CHAPTER 1

INTRODUCTION


1.1 Introduction

Investors have always observed the trading volume carefully which presumably conveys valuable information about future price movements (Llorente, Michaely, Saar, and Wang, 2002). The basic logic to use the trading volume in studying stock prices is that the trading activity has explanatory power in addition to past returns, and price changes accompanied by high volume tend to be reversed (Ali, 1997). Hence, trading volume has been used as a very important element of technical analysis. Often, investors keep track of this important technical indicator by following the market and stock volume data that are frequently published in the financial press in order to obtain some additional indication of a potential move. If the market is not fully efficient, there are possibilities of investors making abnormal profits by observing the volume traded to find and buy good value stocks at low prices and then wait for their prices to go up. Thus, concept of market efficiency is essential to be discussed in this study.

The efficient-market[1] issue has been hotly debated. In an efficient market, information is impounded into security prices with such speed that there are no opportunities for investors to profit from publicly available information. Types of information being immediately reflected in security prices and the speed in which information is reflected determine how efficient the market is. Though there is evidence in support of this hypothesis, there is also evidence that financial markets are not completely efficient. Lo and MacKinlay (1988, 1999) had indicated that stock prices did not completely follow the random walk. Hence, it is possible that the stock market is not efficient when stock prices do not reflect all available information regarding the value of the company. George Soros who was the graduate of the London School of Economics critiqued and challenged the facts of the efficient markets hypothesis and rational expectations theory. Soros stated that "I have to confess that I am not familiar with the prevailing theories about efficient and rational expectations. I consider them irrelevant and I never bothered to study them because I seemed to get along quite well without them" (Soros, 1998, p.41).

In addition to observing the trading volume, emotions and other subjective factors are believed to play a role in investment decisions. Hence, to truly succeed, market participants need to understand and deepen the understanding of individual and collective behaviour of market players who are also the ordinary human beings. Cassidy (2001, p.22) described the stock market as follows:

"Markets are the interactions of human beings making decisions. Those who see humans as automatons ruled entirely by pure logic and fact, I would propose, run a high risk of reaching imperfect conclusions because they have proceeded from an incomplete, if not heavily mistaken, starting point. Inside our heads are not just facts and logic machines but also drives and emotions. Our economic and financial behaviors therefore must be studied with that context included rather than excluded."

The principal questions are what do people do and how does investor behaviour influence the structure and dynamics of stock prices? Blume, Easley and O'Hara (1994) and Suominen (2001) investigated the information content of trading volume on financial markets. Both studies suggested that stock prices are noisy and cannot convey all available information to market participants. Hence, trading volume could be used as an informative statistic.

Llorente et al. (2002) noted that "what we can learn from trading volume depends on why investors trade and how trades with different motives relate to stock prices" (p.1). George Soros was ranked as an enormously successful speculator by a former Federal Reserve chairman Paul Volcker (2003, p.xii) in the foreword of Soros' book "The Alchemy of Finance" which stated that "Soros was wise enough to largely withdraw when still way ahead of the game. The bulk of his enormous winnings is now devoted to encouraging transitional and emerging nations to become 'open societies,' open not only in the sense of freedom of commerce but more important tolerant of new ideas and different modes of thinking and behavior". To this extent, the New Statesman of Mindfully when queried about the turmoil Soros's speculation caused to Far Eastern economies in 1997 noted that Soros himself commented that he needed not be responsible on the consequences of his actions as an investor (Mindfully, 2007). Thus, this implies that investors who trade in the stock market with different motives related to stock prices would affect market condition.

Speculation occurs frequently, and many stock price trends are influenced by the investors' expectations about firms, industries, and government action or inaction. Phoon (1993) indicated that the Malaysian stock market was moved up mainly because of speculation or rumours. This was due to the investors' fanatical and stock chasing behaviour in the market. From the previous experience of financial crisis of 1997/1998, speculation activities had been identified as one of the major factors that had contributed towards the slowdown of the economy (Chris, Wendy, Russell, and Marika, 2001). The Kuala Lumpur Stock Exchange Composite Index (KLSE CI)[2] had dropped 79.34% from a peak of 1271.57 on 25th February 1997 to 262.70 point on 1st September 1998, the lowest point in the Malaysian stock market history, after continuous dumping and selling of the Malaysian stocks by both foreign and local investors (Yahoo Finance, 2006a).

