author’s work using SPSS

Table 2

ANOVA^b

Model		Sum of squares	df	Mean square	F	Sig
1	Regression	241.925	11	21.993	48.405	0.000a
	Residual	211.274	465	0.454
	Total	453.199	476

Note(s): a. Predictors: (constant), Correct investment decision, market types, investors’ category, price ranges of shares investors prefer to invest in, risk consideration, investment monitoring activities, the investment source, investment duration, emotional tolerance level, financial literacy level, internal feeling

b. Dependent Variable: The amount of capital investment in the share market

Source(s): Author’s work using SPSS

Table 3

Coefficients^a

Model		Unstandardized coefficients		Standardized coefficients	T	Sig
		B	Std. Error	Beta
1	(Constant)	0.265	0.341		0.777	0.438
	Market types	−0.232	0.112	−0.069	−2.076	0.038
	Investors’ category	0.305	0.052	0.229	5.839	0.000
	Financial literacy level	0.188	0.074	0.095	2.547	0.011
	The investment source	−0.067	0.036	−0.064	−1.828	0.068
	Investment duration	0.518	0.062	0.305	8.371	0.000
	Price ranges of shares investors prefer to invest in	−0.322	0.053	−0.210	−6.101	0.000
	Emotional tolerance level	0.264	0.058	0.171	4.594	0.000
	Risk consideration	0.015	0.044	0.012	0.348	0.728
	Investment monitoring activities	0.017	0.061	0.009	0.281	0.779
	Internal feeling	0.211	0.064	0.125	3.297	0.001
	Correct investment decision	0.254	0.070	0.130	3.660	0.000

Note(s): a. Dependent Variable: The amount of capital investment in the share market

Source(s): Author’s work using SPSS

Table 4

Coefficients^a and Rank order of different predictors

	Semi-partial correlation (part)	Squared semi-partial	Rank order of importance
Market types	−0.036	0.0013097	9
Investors’ category	0.191	0.0365784	3
Financial literacy level	0.096	0.0091420	7
The investment source	−0.098	0.0097007	6
Investment duration	0.244	0.0596770	1
Price ranges of shares investors prefer to invest in	−0.197	0.0389327	2
Emotional tolerance level	0.162	0.0263396	4
Risk consideration	0.025	0.0006438	10
Investment monitoring activities	0.010	0.0000946	11
Internal feeling	0.092	0.0084972	8
Accuracy level in decision-making	0.122	0.0149927	5

Source(s): Author’s work using SPSS