Table 5 - uploaded by Noman Hossain Chowdhury
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Distribution of Stock Traders by " Gender and on average how long investors hold their stocks before selling (Average holding period) "
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When it comes to trading stocks, behavior is often an issue. Being aware of the trading behavior of investors is vital as many stockholders are subject to their behavioral influences. This study uses descriptive statistics to investigate the stock trading behavior of investors of Dhaka Stock Exchange, explore the relationship between demographic ch...
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... of the female traders have invested less than 10 Lac whereas majority male traders' investment size is above 10 Lac. Table 5 shows than majority of traders prefer to hold stocks for period less than six months, but the preference tends to be stronger in female traders. For holding period of more than six months, the percentage is higher for male traders. ...
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Citations
... We all know that the stock market is a capital market that assists a country in allocating scarce resources among various sectors in the most efficient manner (Arifuzzaman, Chowdhury, & Abdus, 2012). Companies can collect the funds they need to finance their operations in such markets, and investors can invest their money with the expectation of making a profit in the future by scarifying their current consumption and backing their investment by selling the holding securities in the secondary market at any time. ...
By illustrating the demographic composition of individual investors in the DSE of Bangladesh, examining the relationship between demographic factors and investment amount, exploring the relationship between demographic factors and investors' investment periods, highlighting the relationship between demographic factors and investors' emotional state, identifying the relationship between demographic factors and the impact of internal feeling on investors’ investment decision and establishing the relationship between demographic factors and investors’ correct investment decision-making, the current study seeks to fill the knowledge gap regarding the influence of demographic aspects on investors’ decision making process. Primary data are utilized to establish and explain concepts, while secondary data are also employed to support this empirical inquiry. Here, causal-comparative and descriptive study designs have both been applied. The study sample was chosen using the judgmental sampling technique. The characteristics of each investor are described by tabulation and percentage analysis. To depict the connection between demographic factors and individual investors' investment behaviour, various hypotheses are developed. For testing the hypotheses, ANOVA and the Chi-square test are utilized. In the DSE of Bangladesh, investors' decisions about investment quantity, investment time, emotional level, internal feeling, and appropriate investment decisions are strongly correlated with respondents' gender, age, education, occupation, and income.
... During the last decade or so, several studies have investigated a number of pertinent issues regarding the functioning of DSE, Bangladesh. Examples of such issues include nonnormality, volatility clustering, presence of autoregressive conditional heteroscedasticity (ARCH) and generalized autoregressive conditional heteroscedasticity (GARCH) effects in stock returns (Aziz & Uddin, 2014;Basher et al., 2007;Bose & Rahman, 2015;Siddikee & Begum, 2016), role of trading volume in reducing stock return volatility (Bose & Rahman, 2015), role of regulators and return volatility (Rahman & Golam Moazzem, 2011), impact of lock-in and circuit breaker measures in curbing return volatility (Basher et al., 2007), impact of circuit breaker measure in halting trade (Chowdhury & Masuduzzaman, 2010), effect of dividend policy on stock prices (Masum, 2014), day-of the week effects in stock returns (Bose & Rahman, 2015;Rahman, 2009), herding behavior among traders and seasonal influence (Ahsan & Sarkar, 2013;Bepari & Mollik, 2009), relationship between financial leverage and stock returns at firm level (Abdullah et al., 2015), stock market reaction to dividend announcement (Hossain et al., 2006;Rahman et al., 2012), market and informational inefficiency (Afzal & Hossain, 2011;Arefin & Rahman, 2011;Joarder et al., 2014;Mobarek et al., 2008), disparity in trading behavior of investors with respect to gender, age and education level (Arifuzzaman et al., 2012), prohibition of short-selling and market inefficiency (Sochi & Swidler, 2018), among others. ...