Therefore, it is very interesting to examine trading with different motives in incomplete financial markets with sequential trading, for instance, Malaysian stock market. So, how does the Malaysian stock market informationally efficient? What do investors do in the market? What are their motives to trade? How does the investor behaviour influence the structure and dynamics of stock prices and trading volume? To what extent are the dynamics of stock prices and trading volume influenced by information asymmetry? This study attempts to provide answers and evidence to these questions.


1.2 Research Problem

The research problem being examined in this study can be expressed in the following research questions: Does trading volume cause stock returns in the Malaysian stock market? And, to what extent does information asymmetry affect the trading-generated returns?

If volume could be used as an informative statistic to investors, the hypothesis that market is fully efficient is questionable. If the market is perfectly efficient, buying and selling securities by investors in an effort to maximise profits would be a game of chance rather than skills. Then, why it fails to explain the events of crashes that occur, for example, in as much as 87% loss of Dow Jones Industrial Average (DJIA) market value from the high point of 452 to the bottom 58 in Wall Street crash of 1929 (MarketWatch, 2008).

According to Gitman and Joehnk (2008, p.393), volume is defined as "a function of the supply of and demand for stock". The volume traded is a clear reflection of the amount of investor interest and this indicates underlying market strengths and weaknesses. The market is considered strong when it is rising on high volume or falling on low volume. In contrast, it is considered weak when rising on low volume or falling on high volume (Gitman and Joehnk, 2008). Gitman (2003, p.214) defined return as "the total gain or loss experienced on an investment over a given period of time".

Theoretically, low volume implies high liquidity risk and vice-versa. Market makers have greater opportunity for profit as the volume turnover increases (Floros and Vougas, 2007). Institutional investors are neither willing to invest in the relatively less liquid and respectively low capitalised market nor willing to keep their portfolio shares of these companies on a low basis. Thus, the issue of efficiency is particularly important for emerging markets since it could indicate an increase in liquidity, a removal of institutional restrictions and an increase in the quality of information revealed in these markets.

According to Kaldor (1939, p.1), speculation is "the purchase (or sale) of goods with a view to resale (or repurchase) at a later date, where the motive behind such action is the expectation of a change in the relevant prices relatively to the ruling price and not again accruing through their use, or any kind of transformation affected in them, or their transfer between markets". This implies that information asymmetry does affect the trading volume and returns of a stock market. Information asymmetry occurs when one party in a transaction has more or better information than the other party (Akerlof, 1970). It is conditioned in which at least some relevant information is known to few but not all parties involved. Since some investors do not have the same type of access to information they need for making investment decisions, information asymmetry causes markets to be inefficient.


1.3 Significance of Study

Putting the research problems of this study together, this study is conducted in two stages. The study starts with an investigation on the contemporaneous and causality relations of trading volume and returns before proceeding to the impact of information asymmetry on that dynamic relation in stage two (2).

The first stage of the study involves an examination of efficiency of market index of Bursa Malaysia. It investigates whether the Malaysian stock market as a whole is an efficient market in disseminating market information to market participants, which is reflected in first objective of this study (refer to Section 1.4). At this stage, the study aims to examine the contemporaneous relation between aggregate trading volume and Kuala Lumpur Composite Index (KLCI) returns through ordinary least squares (OLS) and generalised autoregressive conditional heteroskedasticity (GARCH) tests corrected with Newey-West heteroskedasticity and autocorrelation consistent covariances (Newey-West HAC Consistent Covariances). Then, an investigation of linear causality of aggregate trading volume and KLCI returns series in the Malaysian stock market through bivariate Granger test is undertaken.

The second stage of the study focuses on the investigation of the investors' motives to trade individual stocks on the Malaysian stock market by using time series and cross-sectional analyses. The findings of this would indicate if Malaysian stock market is mainly dominated by driven speculative trading or by the expectation of real activity in the economy, which are to meet the second and third objectives of this study (refer to Section 1.4).

