Issuu on Google+

Determinants of Volatility of Stock Returns in Dhaka Stock Exchange 1.0EXECUTIVE SUMMARY Volatility of stock returns has long been an issue of interest in financial literature. A wide variety of research has been conducted on stock returns volatility in developed and emerging markets since 1970s. Nature of volatility in different markets at different times are discovered, which are indeed of great interest for financial economists. Financial economists are also interested about the causes and variables behind the existence and nature as well as the anomalies relating to stock market volatility. Emerging Markets are characterized by high risk and return, highly predictable and high volatility compared to the developed markets. Volatility is one of the important aspects of financial market developments providing an important input for portfolio management, option pricing and market regulations. Stock market volatility differs dramatically across international markets. The stock market is an important ingredient of the financial system in Bangladesh. It is an important avenue for channeling funds to investors through mobilizing resources from individuals. In view of the rapidly increasing role of the stock market, volatility in stock prices can have significant implications on the performance of the financial sector as well as the entire economy. There exists important link between stock market uncertainty and public confidence in the financial market. The policy makers usually rely on the market estimate of volatility as the barometer of the vulnerability of the stock market. Stock return volatility represents the variability of day-to-day stock price changes over a period of time, which is taken as a measure of risk by the relevant agents. The aim of this study is to examine that the considering variables have any impact on volatility of stock returns in an emerging market of Bangladesh especially in the Dhaka Stock Exchange. The rest of the paper is organized as follows: Chapter-1, Introduction of the Report Chapter-2, An overview of Dhaka Stock Exchange Ltd. Chapter-3, describes an overview of Literature review Chapter-4, incorporates the Methodology that has been developed for conducting this study, Chapter-5, describes about the Empirical Results, and Chapter-6, Conclusion and Recommendation. 1.1. Background of the Paper: The stock market in Bangladesh is one of the emerging markets; it consists of two markets, Dhaka Stock Exchange and Chittagonj Stock Exchange. These markets need to be developed to operate efficiently and effectively in a competitive stock market environment. The current study will attempt to identify the most influencing factors of these stock markets. Portfolios managers and investors may find results in this research useful for determining the future behavior and performance of stock prices, for identifying investment approaches, pursuing available investment opportunities, and reducing the probability of high value losses in the market. Moreover, the stock market authority might find the results helpful in avoiding any unexpected catastrophe, controlling market strategies, improving the stock market industry, and assessing the degree to which the Stock market may need to be reformed. 1.2. Objective of the Paper: The objectives of the study are to test the following hypotheses:


 To investigate whether the companies with larger size of market lot are more stable than that of smaller market lot size.  To analyze if the companies with higher face value are more stable than that of lower face value.  To find out whether the companies with higher P/E ratio are more unstable than that of lower P/E ratio, and last but not least  To investigate the relationship between net assets value (NAV) of companies with the volatility of stock returns; measured by their standard deviations. 1.3. Scope of the Paper: One of the areas that volatility takes on greater importance is in the area of investment in the capital market. If a stock price has a history of relatively large price swings, then it becomes more likely that it can be more stable to invest in the market. If the long term average price of stocks is stable then investment in the market is more secured. To find the relationship of determinants that are taken into consideration in this study have any impact on volatility of stock returns in Dhaka Stock Exchange. 1.4. Statement of the Problem: Bangladesh stock market is an emerging market. The drastic volatile nature of Dhaka Stock Exchange (DSE) is the main problem. Sometimes market index increases continuously and as a result the prices of stock become very high and investors enjoy abnormal returns. On the other hand sometimes the market falls drastically and at that time investors incur losses. This abnormal volatile nature of stock prices in Dhaka Stock Exchange (DSE) is one of the greatest concern requiring deeper investigation. 1.5. Rationale of the Paper: This study will help the individuals as well as institutions, portfolio managers to take better decision regarding investment in the Capital Market of Bangladesh especially in Dhaka Stock Exchange. It will help to know the actual risk-return characteristics of the companies listed under Dhaka Stock Exchange (DSE). AN OVERVIEW OF DHAKA STOCK EXCHANGE LIMITED 2.1. An Overview of Dhaka Stock Exchange: The Dhaka Stock Exchange (DSE) is registered as a Public Limited Company and its activities are regulated by its Articles of Association rules & regulations and bye-laws along with the Securities and Exchange Ordinance, 1969, Companies Act 1994 and Securities & Exchange Commission Act, 1993. 2.1.1 Functions of DSE: The major functions are: - Listing of Companies (As per Listing Regulations). - Providing the screen based automated trading of listed Securities.


