# CHAPTER 4: DATA ANALYSIS

## 4.1 Presentation of Simulation Results

In This section, the results simulated from SPSS will be presented. Firstly, for each pair of the fundamental variables to stock returns, correlation coefficient will be generated. Statistically significant correlation will suggest that there are significant relationships between the two variables. For those variables that exhibit statistically significant relationships with stock returns, the regression line with the scatter plot of the particular variable to stock returns will be simulated. This is important to present graphical representation for investors to further understand how these two variables related to each other graphically.

The output generated from SPSS will be largely presented in the Appendix section, to facilitate the presentation flows and process in this dissertation. Appendix section is accessible at the end of this dissertation. In the Appendix section, the tables detailing the correlations coefficients between cross sectional stock returns as well as the other fundamental variables will be presented. A total of nine tables, corresponding to correlation coefficients between stock returns and the following variables, 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) are presented. In these tables, the correlations corresponding to the pair of variables for each of the year is highlighted in the table. For example, the correlation between the cross sectional stock returns in year 2006 and the average ROE for the samples in year 2006 will be highlighted. In similar way, the correlations between cross sectional stock returns and the average ROE for the samples in year 2007, 2008, 2009 and 2010 will be highlighted as well.

Nevertheless, the correlations between stock returns to the fundamental variables will be summarized in Table 4.1 as follow. The p-value of the respective correlation coefficient is also shown in bracket. In the table, the average figure is also presented. The ‘average’ figure is actually the correlation coefficients between the averages cross sectional stock returns from year 2006 to 2010, to the average of the respective fundamental variables (from year 2006 to 2010). A discussion on the results findings related to correlation coefficients shown in Table 4.1 below will be presented in the following paragraphs.

**Relationships between return on equity (ROE) to cross sectional stock returns**. In theory, holding everything constant, the higher the return on equity, the higher the stock returns. To explain, the higher the ROE of a company, it suggests that the company is more profitable. As the company is more profitable, the company is likely to be valued more favorably by investors. Thus, overall, ROE should be positively related to stock returns. From Table 4.1, it is discovered that the correlation between ROE and cross sectional stock returns in financial year 2007 is statistically significance at the 5% level. This findings, is consistent with the theory. For this, the scatter plot as well as the regression line for the relationships between ROE and cross sectional stock returns in financial year 2007 is presented in Figure A.1 in the Appendix section. It is found that the relationships are not affected by outliers. Indeed, there are several few observation points contributing to the positive relationships between ROE and cross sectional stock returns in financial year 2007. Nevertheless, the correlations in the other financial years are not statistically significant. Indeed, the sign of these correlation coefficients are mixed. Considering all of these findings, it can be concluded that there are weak findings supporting the idea that in Malaysia, ROE is positively related to cross sectional stock returns. The absence of statistically significant relationships between the two variables, however, suggests that in certain years, ROE may not be able to be used in explaining cross sectional stock returns in Malaysia.

**Relationships between P/E ratios (PE) to cross sectional stock returns**. In theory, holding everything constant, the lower the price to earnings ratio, the higher the stock returns. In other words, PE should be inversely related to cross sectional stock returns. Such a theory is actually consistent with the philosophy of value investing, whereby the price is what investors pay, while the real value is what the investors get. In order to be successful in investing, the price is a crucial element to be aware of. Investors should never pay high prices for stocks, based on the fundamentals of the particular stock or company. As shown in Table 4.1, it is found that overall, in the entire research periods, the correlation coefficients between PE and cross sectional stock returns is negative – consistent with the theory previously discussed. On closer investigation, it is found that statistically significant relationships between PE and cross sectional stock returns can only be found in year 2007. In financial year 2007, both the variables are statistically significant at 1% level. Overall, the findings are supporting the claims from successful value investors such as Warren Buffet, John Neff and Peter Lynch as discussed before. The higher the price investors paid for a security, the lower the expected returns tend to become. Considering that throughout the research period, the PE ratios are inversely related to cross sectional stock returns, it can be concluded that there are empirical evidences supporting the notion that stock priced at a lower price to earnings ratios tend to yield higher returns in the future.