A total of nineteen null hypotheses are tested in this study. The null hypotheses 1 to 13 are tested in the first part of the study to evaluate the issue of efficiency of the Malaysian stock market in terms of contemporaneous and causality relations. The null hypotheses 14 to 19 on the other hand, are used in the second part of the study to investigate the investors' motives to trade on the Malaysian stock market. Then, the findings of both parts will be integrated and combined to develop an integrated trade-generated return and information asymmetry framework. This framework would be considered as an active asset management approach if special insights could be used to generate extra returns by selecting particular stocks in the portfolio. This framework incorporates the insights of what, when, and why to buy or sell shares to investors in search for greater profits. Meanwhile, firm size, time interval, linearity and, firm-specific factors are controlled in this study.

It is worth noting that this study contributes to current finance literature by filling the gap among the efficient market hypothesis (Fama, 1965), mixture of distributions hypothesis (Clark, 1973) and the sequential information arrival hypothesis (Copeland, 1976) by combining the implications of OLS, GARCH, and bivariate Granger causality test on trading volume, KLCI, and stock returns. This study extends the study of Shamsher and Annuar (1993; 1995) by examining the effects of hedging and speculative motives to trade-generated returns, both that of the individual stocks and the stock market as a whole. This study is also useful in providing investors a picture of a decision-making process in the Malaysian stock market which departs in systematic way from the classical and rational economic theory.

The ultimate contribution of this study is the comprehensive integration and incorporation of both informative statistics and level of information asymmetry in making investment decisions in the Malaysian stock market. Ariff (1996) documented that emerging markets were generally inefficient securities markets. For instance, Malaysian stock market is an inefficient market in disseminating market information to all market participants. It has relatively smaller trading volume and less well-informed investors with access to inaccurate information as compared to developed markets. Hence, Malaysian stock market appears to be less liquid and highly volatile. The research of linkage of trading volume and stock return in terms of contemporaneous and causality has been carried out almost exclusively on the well-developed financial markets, usually the United State market. There is also very little attempt made on examining the dynamic relationship between returns and trading volume in the Malaysian Stock Market (Shamsher and Annuar, 1993; 1995). No evidence that anticipated events are fully reflected in stock prices in the Malaysian stock market is found (Fatimah and Rahana, 2003). With the rapid development of the Malaysian stock market and the increasing availability of reliable data, there is a growing concern in this emerging market and in view of all these, research of this nature is timely and justified.


1.4 Research Objectives

The primary objective of this research is to incorporate volume-return relation in investment decisions in the Malaysian stock market. This main objective is complemented via the secondary objectives: first, to examine the information contained in trading volume at aggregate. Second, to identify trade-generated returns of three size groups of individual stocks, namely large, medium, and small firms, with particular attention to the relative amount of hedging trade versus speculative trade in different length of time period. Third, to investigate the relative impact of linearity and firm-specific speculative trade versus hedging trade on stock prices in three size groups of individual stocks using different length of time interval.


1.5 Why Study an Emerging Market?

The Malaysian stock market is an emerging stock market which is differentiated from developed markets with respect to their heterogeneous nature and inherent dynamics. Since the 1980s, investments in emerging markets have become increasingly important especially in international portfolio management. In 2007, the share of the emerging markets in the global market capitalisation was 14.8%. The number of listed companies in emerging markets increased to over 20,106 companies in 2007 and with a share of 40.04%% of all globally listed companies. The portfolio equity flows had increased from USD$ 13,794 million in 1995 up to USD$ 104,849 million in 2006 (World Development Indicators, 2008). There is an evidence of increasing mobility of resources around the world.

Investors are not only investing in their domestic markets but also in global markets. This can be seen in the Malaysian stock market which has USD$ 2,473 foreign direct investment and USD$ 1340 million portfolio investment flows in year 2003 compared to none in year 1990 (Bank Negara Malaysia, 2005). Thus, it is worth noting that the findings are important to provide implications for portfolio managers and investors when making their investment decisions in these emerging markets. Hence, the importance of studying the Malaysian stock market which is an emerging market that involves with foreign investment is justified.