The primary objective of this paper is to empirically examine the nature and statistical significance of the news effect on conditional volatility of unpredictable components of stock returns. Daily stock return data of 12 local and multinational companies on Dhaka Stock Exchange Ltd., Bangladesh, for the period 1990 to 2011 were used in this study. The likelihood of asymmetric effects of news on conditional volatility was tested using a set of diagnostics under the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) framework. The results fail to reject the null hypothesis of symmetric effects, thereby suggesting that the conditional volatility of unpredictable components of stock returns is affected equally by positive and negative news. The robustness of the results was further checked by using three widely used asymmetric models, namely exponential GARCH (EGARCH), Glosten, Jagannathan & Runkle (GJR)-GARCH, and a partially non-parametric Autoregressive Conditional Heteroscedastic (PNP-ARCH) models. Yet again, the results do not provide any evidence of significant asymmetric effects in the volatility process. In addition, the descriptive results confirm the stylized facts of unpredictable return series such as non-normal distribution, time variant conditional volatility, and
persistence in return volatility. Collectively these findings, perhaps, indicate the adequacy of the GARCH (1,1) model in representing the data generating process. A number of regulatory and behavioral factors that are anticipated to be accountable for the absence of asymmetric news effects are underlined. Finally, some policy implications of the results and possible extensions of the present paper are also conveyed.
... During the last decade or so, several studies have investigated a number of pertinent issues regarding the functioning of DSE, Bangladesh. Examples of such issues include nonnormality, volatility clustering, presence of autoregressive conditional heteroscedasticity (ARCH) and generalized autoregressive conditional heteroscedasticity (GARCH) effects in stock returns (Aziz & Uddin, 2014;Basher et al., 2007;Bose & Rahman, 2015;Siddikee & Begum, 2016), role of trading volume in reducing stock return volatility (Bose & Rahman, 2015), role of regulators and return volatility (Rahman & Golam Moazzem, 2011), impact of lock-in and circuit breaker measures in curbing return volatility (Basher et al., 2007), impact of circuit breaker measure in halting trade (Chowdhury & Masuduzzaman, 2010), effect of dividend policy on stock prices (Masum, 2014), day-of the week effects in stock returns (Bose & Rahman, 2015;Rahman, 2009), herding behavior among traders and seasonal influence (Ahsan & Sarkar, 2013;Bepari & Mollik, 2009), relationship between financial leverage and stock returns at firm level (Abdullah et al., 2015), stock market reaction to dividend announcement (Hossain et al., 2006;Rahman et al., 2012), market and informational inefficiency (Afzal & Hossain, 2011;Arefin & Rahman, 2011;Joarder et al., 2014;Mobarek et al., 2008), disparity in trading behavior of investors with respect to gender, age and education level (Arifuzzaman et al., 2012), prohibition of short-selling and market inefficiency (Sochi & Swidler, 2018), among others. ...
The primary objective of this paper is to empirically examine the nature and statistical significance of the news effect on conditional volatility of unpredictable components of stock returns. Daily stock return data of 12 local and multinational companies on Dhaka Stock Exchange Ltd., Bangladesh, for the period 1990 to 2011 were used in this study. The likelihood of asymmetric effects of news on conditional volatility was tested using a set of diagnostics under the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) framework. The results fail to reject the null hypothesis of symmetric effects, thereby suggesting that the conditional volatility of unpredictable components of stock returns is affected equally by positive and negative news. The robustness of the results was further checked by using three widely used asymmetric models, namely exponential GARCH (EGARCH), Glosten, Jagannathan & Runkle (GJR)-GARCH, and a partially non-parametric Autoregressive Conditional Heteroscedastic (PNP-ARCH) models. Yet again, the results do not provide any evidence of significant asymmetric effects in the volatility process. In addition, the descriptive results confirm the stylized facts of unpredictable return series such as non-normal distribution, time variant conditional volatility, and persistence in return volatility. Collectively these findings, perhaps, indicate the adequacy of the GARCH (1,1) model in representing the data generating process. A number of regulatory and behavioral factors that are anticipated to be accountable for the absence of asymmetric news effects are underlined. Finally, some policy implications of the results and possible extensions of the present paper are also conveyed.
JEL codes: G10, G12, G14
