The country selected for investigation purposes is Malaysia. Malaysia is selected because it is a smaller country, and often is neglected in the context of study of stock returns. In contrast, there are already many studied conducted for developed nations, such as in United States, United Kingdom, Japan, or the more popular emerging country such as China and India. Secondly, Malaysia is a viable candidate for research due to advantage of data availability. The author has friends from Malaysia capable to collecting data from the database of Malaysian local stock brokerage firm. Overall, Malaysia is a viable candidate for research because there is no such study being conducted before, and this dissertation will be able to cover the knowledge gap unknown to scholars.
As discussed in the previous chapter, there are many different types of variables that are perceived to be influential in affecting or explaining stock returns. One of the categories of variables is the macroeconomic factors. Among macroeconomic factors that are perceived may be able to affect or explain stock returns include the following: interest rates, inflation rate, money supply, industrial production index, oil prices, exchange rates, unemployment rate, consumer confidence as well as many other economic indicators widely discussed by economists or in financial mass media. Then, it is also discussed that fundamental factors are of the firms’ specific factors, which include the following: return on capital, return on equity, price to earnings ratios, price to sales ratio, price to net worth ratio, dividend yield, rate of growth in revenue, rate of growth in earnings per shares, Price Earnings to Growth ratio, as well as any other relevant financial ratios or metrics.
In this research design, only those fundamental variables will be investigated, because it is found from literature review that fundamental factors tend to be more able to explain stock returns. Specifically, studies on relationships between firms specific fundamental and financial ratios tend to yield better statistical results when compared to macroeconomic factors. Besides, this is a study on stock investment, which the objective is to understand on how to pick the high performance stock in the future. Thus, firm specific factors are more relevant in such a context – in explaining cross sectional stock returns in the financial market. In the contrary, macroeconomic forces is more likely to affect the stock market returns in a systematic manner.
Thus, in this study, the fundamental variables investigated include the following: return on equity (ROE), price to earnings ratios (PE), price to sales ratio (PS), price to net worth ratio (PNet), dividend yield (DY), rate of growth in revenue (RG), payout ratio, rate of growth in earnings per shares (EPSG), and Price Earnings to Growth ratio (PEG). The cross sectional stock returns for Financial Year 2006 to Financial Year 2010 will be investigated. The companies listed under Kuala Lumpur Composite Index (KLCI) will be selected in this study. There are a total of 100 companies listed under KLCI. However, not all of the firms listed in KLCI are employed in this study. A total of six companies are excluded because they undergo merger and acquisition activities, which will affect the interpretation and calculation of appropriate financial ratios and price multiples for these firms complicated. As such, there are 94 companies listed under KLCI being used in this research. The listed companies under KLCI can be obtained from Bursa Malaysia (or more commonly known as, the Kuala Lumpur Stock Exchange) as the following web portal: www.klse.com.my.
The firm specific data, pertaining to the 94 listed companies under KLCI, being studied in this research can be obtained from databases of OSK Investment Bank Bhd. OSK Investment Bank Bhd is the leading brokerage and investment bank in Malaysia. The brokerage house provide a comprehensive database on firms financial statement and other relevant firm specific details for the clients that are trading using the firm’s stock trading platform. The website of the trading platform for OSK Investment Bank Bhd can be reached at the following address: http://www.osk188.com/index.jsp. However, the database does only provide financial information for the firms listed in Malaysia to a maximum period of 5 years. Thus, the study conducted in this dissertation is only limited to the five year research period, from Financial Year 2006 to Financial Year 2010.
In order to save space for this report, symbols for the respective variables are employed. As discussed before, the fundamental variables employed in this study include the following: return on equity (ROE), price to earnings ratios (PE), price to sales ratio (PS), price to net worth ratio (PNet), dividend yield (DY), rate of growth in revenue (RG), payout ratio, rate of growth in earnings per shares (EPSG), and Price Earnings to Growth ratio (PEG). The description of these variables will be presented in table 3.1 as follow.