The term 'emerging market' was originally created by International Finance Corporation (IFC), a subsidiary of the World Bank. This term is used to describe equity markets which are in low-to-middle income economies among the developing countries, with stock markets in which foreigners could buy securities. By the end of 2003, all economies with a Gross National Income (GNI) per capita of USD$9,385 or less were classified as developing countries.[3] At this point, from all countries worldwide with a population of more than 30,000 people, 154 nations belonged to developing countries and 54 to developed countries.[4]

Bekaert, Harvey, and Viskanta (1998) stated that emerging markets had high average returns while Aggarwal, Inclan, and Leal (1999) noted that emerging markets had high level of volatility. An emerging market is the one in which the economy has enormous growth potential and generates typically higher rates of return than developed markets. This is in contrast to the developed markets, which are relatively old and stable. These emerging markets tend to be more erratic, offering by turns great increases and great decreases in the returns achieved. This is especially preferred by the investors who are willing to brave the potentially high risks as the emerging markets have the possibility of achieving higher returns than the developed markets.

Ariff, Shamsher and Annuar (1998) pointed out that the nature and behaviour of emerging markets and developed markets were significantly different. They highlighted that the returns generated on average by emerging markets was about 20 percent per annum with a standard deviation of about 40 percent over the last decade compared to an average return of about 15 percent with a standard deviation below 20 percent in the developed markets. It has been shown that they are not integrated to the developed markets of the world as evidenced by very low correlation with the rest of the World and among them. Ariff et al. (1998) also indicated that of the 276 correlation coefficients observed in the recent 7-year period, 89 were negative in emerging markets. Thus, the integration of emerging markets into stock portfolios could provide international diversification benefits and stabilise the return rates over time. This eventually leads to a reduction in the existing portfolio risk as they are characterised by low correlation coefficients with well-developed stock markets.


1.6 An Overview of Bursa Malaysia

It should be pointed out that the scope of this research is limited to the public listed companies in Bursa Malaysia, particularly those on the main and second boards of Bursa Malaysia. Essentially, these main and second boards will differentiate the capital standings of the listed companies, which are evident from the listing requirement discussed in section 1.6.1.

Some background information on the Bursa Malaysia is provided here for clear understanding before conducting the study. Information book of Kuala Lumpur Stock Exchange (KLSE) stated that the securities industry in Malaysia has effectively begun in the late 19th century as an extension of the presence of British companies in the rubber and tin industries (KLSE, 1998).

Singapore Stockbrokers' Association was the first formal organisation in the securities business in Malaysia. It was formed in 1930 and then it was re-registered as Malayan Stockbrokers' Association in 1937. However, there was still no public trading of shares. Malayan Stock Exchange was formed and public trading of shares had only begun formally on 9th May 1960 and the name of Malayan Stock Exchange was changed to Stock Exchange of Malaysia in 1964. Then, a year later, with the secession of Singapore from Malaysia, the common stock exchange still continued to function only to be named as the Stock Exchange of Malaysia and Singapore (SEMS). In 1973, with the termination of currency interchangeability between Malaysia and Singapore, the SEMS was separated into The Kuala Lumpur Stock Exchange Bhd (KLSEB) and The Stock Exchange of Singapore (SES). Malaysian companies continued to be listed on SES and vice-versa (Bursa Malaysia, 2006a).

In 1976, The Kuala Lumpur Stock Exchange (KLSE) was established and it took over operations of KLSEB as the stock exchange. Ever since 1986, the KLSE Composite Index was regarded as the main market barometer. To enable smaller companies which are viable and have strong growth potential to be listed, Second Board of the KLSE was then launched in 11th November 1988. Further, beginning from 1st January 1990, all Singapore incorporated companies were not allowed to be traded in the KLSE and hence were delisted from KLSE and like Malaysian companies likewise. Mesdaq market at KLSE, on the other hand, was launched on 18th March 2002. Eventually after operating for 40 years, Kuala Lumpur Stock Exchange had become a demutualised exchange and was re-named as Bursa Malaysia in 2004 (Bursa Malaysia, 2006a).