- Settlement of trading (As per Settlement of Transaction Regulations). - Gifting of share / granting approval to the transaction/transfer of share outside the trading system of the exchange (As per Listing Regulations 42). - Market Administration & Control. - Market Surveillance. - Publication of Monthly Review. - Monitoring the activities of listed companies. (As per Listing Regulations). - Investors grievance Cell (Disposal of complaint bye laws 1997). - Investors Protection Fund (As per investor protection fund Regulations 1999). - Announcement of Price sensitive or other information about listed companies through online. 2.1.2. Recent Developments in DSE: Total market capitalization of all listed securities in DSE increased substantially (by around 133 percent) in end of December, 2007 to Tk. 753.9 billion which, as a share of GDP, reached a new height in 2007 of nearly 16.0 percent as against 2.3 percent in 2003. In December 2007, a total of 350 securities were listed at DSE comprising 266 companies, 14 mutual funds, 8 debentures, 61 treasury bonds, and 1 corporate bond asmopposed to a total of 267 securities comprising of 248 companies, 11 mutual funds, and 8mdebentures in December 2003. Thus during the last four years only 43 new companies got listed in the DSE of which only three were listed by direct listing route, and the rest were listed through public offering. There are some big companies are enlisted in recent year like Grameen Phone Ltd., United Airways and some Mutual Funds and Spinning Mills in 2009 and 2010. 2.1.3. DSE Performance over the Years: Market indicators started to show new dynamism from November 2003 and reached new heights at the end of December 2003 as the daily average turnover jumped to Tk.136.9 million from the recorded low of Tk. 30.3 million in September 2003 (Chart 1). The DSE general index also started to rise from November 2003 which continued till the end of December 2004, as the DSEGen. index reached its peak at 1971.3. These developments owed significantly to the banking sector performance, as indicated by marketcapitalization and total turnover. Declaration of lucrative incentives in the FY04 national budget, floatation of shares of some profitable companies through Initial Public Offer (IPO) along with several important reform measures initiated by the Securities and Exchange Commission (SEC) helped to regain investor’s confidence back to the capital market. The FY04 national budget exempted the purchasers of listed equities of any queries as to the source of fund so long as purchased shares were not sold or transferred within two years of purchase. This was made effective for a limited period (FY04 to FY05). In addition, dividend-income tax was exempted and a new dividend distribution tax was imposed on the companies paying dividend.1 One important development in the capital market in 2004 was the initiation of electronic settlement through the Central Depository System (CDS) in January 2004. In order to prevent market manipulation by in-house officials of listed companies, SEC banned the purchasing or selling of shares of a company by its owners during an interim period (from the date of the financial year closure and the day of approval of accounts by the company’s board). De-listing of 13 companies in August 2004 by DSE due to their repeated failure in complying with the listing rules was also an important step toward bringing discipline in the stock exchange. The trading of Bangladesh Government Treasury Bonds (BGTBs) started in DSE from