**Relationships between dividend yields (DY) to cross sectional stock returns**. In theory, holding everything constant, the higher the dividend yield, the higher the stock returns. The logic of paying dividend to investors is not something new. Indeed, according to the Discounted Dividend Model (DDM), dividend payments are used to establish the intrinsic value for securities. The higher the dividend paid to investors, the higher the intrinsic value of that particular stock. As such, generally speaking, the higher dividend payment from a stock, the more likely the particular stock will be valued favorably by investors, and hence, the higher expected stock returns the particular stock should have. From Table 4.1, it is found that there are strong evidences supporting the notion that dividend yield is related to cross sectional stock returns. In all of the periods under studied, dividend yields are positively related to stock returns. Indeed, the positive relationships between dividends yield to cross sectional stock returns are most obvious among the various fundamental variables being investigated. Indeed, the relationships between cross sectional stock returns to dividend yield are statistically significant, at 5% level, for financial year 2007, 2009 and 2010. For all of these financial years, the scatter plots as well as the regression lines for the relationships between dividend yield and cross sectional stock returns are presented in Figure A.3, Figure A.4 and Figure A.5 in the Appendix section. Generally speaking, a review of these scatter plot discover that the relationships is not affected by only a single outliers. Indeed, there are several observations contributing to the positive relationships. Indeed, it is found that none of those stocks with excessively high dividend yield experiences negative cross sectional stock returns at the respective years. In a nutshell, for investors planning to invest in Malaysia stock market, they should look seriously into dividend yield of the different stocks. The usefulness of dividend yield, in explaining stock returns in Malaysia is not irrational. Firstly, in emerging market, it is easy to imagine that the corporate governance can be weak, and accounting fraud may be rampant. Thus, the only real indicator that investors can rely upon is the dividend payment from the company to investors. Ultimately, management cannot fake dividend payment – it is hard cold cash – not subjected to accounting gimmicks.

**Relationships between price to sales ratios (PS) to cross sectional stock returns**. In theory, holding everything constant, the lower the price to sales ratio, the higher the stock returns. Similar to the concept of price to earnings ratios, price to sales ratios is essentially a variation of price multiple criteria widely used by investors in investing decision making process. As discussed before, in order to be successful in investing, the price is a crucial element to be aware of. Investors should never pay high prices for stocks, based on the fundamentals of the particular stock or company. As such, the negative or inverse relationships between prices to sales ratios to cross sectional stock returns are to be expected. In Table 4.1, it is observed that in most of the financial years being studied, the prices to sales ratios are negative, except in financial year 2010. Nevertheless, none of the correlation coefficients between prices to sales ratios to cross sectional stock returns are statistically significant. Thus, there are no evidences supporting the notion that prices to sales ratios can be used to explain cross sectional stock returns in Malaysia.

**Relationships between price to net worth ratios (PNet) to cross sectional stock returns**. In theory, holding everything constant, the lower the price to net worth ratio, the higher the stock returns. Similar to the concept of price to earnings ratios, price to net worth ratios is essentially a variation of price multiple criteria widely used by investors in investing decision making process. To reiterate, in order to be successful in investing, the price is a crucial element to be aware of. Investors should never pay high prices for stocks, based on the fundamentals of the particular stock or company. Thus, the negative or inverse relationships between price to net worth ratios to cross sectionals tock returns is to be expected. From Table 4.1, it is found that prices to net worth ratio in financial year 2006 is statistically significant and related to cross sectional stock returns in that particular year, as 5% level. However, in the other financial year, the correlation coefficients are not statistically significant. As such, it can be concluded that there is only weak evidence supporting the notion that prices to net worth ratios can be used to explain cross sectional stock returns in Malaysia.

**Relationships between rates of growth in revenue (RG) to cross sectional stock returns**. In theory, holding everything constant, the higher the rate of growth of revenue achieved by a company, the higher the stock returns. In Table 4.1, it is however, observed that there is not statistically significant relationships between rates of growth in revenue to cross sectional stock returns in Malaysia, from financial year 2006 until 2010. As such, it is concluded that there are no evidences supporting the notion that rates of growth in revenue can be used to explain cross sectional stock returns in Malaysia.