Companies can go for listing either on the main board, second board or MESDAQ of the Bursa Malaysia[5]. The main board companies are relatively more stable and established than the second board companies. With the launch of the second board on 11th November 1988, smaller, viable and strong growth potential companies were encouraged to be listed on them as a way to obtain additional funds for business expansion. Meanwhile MESDAQ market provides a platform for shares of technology-based companies with minimal track record to be traded (Bursa Malaysia, 2006b).

The shares of public listed companies are normally traded in specific amounts called board lots of 100 units. Any amount less than board lots are called special or odd lots. The trading of shares takes place five days a week from Monday to Friday, except on public holidays and other market holidays which are declared closed by the Bursa Malaysia Committee. Trading hours on any market days is from 9.00 a.m. to 12.30 p.m. for morning session and from 2.30 p.m. to 5.00 p.m. for afternoon session (Bursa Malaysia, 2008a). Selected statistics of total firms listed on the main board, second board, and MESDAQ in the Bursa Malaysia as well as the market capitalisation from 1987 - 2007 is summarised in Table 1.1.

Table 1.1: The Summary of Selected Statistics of Bursa Malaysia from 1987-2007

Year

Number of listed companies

Composite index

Total Turnover1

(Million units)

Total turnover1

(RM Million)

Market capitalisation

(RM billion)

Main board

Second board

Mesdaq

Total Firms

1987

291

-

-

291

261.19

5286.00

10077.30

75.27

1988

295

-

-

295

357.38

4005.00

6760.40

98.72

1989

305

2

-

307

562.28

10162.00

18535.40

155.87

1990

271

14

-

285

505.92

13,137.90

29,521.60

131.66

1991

292

32

-

324

556.22

12,348.10

30,096.50

161.39

1992

317

52

-

369

643.96

19,264.60

51,468.50

245.82

1993

329

84

-

413

1,275.32

107,756.30

387,275.50

619.64

1994

347

131

-

478

971.21

60,143.00

328,057.40

508.85

1995

369

160

-

529

995.17

33,979.10

178,859.10

565.63

1996

413

208

-

621

1,237.96

66,461.20

463,264.50

806.77

1997

444

264

-

708

594.44

72,799.20

408,558.40

375.80

1998

454

282

-

736

586.13

58,287.30

115,180.50

374.52

1999

474

283

-

757

812.33

85,156.60

185,249.50

552.69

2000

498

297

-

795

679.64

75,408.60

244,054.30

444.35

2001

520

292

-

812

696.09

49,663.00

85,012.00

464.98

2002

562

294

12

868

646.32

55,630.20

11,6951.40

640.28       

2003

598

276

32

906

793.94

112,183.20

183,885.90

722.04       

2004

622

278

63

963

907.43     

107,610.20     

215,622.80     

722.04       

2005

646

268

107

1021

899.79     

118,819.10     

201,090.10     

695.27     

2006

649

250

128

1027

1096.24

215,448.20

277,783.20

848.70

2007

636

227

124

987

1445.03

361,282.20

540,381.10

1,106.20

2008

634

221

122

977

876.75

146,855.09

296,975.86

663.82

1Since 1995, it includes turnover of call warrants and since 2008, it includes loan stocks and exchange traded fund.
Source: Bursa Malaysia, http://klse.com.my/website/listing/totallc.htm(klse), no author, access data: 03/01/2005.

Economic Planning Unit, Prime Minister's Department, http://www.epu.jpm.my/New%20Folder/Figures2007/chapt8.pdf, no author, access data: 18/03/2008.