January 2005. However, in order to temper the rising trend of stock index and control excess liquidity in the capital market, SEC temporarily suspended the credit facility extended by brokers to their clients. At the same time, SEC also increased the members’ trade margin requirements by reducing the free trading limit from Tk. 10 million to Tk. 5 million. As a result, secondary market activities became quiet during January-February 2005 and the daily average turnover declined to Tk. 245 million from Tk. 402 million in November-December 2004. However, the daily average turnover of DSE increased to Tk. 447 million in March 2005, which significantly surpassed the level of daily average transactions during the FY03-FY05 period.3 Considering the interest of the investors, SEC amended the margin rule in February 2004 by increasing the free limit to Tk. 10 million; and withdrew the order relating to the suspension of margin rule in April 2005. At the end December 2005, the stock index stood at 1,677.3. The market observed a downward trend during January-June 2006 and then turned positive from July 2006. In August 2006, the daily average turnover at DSE reached Tk. 561 million. Sign of vibrancy in DSE started from the beginning of 2007 and continued till the last trading day of the year. All the market barometers significantly rose during 2007 reflecting regained investors’ confidence after 1996 stock market bubble. The increasing trend of DSE-Gen index started in January 2007 and continued over the year except for a short period covering February-April 2007. The DSE-Gen index crossed the 3,000 mark for the first time and closed at 3,017.2 on the last trading day in 2007. In October 2007, the daily average turnover at DSE reached Tk. 2,297 million, but declined to Tk. 1,244 million in December 2007 mainly due to SEC intervention. In January 2008, DSE index again got the positive trend and till 2009 it is continuing with fluctuations. LITERATURE REVIEW There are a diverse number of literatures on the stock market in terms of returns and volatility. Some studies have examined the return characteristics of the market; where as some other studies have examined the volatility behavior of the stock market. There are factors may have impact on returns as well as on volatility. Having the view of volatility of returns this literature survey has been conducted. Elyasiani (1998), Janakiramanan (1998), Gilmore (2002), Hsiao (2003), Leong (2003), Nath (2003), Bessler (2003). Mukherjee (2005), Alexander (2008), etc. are some important studies that are carried out to spillover the stock market volatility. Bekaert and Harvey (1994) use the world portfolio as a benchmark for measuring risk. They reported that an unconditional single-factor CAPM is unable to characterize returns in emerging markets. This phenomenon means that emerging markets are less integrated with world market. However, they observe that the slope coefficient of the country return on the world portfolio return (Beta) has increased for most emerging markets in recent years. They interpreted this as signs of increased integration. Harvey (1994) tests multi-factor models and finds significant evidence that global risk factors are not powerful in explaining returns in emerging markets, especially compared with explaining returns in industrial countries. His evidence is consistent with the view that the emerging markets are segmented from developed markets. Buckberg (1995) uses a single-factor CAPM in which expected returns are allowed to change over time. She cannot reject that emerging equity markets were integrated in recent years (1984-1991), whereas she rejects it for many of the countries in the earlier period (1977-1984) and this finding suggests that the benefits of further diversifying into emerging markets have


been reduced. She thinks that increase in capital inflows from industrial economies that began in the late 1980s, is the main cause behind recent integration. Tandon (1994) shows that risk-adjusted cost of capital in emerging markets has moved more in line with that in industrial markets. This lower cost of capital associated with increased integration is also backed up by studies of individual security’s offerings. He shows that offering bonds on the international markets leads to a reduction in the required rate of return of the same firm’s equity. Aggarwal (2003) examine the integration of the three participating equity markets before and after the 1993 passage of NAFTA based on daily, weekly, and monthly data for seven years before and after the passage of NAFTA (1988-2001), unit root tests for the overall period 19882001 and the two sub-periods, 1988-1993 (pre-NAFTA) and 1994-2001 (post-NAFTA), indicate that stock prices are 54 International Research Journal of Finance and Economics - Issue 16 (2008) non-stationary but stock returns are generally stationary for all three markets for all three periods. However, daily, weekly, and monthly equity prices in the three NAFTA countries are co-integrated only for the post-NAFTA period. Ferson and Harvey (1994) examine multi-factor asset pricing models for eighteen national equity markets. They found that world market betas do not provide a good explanation of cross-sectional differences in average returns. Multiple beta models improve the explanatory power of equity returns. Harvey (1995a) found that standard global asset pricing models, which assume complete integration of capital markets, fail to explain the cross-section of average returns in emerging countries. An analysis of the predictability of the returns reveals that emerging market returns are more likely than developed countries to be influenced by local information. Harvey (1995b) examines the sensitivity of the emerging market returns to measures of global economic risk. He found that emerging markets have little or no sensitivity, which confirms the results of previous studies. He concludes that the world-market model fails to explain the emerging market returns. Bekaert (1995) develops a return-based measure of market integration for nineteen emerging equity markets. He then investigates the relation between that measure, other return characteristics, and broadly defined investment barriers. Two conclusions emerge from the analysis. First, global factors account for a small fraction of the variation in expected returns in most markets, and global predictability has declined over time. Second, emerging markets exhibit differing degrees of market integration with the U. S. market, and the differences are not necessarily associated with direct barriers to investment. Tesar and Warner (1995) find no evidence of relation between the volume of US transaction in foreign equity and local turnover rates or volatility of stock returns. This finding implies that the activity of US investors is not the source of excess volatility or high turnover on local (emerging) equity markets. Korajczyk (1996) measures the deviations of asset returns from an equilibrium model assuming market integration. Applying the measure to stock returns from 24 emerging markets indicate that market segmentation tends to be much larger for emerging markets than for developed markets, and the measure tends to decrease over time. Naeem (2000) examines the interlinkages among South Asian equity markets and equity markets of United States and United Kingdom for the period 1/94 to 12/99. Monthly stock market indices of Pakistan, India, Sri Lanka, Bangladesh, United States and United Kingdom has been investigated by using bivariate and multivariate cointegration analysis. Results reveal that


