In the last decades, it can be seen that quantitative methods and mathematical models are increasingly used by researchers in the context of security pricing. One of the important breakthrough concepts is the rise of Capital Asset Pricing Model (CAPM). Under the CAPM framework, the major risks relevant to security pricing can be separated into two main risks, namely the firm specific risks as well as the systematic risks. Under the theory of CAPM, in a diversified portfolio, the relevant risks that should be priced in the portfolio of security are the systematic risks. The systematic risks can be measured by beta. However, the use of beta to price security has been receiving many critiques. A review of the literatures on assets pricing indicates that the many systematic risks cannot be captured by beta; as there are many other macroeconomic factors contributing to the variation of assets prices. Some other risks to be priced in may include the business cycle risks, energy price risk, inflation risks, interest rate risk and any other possible economy-wide risks affecting the financial markets (Borys, 2011; DeStefano, 2004). In other words, beta is not sufficient in pricing of the many economic related risks, and hence fails to explain the variability of assets returns in the financial markets around the world (Bernstein, 2007). As such, more factors should be considered in modeling or establishing more reliable asset pricing model. The multifactor equity pricing model is perfectly suited to price the equity market, as there are evidences supporting that the systematic risks can be decomposed or better represented by many other systematic factors. It is also intuitively logical. It enables researchers to investigate the relevant risks exposures being priced in the financial market, and convey richer information on the systematic factors affecting the assets returns in the financial market (Faff & Chan, 1998).
One of the frameworks developed to improve the low explanationary power of CAPM or beta is performed by Fama and French (1992). Accordingly, Fama and French (1996) suggested a three factor model to explain average stock returns. Since then, the Fama and French three factor model has become one of the standard tools popularly employed by researchers to study assets returns in different context or countries around the world. To be specific, Fama and French (1992) added firm size as well as book-to-market value ratio to the conventional market index model to explain average stock returns. Many studies on Fame and French three factor model had been performed. As will be further articulated in next Chapter, among the studies employing Fama and French three factor model in attempting to explain cross sectional average stock returns include: Javid (2008); Singh (2009); Hearn (2010); Naughton and Veeraraghavan (2005); Walid (2009); Dempsey (2010); Kassimatis (2008); Simlai (2009); Drew, Naughton and Veeraraghavan (2005); Nartea, Ward & Djajadikerta (2009); Mirza & Afzal (2011); and Novak & Petr (2010).
In this report, multifactor equity pricing model will be applied to develop the multifactor equity model for stock index returns in Malaysia. The methods used in establishing the multifactor model will be similar to the process used to construct the Fama-French Three Factor Model, as outlined in the famous literature of Fama and French (1992). Specifically, the firm size, book to market ratio will be added to the market index to explain the variation of stock index returns in the Kuala Lumpur Stock Exchange.
Since the proliferation of the CAPM concepts in the finance literature, many researchers are conducting various researches to test the validity as well as the applications of the model in the different financial market around the world. However, unsatisfactory results had been obtained, as beta is obviously not sufficient to explain the variation of asset returns in different countries around the world (Borys, 2011; DeStefano, 2004; Fifield et. al., 2002). Thus, to establish better model that is able to explain the variations of assets returns, multifactor models are widely used. The multifactor model are selected in this report as it is academically sound, widely acknowledged on its usefulness and has been proven to explain more variations of assets returns by several literatures. Apart from that, by establishing a multifactor model to characterize the stock index returns on a particular market, many valuable insights or information can be obtained. The relevant risks factors being priced in the financial market can be investigated and ferreted (Reilly & Brown, 2003). As such, it is reasonable to conduct multifactor model to investigate the nature of financial market in the selected stock exchange.