1.6.1 Listing Requirements of Bursa Malaysia Main and Second Board as well as Mesdaq Market

Listing Requirements of Bursa Malaysia Securities Berhad and Listing Requirements of Bursa Malaysia Securities Berhad for the MESDAQ Market outlined the main board's listing admission requirement, taking into consideration the Securities Commission (SC)'s Guidelines. The following are the listing requirements of Bursa Malaysia Main and Second Board as well as MESDAQ market (Bursa Malaysia, 2008b):

1. Main and Second board

  1. Have issued and paid-up capital of minimum RM60 million for Main board and minimum RM40 million for Second board[6], comprising ordinary shares of at least RM0.10 each[7].
  2. Have at least 25% of the total number of the company shares at the time of listing in the hands of minimum 1,000 public shareholders holding not less than 100 shares each. In fulfilling the requirements:-

  3. Bumiputera equity participation of at least 30%. Bumiputera equity participation can also make up the 25% public spread for the purpose of compliance with the National Development Policy.
  4. Minimum number of public shareholders upon listing:

    Paid-up capital                         Minimum number of shareholders

    RM40 - RM60 million                     750

    RM60 - RM100 million                    1,000

    Above RM100 million                     1,250
  5. Have a total market capitalisation of at least RM500 million upon listing and profit after tax of at least RM30 million for the most recent full financial year for main board. There are no listing requirements on market capitalisation and profit after tax for second board.

  6. Have traded in board lots of 100 shares or odd lots of any amount less than board lots.

2.MESDAQ market

  1. Profit record for the past 5 financial years or since the date of incorporation or commencement of operations, whichever is later, is required for technology and non-technology companies and Technology Incubators.

  2. Have achieved minimum RM2 million of paid-up capital for technology and non-technology companies and minimum RM20 million for Technology Incubators comprising ordinary shares with par value of at least RM0.10 each.

  3. Have at least 25% of the total number of the company shares at the time of listing in the hands of minimum 1,000 public shareholders holding not less than 100 shares each.

  4. Have traded in board lots of 100 shares or odd lots of any amount less than board lots.

1.6.2 The Kuala Lumpur Composite Index (KLCI)

Prior to 1986, there was no index which represented the entire Malaysian stock market. In 1986, the KLSE Composite Index (KLSE CI) was introduced and was accepted as the local stock market barometer. It has served as an accurate indicator of the performance of the entire Malaysian stock market and the economy through providing an opportunity for greater information dissemination for all market participants, including investors, to make well-considered investment decisions. The KLSE CI comprises a sample of stocks listed on the Main Board of Exchange and the number of stocks included in the composition could vary from time to time. The index started with a sample of 67 component stocks. In 1995, the number of component companies which compute the composite index was increased to 100 stocks (refer Appendix 1). The number of component companies is limited as such although the actual component companies may change from time to time (Bursa Malaysia, 2008c).

The name of the KLSE Composite Index (KLCI) was later changed to Kuala Lumpur Composite Index (KLCI) in 2004[8]. The construction of the KLCI is based on the market capitalisation weighted method. The KLCI represents the average price of all component stocks on a given date and the chosen base period was 2nd January 1977 then. Being a market capitalisation-weighted index, the KLCI gives more weightage to companies which have greater market capitalisation than others. This implies that stocks with greater number of outstanding shares and higher stock price will give greater contribution or impact to the value of the index. To further illustrate, the method of computation is shown below (Bursa Malaysia, 2008c):

Aggregate Market Capitalisation of Component Stocks on a Given Date x 100
Aggregate Market Capitalisation of Component Stocks on 2.1.1977

  1. Companies whose market capitalisation fall within the first two quartiles of the main board companies' market capitalisation.

  2. Companies whose annual volume fall within the first three quartiles of the main board companies' volume.

  3. Index constituents are not suspended for more than 3 calendar months. Otherwise, they are only eligible for inclusion after 6 calendar months from the date the suspension is uplifted.

  4. Affected companies pursuant to PN4, PN10, PN16 or PN17 are not eligible for inclusion. Index constituents designated as such will be excluded.

  5. Companies are owned not more than 50% by any KLCI constituents and in fact are defined as subsidiaries under the Malaysian Companies Act.

  6. Newly-listed companies will be considered for inclusion after a minimum period of 3 months from the date of listing. Those in new industries may even be considered for inclusion after a minimum period of 1 month from the date of listing.