no long term relationship exists among these markets in full sample period. However, in prenuclear test periodcointegration is observed. It is worth mentioning that south Asian markets are not cointegrated with equity markets of the United States and United Kingdom. Mukherjee (2002) finds that Dhaka Stock Exchange (DSE) returns cannot be explained by developed and world markets' returns, implying the segmentation of it from the world. However, the integration between Bangladesh and developed countries increased gradually during the 1990s. Kasa (1992) examines the equity markets of the Japan, Germany Canada U.S. and U.K. to identify the common stochastic trends in monthly and quarterly time series for the period 1974 - 1990 by employing Johansen cointegration technique. Results provide evidence about the existence on one co-integrating vector that drives these equity markets. METHODOLOGY To investigate the issues of return and stock market volatility, this study uses daily all share price index of Dhaka Stock Exchange for the period of 2000-2009. This research is unique in the sense that it has considered very extensive and long time-series data set. Day to day price index data from January 2000 through December 2009 have been taken into account. In this study 92 DSE enlisted companies have been considered. For covering all the industries of DES, companies are selected randomly. In this study Net Asset Value (NAV) per share, Price Earnings (P/E) ratios, face values and market lot sizes are considered as independent variables. Considering these a regression analysis has been conducted for this study. Net Asset Value (NAV) of each company for 10 years has been taken into consideration and finally average NAV of each company is calculated for regression analysis. Price Earnings (P/E) Ratio of each company for 10 years has been considered and their averages are calculated for regression analysis. Both the face values as well as market lot size of the company are fixed. In case of market lot size it vary from company to company that’s why a dummy variable has been created. The companies for which market lot size fall in 1 to 10 are assumed as1, for 11 to 50 it is taken as 2, and above 50 is considered as 3 for regression analysis. Returns are calculated as follows:Rit , =

Pit − Pit − 1 Pit − 1

Where Rt is the return at time t, Pt and Pt- 1 are the closing price at time t and t-1, respectively, and i is each stock. The average day-to-day changes over a certain period (say, one year) is measured by adding together all changes for a given period (n) and calculated average (Rm) as follows: ∑ Rt Rm = n Risk: Risk is defined as the standard deviation around the expected return. In effect, we equated a security’s risk with the variability of its return. More dispersion or variability about a security’s expected return meant the security was riskier than one with less dispersion.


Standard Deviation (Volatility): Standard deviation is a statistical term that measures the amount of variability or dispersion around an average. So standard deviation works as a measure of volatility. Generally speaking, dispersion is the difference between the actual value and the average value. The larger this dispersion or variability, the higher is the standard deviation. The smaller this dispersion or variability, the lower is the standard deviation. Square root of mean squared deviation of the values from mean is called the standard deviation:

∑( x − x )

− 2

σ=

n

In this study a group data for 10 years has been taken in to consideration. For more than one group of data an established formula is used to estimate the volatility or the standard deviation that is stated below:

n1 ( d 21 + σ 21 ) + n2 ( d 2 2 + σ 2 2 ) + ........ + nk ( d 2 k + σ 2 k ) σ = n1 + n2 + ......... + nk In this study the functions is to be considered as

σ=

∫(Market lot size, Face value of the share, P/E Ratio, NAV Per share)

Specifically, the equation becomes:

σ = α + β1 x1 + β 2 x 2 + β3 x3 + β 4 d1 + β5 d 2 + e

Where,

σ = Volatility (Mean Standard deviation) α , βi =Intercepts 1,1τ market lot size is 1 - 10.  d1 =    0, Otherwise 