Many literatures have been conducted to investigate the relevant systematic factors prevalent to certain financial markets in the world. The use of multifactor equity pricing model to characterize or model the assets returns of financial market for stock exchange for a particular country is nothing uncommon. However, it can be seen that most of the multifactor model had been conducted or applied to the context of the developed countries, particularly to investigate the stock returns in the United States. Although there are also more researches of such kind being carried out in the Asian context, the relevant studies are relatively lacking. Indeed, for those studies related to applications of multifactor models in Asia, the applications of multifactor models have been largely concentrating on more popular countries such as China, India, Korea, Japan, or Hong Kong. Thus, it is of the author interested to investigate how the multifactor model can be applied or used in the context of characterizing stock index returns on stock exchange in the less popular country in Asia. Malaysia is selected for this purpose. Malaysia is selected because it is becoming a more important economy in the South East Asian region, whereby the economy of that region is expected to be strongly benefited by the rise of China and India in Asia. Besides, there are also no studies being performed to establish multifactor model to characterize the stock index returns from Kuala Lumpur Stock Exchange. By having greater understanding on the validity of multifactor models in Malaysia, the relevancy of these models in emerging and small countries can be investigated. In fact, such a study will also reveal if different risks factors are responsible in driving stock returns in the smaller emerging countries such as Malaysia.
Since the proliferation of multifactor framework and concepts, different researchers have been trying to employed different factors to be included in their respective multifactor model. However, the great challenge in this context is that the empirically important factor is hard to be identified. Indeed, there is little way to identify the priced factors that can be expected to affect stock returns in the future. Apparently, different researchers have been utilizing different factors in their model in attempting to explain stock returns. As will be further discussed in Chapter 2, among the different types of multifactor models developed include the following: Chen, Roll and Ross model; Burmeister, Roll and Ross model; Fama and French three factor model; as well as Carhart model.
Although there are many different multifactor models suggested by different scholars or researchers, it is indeed easy to observe that the most widely tested and popularly discussed multifactor models, be it in finance textbook or literature is the three factors model developed by Fama and French (1992). There are many reasons to which Fama and French three factors model is chosen to be tested in this study. Firstly, as mentioned before, Fama and French three factors model is widely employed by many researchers or scholars in attempting to explain cross sectional average stock returns in the context of their interest. For example, some of the studies designed to investigate empirical evidences on cross sectional average stock returns through application of Fama and French three factors model include the following: Javid (2008); Singh (2009); Hearn (2010); Naughton and Veeraraghavan (2005); Walid (2009); Dempsey (2010); Kassimatis (2008); Simlai (2009); Drew, Naughton and Veeraraghavan (2005); Nartea, Ward & Djajadikerta (2009); Mirza & Afzal (2011); and Novak & Petr (2010).
Secondarily, it is also found that the results findings by previous researchers on the validity or explanatory power of Fama and French three factors model is contradictory. Empirical evidences on the issue if Fama and French three factors model is valid in different countries are mixed. More specifically, there are studies found that firm size or market-to-book-equity ratio is not being priced in certain stock exchange, while other researchers apparently able to discover empirical evidences supporting the assertion or findings of Fama and French (1992). Those researchers findings empirical evidences supporting Fama and French three factor model include: Javid (2008); Singh (2009); Hearn (2010); Naughton and Veeraraghavan (2005); Walid (2009); Dempsey (2010); Kassimatis (2008); and Simlai (2009). Then, researchers found mixed empirical evidences on Fama and French three factor model are Drew, Naughton and Veeraraghavan (2005) and Nartea, Ward & Djajadikerta (2009). Lastly, there are studies indicating that Fama and French three factor model has no explanatory power in explaining variation of stock returns in certain countries. Example of such studies include: Mirza & Afzal (2011); and Novak & Petr (2010).
Following from our discussion above, the following two research objectives can be formulated.
- To review the relevant theories and literatures related to multifactor equity pricing model.
- To test the validity of Fama and French three factor model in Kuala Lumpur Stock Exchange, Malaysia. To be more specific, this study aim to investigate if both firm size and book-to-market value ratio is indeed priced risk factors in Malaysia stock exchange.