Besides, the theoretical relationships between variables to stock returns will also be articulated. The theoretical relationships can then be compared to the simulated results to understand if the conventional understandings are true or contradict the theories or assertion of successful investors or diligent scholars as discussed in Chapter 2. The theoretical relationships between the variables to future stock returns are shown in Table 3.2 below.
Having discussed the research variables to be employed in this study, the discussions in the following sections will focus on the research methodologies used for the study conducted in this dissertation.
Generally speaking, this is a study of quantitative research, whereby historical data concerning stock returns as well as the relevant fundamental factors or variables, which are perceived to be influential in affecting stock returns, will be obtained, and subsequently analyzed. It is also assumed that historical data and events can be useful in guiding investors in making their investment decision. As discussed before, the fundamental variables employed in this study include the following: return on equity (ROE), price to earnings ratios (PE), price to sales ratio (PS), price to net worth ratio (PNet), dividend yield (DY), rate of growth in revenue (RG), payout ratio, rate of growth in earnings per shares (EPSG), and Price Earnings to Growth ratio (PEG).
Upon obtaining the data, SPSS Version 17.0 will be employed to conduct statistical analysis. Statistical concepts employed in this research include both Pearson correlation coefficient and R-square. In the study of financial market and social science, correlation coefficient is a common concepts employed by scholars. It is actually a measure of the degree of association between two variables. When the two variables are said to have positive correlation, it means that the two variables move in tandem. When a particular variables move upwards, another variables tend to move upwards as well. In contrast, when a set of two variables have negative correlation, it is suggesting that when a particular variables move upwards, another variables tend to move in the opposite direction. From correlation coefficient, it is possible to understand how the two variables, which in this study, the fundamentals variables of a company to the stock return of the particular company, relate to each other. By understand how the fundamental variables associated with stock returns from a historical perspective, then it is possible for scholars to further investigate the rationales behind the relationships, and hence, more likely to ferret out the real factors or driving forces affecting stock returns in the future. Apart from that, regression line and scatter plot will be generated to investigate the relationships between stock returns to the specific fundamental variables from a graphical perspective. This is important as detection of outliers that affect the regression line is crucial. Outliers may be meaning or not in describing the relationships between two variables. Besides, the R-square of the regression line will also be computed. Generally, a higher score of R-square suggest that a variable can explain the variation in the other variable more satisfactorily. In this study, scatter plot and regression line will be generated for each pair of the variables that generates statistically significant correlation coefficients.
There are several limitations inherent in the nature of the research methods employed in this dissertation. Firstly, the measures of correlation suggest linear relationships exist between the two variables being investigated. However, in actual, the relationships between the fundamental variables to stock returns may be far from linear. The relationships between a specific fundamental variables to stock returns may be dynamic, time varying and not constant. Thus, correlation coefficient may not be able to capture the real relationships between fundamental variables to stock returns.
Apart from that, correlation, after all, is a measure of degree of association between fundamental variables to stock returns. It does not imply that there must be economically meaningful relationships between fundamental variables to stock returns. Technically speaking, correlation is not similar to causation. Thus, existence of correlation between fundamental variables to stock returns does not imply that the specific fundamental variables are actually affecting stock returns, positively or negatively. As in the study of stock market, many factors could be affecting the stock returns simultaneously, in different ways, and in different directions. As such, to truly understand the real relationships between fundamental variables to stock returns, many different types of studies are required to further enhance the researchers’ understandings on the real factors driving stock returns.
In a nutshell, this is a study to identify the existence of any statistically relationships between fundamental variables to stock returns. It is best viewed as a preliminary or introductory study on relationships between fundamental variables to stock returns. If there are statistically significant between the variables, the views of the economists, successful investors or economists may be justified. In the last chapter, suggestions for research topics in the future will be presented. These studied can be used to better reveal the real reflection of the financial market and drivers of stock returns.