1,1τ market lot size is 11 - 50.  d2 =   0, Otherwise   x1 = face value x2 = Average P/E x3 = Average NAV

e = Error term Therefore, the hypothesis to be tested is H 0 : β1 = β 2 = β 3 = β 4 = β 5 = 0

EMPIRICAL RESULTS OF THE STUDY 5.1. Descriptive Analysis: Empirical studies demonstrate that the volatility of stock prices change over time. This suggests a need for financial instruments that can be used to manage this type of risk. In this paper, we have valued Dhaka Stock Exchange (DSE) on volatility in the context of finding out the determinants that are contributing the volatility of stock returns. Face Value 1 10 100 Total

Frequency 1 17 74 92

Table-1: Face Value of the samples Source: www.dsebd.org This section states the face values and their respective frequencies. Among the sample companies only 1 company has face value Tk. 1. There are 17 companies with face value Tk. 10 and the rest of the companies i.e., 74 companies have face value Tk. 100 total of 92 sample companies.


50

Company

40 30

100

20

10 1

10 0 1-10

11-50

51 or more

Figure-1: Market Lot Sizes For market lot size dummy variable has been created and this figure is showing that how many companies are falling between 1-10, 11-50, and 51 or more. X- axis is showing the market lot size class and Y-axis is representing the number of companies with face values with the respective numbers. This study is giving result that there is no impact of variation of stock prices maintaining that if the market lot size is high, its price not necessarily be more stable. Market lot size 1-10 11-50 51 or more

Frequency 38 44 10

Percent 41.30435 47.82609 10.86957


Total

92

100%

Table-2: Frequency table for market lot size For conducting the study total 92 companies have been taken in to account. Market lot size 1-10 class has 38 companies that indicates approximately 41% companies. Market lot size 11-50 is containing a total of 44 companies that indicates near about 48% of the total sample. The rest of the companies are in market lot size of 51 or more which is near about 11%. Lot size class 1-10 11-50 51 or more Grand Total

Face Value 1

10

1 1

8 9 17

100 38 36

Grand Total 38 44 10 92

74

Table- 3: Cross tabulation between market lot size with face value. This table is stating the number of companies with its face value and respective market lot size. The result is showing that one company has face value of Tk. 1 and its market lot size falls in 51 or more class. There are 17 companies with face value of Tk. 10 and among them 8 companies are falling in market lot size 11-50, and rest of the companies i.e., 9 companies are in 51 or more market lot size class. The table is showing that total 74 companies having the face value of Tk. 100. There are 38 companies with face value of Tk. 100 are falling in the 1-10 market lot size class and 36 companies are in 11-50 market lot size class. There are no companies with the face value of Tk. 100 in the market lot size class of 51 or more. There has been no significant result found about the face value of a particular stock that implies about volatility of stock returns. Average P/E Average NAV

Average P/E 1 -0.16580687

Average NAV 1

Table-4: Correlation between NAV and P/E ratio This table is showing the correlation between the average Price Earnings (P/E) ratios and average Net Asset Value (NAV). The result is showing the negative correlation. This not surprising as it is expected that companies with higher NAV should have lower P/E ratio and vice versa.


SUMMARY OUTPUT Regression Statistics Multiple R

0.252417085

R Square

0.063714385

Adjusted R Square

0.009172518

Standard Error

131.3532032

Observations

92

5.2. Regression Analysis: Table- 6: Regression Statistics Regression analysis shows that there is no true relationship has been found among the variables. The regression of standard deviation with the variables of NAV, P/E ratios, Face values and Market lot size are not significant. In DSE investors are making profit or suffering loss with just rumor and some assumptions. Manipulation is highly affecting the DSE. No analytical result can predict the risk-return relationship of this emerging market using the above four variables. The above analysis also indicates that the stock market volatility changes significantly over time. The volatility of stock return is determined by the fluctuations in stock index. Fluctuation in the stock index also depends on the demand for and supply of securities traded in the stock exchange. Sometimes the stock return volatility is driven by trading volume following new information and by the process that incorporates new information into market prices. At the aggregate level, stock return volatility rises sharply during stock price declines following bad news than in periods of stock price increase following good news. While relating changes in stock market volatility with a number of economic factors, such as financial leverage, corporate bond yields, corporate earnings and