  7. Where a new issue is more than 1.0% of the full capitalisation of main board, Bursa Malaysia may decide to include the new issue as a constituent of KLCI after 1 month of listing, provided the volume traded for the month is within the first three quartiles.

  8. Index constituents with two consecutive years of losses may be excluded;

  9. The market capitalisation weighting of each sector within the KLCI shall not exceed 125% of the main board 's sectoral weight to avoid over-representation of a particular sector.

  10. Where the market capitalisation of companies to be included or excluded exceed 5% of the market capitalisation of the KLCI, the proposed index constituent changes may be carried out on a staggered basis. If a single constituent's market capitalisation exceeds the 5% rule, only that constituent will be included or excluded at any effective date.

  11. Where Bursa Malaysia considers that an exception should be made to any of the Index Rules, the exception granted shall not be deemed to create a precedent for future decisions.

1.6.3 Regulatory and Market Structure

Starting from 1965, all listed companies in the Stock Exchange of Malaysia were governed by the Companies Act 1965 through its comprehensive legal framework. Then, Capital Issues Committee (CIC) was formed in year 1968 to guide the development of this securities industry. Next, the KLSE Berhad was incorporated under the Securities Industry Act 1973 (SIA) enacted in year 1973 which had then been replaced by SIA (1983) in order to provide better supervision and control of the industry. Consequently, Securities Industry (Central Depositories Act) emerged in year 1991. Somehow there is no single authority that was entrusted with the responsibility of regulating and systematically developing the Malaysian capital market before year 1993. Supervisory powers were mainly shared between industry organisations like the stock exchange and government institutions (Bursa Malaysia, 2008d).

Soon on 1st March 1993, Securities Commission (SC) was established under the Securities Commission Act 1993 which was then replaced by Securities Commission Act 2007. SC is a self-funding statutory body with investigative and enforcement powers to protect investors and promote the development of securities and futures markets in Malaysia. It is the primary authority presiding the Malaysian capital market. It holds the centre stage as the market's mover and regulator of all fund raising activities in equity, derivative and debt market. It encourages the development of the securities and futures markets in Malaysia and regulates the capital market pursuant to the Capital Markets and Services Act 2007 that consolidates the Securities Industry Act 1983 and Futures Industry Act 1993 (Securities Commission, 2008).

In 1995, the Labuan Offshore Financial Services Authority (LOFSA) was established under the Labuan Offshore Financial Services Authority Act 1995. It acts as the regulatory authority of the Malaysian capital market which provides leadership and strategic focus for the development of the IOFC under Labuan Offshore Securities Industry Act 1995 (Labuan Offshore Financial Services Authority, 2008).

Both SC and LOFSA report and table their accounts to the Minister of Finance in Parliament annually. In general, the regulatory structure diagram of security industry in Malaysia is as follows:

Figure 1.1: Regulatory Structure Diagram of Malaysian Security Industry

Source: Bursa Malaysia, 2008d, http://www.klse.com.my/website/bm/about_us/the_organisation/regulatory_structure.html, no author, access date: 01/05/2009

Having completed the demutualisation, the Kuala Lumpur Stock Exchange forged ahead with its efforts to rebrand and position itself as the premier exchange in the region. On 20th April 2004, it officially launched its new name, Bursa Malaysia, together with a new organisation structure. The holding company is now known as Bursa Malaysia Berhad which is generally called the 'exchange' and was listed on the Main Board of Bursa Malaysia Securities Berhad on 18th March 2005[9] (Bursa Malaysia, 2008d). Under the holding company are the equity exchange (Bursa Malaysia Securities Berhad), the derivatives exchange (Bursa Malaysia Derivatives Berhad), the central depository (Bursa Malaysia Depository Sendirian Berhad), and the clearing houses (Bursa Malaysia Securities Clearing Sendirian Berhad and Bursa Malaysia Derivatives Clearing Sendirian Berhad) as well as the Malaysian offshore exchange, the Labuan International Financial Exchange.