**Relationships between rates of growth in EPS (EPSG) to cross sectional stock returns**. In theory, holding everything constant, the higher the rate of growth of EPS achieved by a company, the higher the stock returns. In Table 4.1, it is observed that there is a not statistically significant relationship between rates of growth in EPS (i.e., earnings per share) to cross sectional stock returns in Malaysia, from financial year 2006 until 2010. As such, it is concluded that there are no evidences supporting the notion that rates of growth in EPS can be used to explain cross sectional stock returns in Malaysia.

**Relationships between PE to Growth ratios (PEG) to cross sectional stock returns**. In theory, holding everything constant, the lower the PEG ratio, the higher the stock returns. However, from Table 4.1, it is discovered that PEG does not exhibit any sort of statistically significant correlation relationship with cross sectional stock returns in Malaysia. Thus, similar to the case of relationships between rates of growth in revenues and rates of growth in EPS to cross sectional stock returns just discussed before this, it can be concluded that there are no evidences supporting the notion that PEG can be used to explain cross sectional stock returns in Malaysia.

## 4.2 Discussions on Research Findings

Overall, it is found that some of the assertions of successful investors are supported with statistically significant correlation coefficients in the study presented in this dissertation. In the context of Malaysia, using historical data from financial year 2006 to financial year 2010, some of the fundamental variables, namely, return on equity (ROE), price to earnings ratios (PE), dividend yields (DY), and price to net worth ratios (PNet), exhibits statistically significant correlation coefficients with cross sectional stock returns in certain financial years. It is noted that the sign of those statistically significant correlation coefficients are indeed consistent with the theory or with the assertions from the successful investors. To explain, in financial year 2007, ROE is statistically significant positively correlated to cross sectional stock returns. Then, in financial year 2007, PE is statistically significant negatively correlated to cross sectional stock returns. Next, in financial year 2007, 2009 and 2010, DY is statistically significant positively correlated to cross sectional stock returns. Lastly, in financial year 2006, PNet is statistically significant positively correlated to cross sectional stock returns.

Nevertheless, some of the fundamental variables are found to exhibit no statistically significant relationships with cross sectional stock returns in Malaysia. Among these variables include: price to sales ratio (PS), rate of growth in revenue (RG), payout ratio, rate of growth in earnings per shares (EPSG), and Price Earnings to Growth ratio (PEG). As such, from this study, it is suggested that it can be concluded that there are no evidences supporting the notion that these fundamental variables can be used to explain cross sectional stock returns in Malaysia.

Overall, the study conclude that the fundamental variables is useful in explaining cross sectionals tock returns even in emerging country such as in Malaysia. For example, firms with high ROE tend to outperform those firms with lower ROE. Although evidences on such outperformance are not available in the other financial years, there are some periods that such outperformance may materialize. Then, dividend yields are found to be the most useful fundamental variables that can explain stock returns in the period under investigation. For example, in a research period of 5 years, dividend yield is positively and statistically significantly correlated to cross sectional stock returns in 3 of the financial years. This suggests that in 60% of the time, dividend yields may be accurate variables to explain stock returns. Then, it is found that, among the many price multiples, namely, prices to earnings ratio, prices to sales ratios, and prices to net worth ratios are useful in explaining cross sectional stock returns in Malaysia. For example, there are empirical evidences supporting that price to earnings and prices to net worth ratios are statistically significantly correlated to cross sectional stock returns in certain financial years. Then, in most of the financial years, the prices to sales ratios are negatively related to cross sectionals tock returns. All of these weak evidences, when combined strongly suggest that in order to be successful in investing, the price is a crucial element to be aware of. Investors should never pay high prices for stocks, based on the fundamentals of the particular stock or company. The notion that – money is made in the buying, not in the selling – is supported. The price investors paid for the securities, will ultimately affect the returns of the investors.

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