dividend yields, stock trading activity, volatility of interest rates, bond prices, and other macroeconomic variables are other factors that need to be considered while investigating on the topic. The insignificant regression analysis indicates that the return series in the stock market of Bangladesh is not predictable, which accepts the null hypothesis of efficient market hypothesis (EMH). The significant regression analysis implies that irrelevant market information generally reflected in the stock price change in Bangladesh. This may be the cause of frictions in the securities market trading. This results also indicate that the participants may have limited access to the market information regarding the firms performance either the firms listed in the Dhaka Stock Exchange fail to call the annual general meeting in timely manner or availability of financial statements information/release of audited financial statements are delayed. In addition, market inefficiency may be the result of non-synchronous effects, which implies that information in the stock market is processed with a lag. Cambell et al. (1997) noted that non-synchronous trading would imply negative autocorrelation in portfolio returns but this study presented a positive autocorrelation, which implies non-enforcement of regulations and/or weak supervision by the Securities and Exchange Commission (SEC) in the stock market of Bangladesh. CONCLUSION AND RECOMMENDATION Conclusions: There is no significant result found regarding the volatility of stock returns in Dhaka Stock Exchange with relationship to NAV, P/E ratio, market lot size of face value. This is also implies that the change of face values and market lot size by some companies does not have impact on the market volatility . This market is not followed any particular method by which the stock return volatility can be characterized. The followings are the probable causes of day -to- day dispersion of stock price in Dhaka Stock Exchange: Market sentiment: The price of the stock of a company is affected most of the time by the general market direction during a session. In a bull market, the stock price of most companies will rise and in a bear market the stock price of most companies will fall. The performance of the industry: The performance of the sector or industry that the company is in also plays in part in determining the stock price of the company. Most of the times, the stock price of the companies in the same industry will move in tandem with each other. This is because market conditions will generally affects the companies in the same industry the same way. Of course, there are exceptions to this that has been found in DSE. Sometimes, the stock price of a company will benefit from a piece of bad news in its competitor if the companies are competing for the same target market. The earning results and earning guidance:


The main objective of a company is to make profit. Therefore, investors and traders always assess a company based on its Earning per Share (bottom line) and Revenue (top line) and its future earning potential. Take-over or merger: In general, a company being taken-over is anticipated to get a stock price boost and the company taking over another company shall experience a drop in its share price. This is assuming that the company is being taken over at a premium, meaning it is being bought over at a higher price than its last traded stock price. Depends on the agreed term, a company can be bought over by cash or stock (of the acquirer) or a combination of the two. New product introduction to markets or introduction of an existing product to new markets: The introduction of new product to market is seen as a revenue enhancer for a company. This also applies to an existing product that breaks into new markets. Sometimes, the prospect of a new product introduction suffices to improve the stock price of a company. New major contracts or major Government Orders: A company that is able to obtain new major contracts or major government order is expected to see a bull run in its stock price. Those companies that fail in the contract bidding normally experience the fate of sell-off in its stocks. Share buy-back: The act of share buy-back by a company will reduce the number of share available in the open market. Due to the law of supply and demand, a reduction in share available for trading in this case will cause a drop in supply, this will normally help increase the share price. Also, the continuing buying back of share of a company will also acts as a support for the share price that helps to maintain or increase the share price. The investors may also see the share buy-back by company as a confidence booster for them in the company itself. Therefore, share buy-back is quite often used as a tool to deliver value to the investors. Dividends Announcement: Before or after the announcement of dividend the stock price may increase by an amount close to the dividend per share value. However, the stock price may drop on the ex-dividend date by the dividend per share amount. This is because anyone buying a stock on or after the ex-dividend date is not entitled to the corresponding dividend payment. Stock splits: Stock splits have an impact to the stock price. However, it is generally observed that the stock price increases (after taking into account the increase in the number of share) after a stock split.