1.7 Outline of the Thesis

Overall, the outline of the thesis can be described as follows:

Chapter 1

Chapter 1 discusses the background of the research, problem statement, research objectives, justification and importance of the research, scope of the research, and the outline of the thesis.

Chapter 2

Chapter 2 reviews the existing theories, practices, and empirical research on the contemporaneous and causal relationships between volume traded and stock returns; linear and nonlinear causality tests; and dynamic volume and returns autocorrelation in both local and international stock markets. The reviews are done with respect to ordinary least squares and Granger causality tests with the efficient market hypothesis, mixture of distribution hypothesis, and the sequential arrival of information hypothesis. In the context of the individual dynamic volume-return relation, this study focuses on the impact of information asymmetry.

Chapter 3

Chapter 3 describes the research design and the development of theoretical framework for the dynamic volume-return relation and information asymmetry. Population, sampling frame, sample procedure, sample size, data, methodologies, and testing procedures of the study are described and discussed. The research hypotheses are also formulated in this chapter.

Chapter 4

The aim of this chapter is to present the results from the tests of linear contemporaneous and causality relations which are consistent with the mixture of distribution hypothesis and sequential arrival of information hypothesis in the Bursa Malaysia throughout a sample period from 1st July 1989 to 30th June 2005. The analysis is conducted on full sample and three sub-sample periods.

Chapter 5

This chapter presents the results of the analysis of motives to trade on daily returns, returns auto-correlation, and trade-generated returns of all the public listed companies in the Bursa Malaysia from 1st July 1997 to 30th June 2005. The analysis is conducted on full sample period and two sub-sample periods.

Chapter 6

Finally, this chapter presents the conclusions of the findings, implications and recommendations, possible limitations of the study as well as suggestions for future research.


[1] Fama (1970) made a distinction between three forms of efficient market hypothesis (EMH): (a) the weak form, (b) the semi-strong form, and (c) the strong form.

[2] The KLSE Composite Index (KLSE CI) was introduced in 1986 and it is accepted as the local stock market barometer. The name of the KLSE Composite Index (KLCI) had been changed to Kuala Lumpur Composite Index (KLCI) in 2004.

[3] Further criteria could be the geographic region or the levels of external debt. See World Bank (2003), p.15. In the income classification of 2003, the World Bank followed for the first time the terminology of systems of National Accounts (SNA) from 1993 by exchanging GNP with GNI.

[4] The World Bank emphasizes that "...developing economies ... does not imply that all the economics belonging to the group are actually in the process of developing nor that those in the group have necessarily reached some preferred or final level of development. Classification by income does not necessarily reflect development status." (Word Bank, 2007).

[5] The Main Board and Second Board of Bursa Malaysia will be merged and known as Main market while Mesdaq market will be revamped and named as Ace market effective on 3rd August 2009 (Oh, 2009).

[6] The minimum paid-up capital will be increased when needed by the Bursa Malaysia. The initial paid-up capital requirement according to Yong (1996) was a minimum paid-up capital of RM40 million for the main board companies and a minimum paid-up capital of RM10 minimum up to maximum of RM40 for second board companies. As of 1st April 1997, the minimum paid-up capital requirement was increased to RM50 million for main board companies. The paid-up capital for the second board companies was RM10 million and up to a maximum of RM50 million. The listing requirements for the main and second board above would be revamped in order to enhance corporate governance and transparency as well as market efficiency. Effective from 1st June 2001, the paid-up capital for the main and second board shall be RM60 million minimum and RM40 million minimum respectively (KLSE, 2004).

[7] The initial par value was fixed at RM1.00. As of 13th June 2000, the par value need not be fixed at RM1.00, subject to a minimum par value of not less than 10 cent per share (KLSE, 2004).

[8] The KLCI will be renamed as the Financial Times Stock Exchange (FTSE) Bursa Malaysia KLCI (FBMKLCI) effective on 6th July 2009 (Financial Times Stock Exchange, 2009).

[9] Bursa Malaysia Berhad is formerly known as Kuala Lumpur Stock Exchange Berhad

Source: Essay UK - http://turkiyegoz.com/free-essays/finance/price-movements.php


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