Some attributed to the better affordability of the stock after stock split, some attributed this to the perception of cheap stock due to the lower stock price after the stock split. Insider Trading: Insiders include CEO, Chairman, board of directors etc, who has first hand information about the operations and the financial status of a company. Therefore, the buying or selling of stocks by these insiders may herald some good or bad news about the company. This is being watched closely by savvy stock investors/traders. Addition/Removal to/from Stock Index: Stock Index Funds are those funds that invest in those company stocks that are included in a particular stock index. Therefore, an inclusion of a company stock to a stock index will generate buying interest in the stock for these stock index fund managers. The stock index fund managers will dispose of the stock that has been removed from the stock index. Others: These include news about new technology, patent approval, war, natural disaster, product recalls and lawsuits that shall have positive and negative impact to the relevant company stocks. Recommendation: Volatility in stock prices is a common phenomenon in the stock market. Individual stock price undergoes ups and downs which is a regular feature of an efficient stock market. In the absence of price volatility, potential investors lose interest to participate in the stock market. However, careful monitoring of volatility by the concerned authority is needed in DSE which is yet not to achieve maturity especially when high volatility exists in the market. Dhaka Stock Exchange is an emerging market; there should be effective intervention when the market experiences excess volatility. During unpredictable movements of individual stock prices, it would be useful for the authority to identify the factors behind such price movements and quickly disseminate the information to interested stakeholders. In addition, the authority may take measures to make available all relevant information relating to real worth of the companies experiencing excess volatility in stock prices, especially to the investors. It is also important to ensure adequate supply of stocks through active participation of the government in the capital market particularly to dampen the excess demand. The regulatory authority of DSE should take necessary steps for sustainable development of the market. If so investors confidence level will high and volatility of stock returns depends on the fundamentals of the company. For further study on the subject matter other technical, fundamental and other factors may be used to predict the stock market volatility in Dhaka Stock Exchange. This task is left to the further research on the topic. References: Aggarwal, R., Inclan, C., and Leal, R., "Volatility in Emerging Stock Markets", Journal of Financial and Quantitative Analysis,Vol. 34, 1999, 33-55.


Aggarwal, R. and P. Rivoli, “Fads in the Initial Public Offering Market?” Financial Management 19, 45–57,(1990). Batra, A., "Stock Return Volatility Persistence in India: 1973-2003", Working paper, ICRIER, New Delhi, India, 2004. Baillie, R. and Degennaro, R., "Stock Return and Volatility", Journal of Financial and Quantitative Analysis, Vol. 25, 1990, 203-214. Barua, S. and M. H. Rahman (2006), “Monetary Policy and Capital Market Development in Bangladesh”, Bangladesh Bank Quarterly, Vol. IV, No. 2. Bekaert, G., Harvey, C. and Lundblad, C. (2005) Did financial liberalization spur economicgrowth? Journal of Financial Economics 77, 3–55. Bessler, D. A., and J. Yang (2003), The structure of interdependence in international stock markets, Journal of International Money and Finance 22, 261–287. Bollerslev, T., "Generalized Autoregressive Conditional Heteroskedasticity", Journal of Econometrics, Vol. 72, 1986, 307-327. Bollerslev, T., Chou, R. Y., and Kroner, K. F., "ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence", Journal of Econometrics, Vol. 52, 1992, 5-59. Brandt, M. W. and Kang, Q., "On the Relationship between the Conditional Mean and Volatility of Stock Returns: A latent VAR Approach", Working Paper, University of Pennsylvania, 2003. Chowdhury, A. R. (1994), “Statistical Properties of Daily Return from the Dhaka Stock Exchange”, Bangladesh Development Studies, Vol. XXII, No. 4. Claessens, S., Dasgupta, S., and Glen, J., "Stock Price Behaviour in Emerging Stock Market," in Stijin Claessens and Sudarshan Gooptu, (eds.), Portfolio Investment in Developing Countries, World Bank Discussions Paper, 228, Washington, D.C., 1993. Campbell, J. Y., Lo, A. W., and Mackinlay, A. C., The Econometrics of Financial Markets, Princeton, 1997. Chou, R. Y., "Volatility Persistence and Stock Valuations: Some Empirical Evidence using GARCH", Journal of Applied Econometrics, Vol. 3, 1988, 279-294 Choudhury, T., "Stock Markets Volatility and the crash of 1987: Evidence from Six Emerging. Markets", Journal of International Money and Finance, Vol. 1.5, 969-981. Cohen K., Ness, W., Okuda, H., Schwartz, R., and Whitcomb, D., "The Determinants of Common Stock Returns Volatility: An international Comparison," Journal of Finance, Vol. 31, 1976, 733-740. Edwards, F. (1998), “Does Futures Trading Increase Stock Market Volatility?”, Financial Analysts Journal, January/February 1998. Engle, R. F., "Autoregressive Conditional Heteroskedasticity with Estimates of UK Inflation", Econometrics, Vol. 50, 1982, 987-1008. Engle, R. F., and Bollerslev, T., "Modeling the Persistence of Conditional Variances", Econometric Reviews, Vol. 5, 1986, 81-87. Ferson, W., and Harvey, C. (1993) The risk and predictability of international equity returns, Review of Financial Studies 6, 527–566.


French, K.R, Schwert, W. G., and Stambugh, R. F., "Expected Stock Return and Volatility", Journal of Financial Economics, Vol. 19, 1987, 3-29. Habib, M. A. and Ljungqvist, A. P. (2001) Underpricing and entrepreneurial wealth losses in IPOs, Review of Financial Studies 14, 433–458. Harvey (eds.), Blackwell Handbook of Judgment and Decision Making. Blackwell, Malden, Mass, pp. 527–546. Glosten, L. R., Jagannathan, R., and Runkle, D. E., "On the Relation between the Expected Value and Volatility of the Nominal Excess Returns on Stocks", The Journal of Finance, Vol. 48, 1993, 1779-1801. Hasan, M. K., Islam, A. M., and Basher, S. A., "Market Efficiency, Time Varying Volatility and Equity Returns in Bangladesh Stock market", 2000, Lee, S., and Ohk, K., "Time-varying Volatilities and Stock Market Returns: International Evidence", Pacific-Basin Capital Markets Research, 1991. Haque, M., and Hassan, M. K., "Stability, Predictability and Volatility of Latin American Emerging Markets", University of Orleans, Working Paper, 2000. Harvey, C. R., "Portfolio Enhancement using Emerging Markets and Conditioning Information", in Stijn Classens and Shan Gooptu, Eds., Portfolio Investment in Developing Countries (Washington: The World Bank Discussion Series, 1993, 110-144. Harvey, C. R., "The Cross-section of Volatility and Auto-correlation in Emerging Markets",Finanzmarkt und portfolio Management, Vol. 9, 1995a, 12-34. Harvey, C. R., "Predictable Risk and Return in Emerging Markets", The Review of Financial Studies, Vol. 8, 1995b, 773-816. Harvey, C.R., "The Specification pf Conditional Expectations", Journal of Empirical Finance, Vol. 8(5), 2001, 573-637. Imam, A. O. and A.S.M. M. Amin (2003), “Volatility in the Stock Return: Evidence from Dhaka Stock Exchange”, Journal of Institute of Bankers Bangladesh, Vol. 51, No. 1. Jain, R. K. (2001), Putting Volatility to Work, ACTIVE TRADERS, April 2001. Kanniainen, J. (2007), “On Dividend Expectations and Stock Return Volatility”, International Research Journal of Finance and Economics, Issue 12. Karolyi, G. A. (2001), Why Stock Return Volatility Really Matters, Preliminary and incomplete version, February 2001. Khalily, M. A. Baqui. et. al. (2003), “Capital Market Development in Bangladesh: Need For More Macro-Economic and Financial Policy Interventions”, Journal of Institute of Bankers Bangladesh, Vol. 50, No. 2. Li, K., "Long-memory versus Option-Implied Volatility Prediction", Journal of Derivatives, Vol. 9(3), 2002, 9-25. Mollah, A. S., Mobarek, A., "Does Stock Market Volatility Differ Across Counties? Evidence from Fifty International Markets", Global Finance Conference, Melbourne , Australia, 2007. Schwert, G. W. and R. Stambaugh (1987), “Expected Stock Returns and Volatility”, Journal of Financial Economics, No. 19. Shahiduzzaman, M. and M. S. Naser (2006), “Volatility in the Overnight Money-Market Rate in Bangladesh: Recent Experiences”, Bangladesh Bank Quarterly, Vol. IV, No. 2.


Determinants of Volatility of Stock Returns in Dhaka Stock Exchange