UNIVERSITI MALAYSIA SARAWAK (UNIMAS)

SEMESTER 2 2012/2013

FACULTY OF ECONOMICS AND BUSINESS (FEB)

EBF 3183 FINANCE SEMINAR

(Group ASSIGNMENT)

Financial Ratios and Stock Return: Evidence on selected Plantation Companies in Malaysia

NAME:VICTORIA AK JUTI 28578

VENOSHNI A/P MANOGARAN 28577

PHUA WEE WEE 27952

TEOH CHIEN NI 28513

LING LING26752

GROUP:1

PROGRAMME:FINANCE

Financial Ratio and Stock Return: Evidence on selected Plantation Companies in Malaysia Abstract

This paper is to investigate the predictive ability of several financial ratios for stock return in Malaysia specifically in plantation industry. 23 listed plantation companies were analysed for the period from 2008 to 2012. Four of the common financial ratios were take into consideration in this study. These financial ratios include dividend yield (DY), book to market ratio (B/M), earning per share (EPS), and firm size. Pool ordinary least squares regression (OLS) method is adopted to estimate the predictive regression. The descriptive statistics indicate that there is a negative relationship between the dependent variable and the two independent variables include B/M and EPS. In contrast, the firm size and DY is positive correlated with the stock return. In addition, the empirical results indicate that dividend yield is the best predictor on stock return in the context of Malaysia’s plantation sector.

Section 1 Introduction

Introduction

Research on predicting stock returns using various variables such as inflation, accuracy of disclosure of public information, discount rates are widely discussed in past studies. Return is something that investor expects to receive on their original investment in the future. Alternatively, financial ratios have provided investors another method in predicting the stock return. Previously, financial ratios are used to evaluate performance of a company. So far, numerous studies on stock return and financial ratios have conducted based on different sectors over the countries. However, the research on plantation sector is limited. Therefore, our main focus of this research is to determine the connection between financial ratio and stock return in the Malaysia stock market especially in the plantation industry.

The reason plantation sector is chosen as our focus in this research is due to the growing of global demand in plantation. Presently, plantation is one of the major contributors in the economy of Malaysia amongst the sectors. In Malaysia, oil palm industry is currently the second largest export revenue earner for Malaysia after the electrical and electronics (E&E) sector. Meanwhile, Malaysia is also known as the world’s top exporter of palm oil which exported to several countries such as China, India, the European Union (EU) and Pakistan. Essentially, plantation sector is expected to rise in the future. In this study, we examine how the stock return can be predicted by using the financial ratio. 23 of plantation listing firms in Bursa Malaysia are selected as our research data. Meanwhile, the period we take into consideration is over the period from 2008 to 2012.

The purpose of this research is to determine the predictability of financial ratio to the stock returns specifically in the plantation sector. By this research, we intend to provide an analysis of forecasting stock return using financial ratio. Financial ratios that commonly used to forecast the stock return are the dividend yield (DY), book to market ratio (B/M), and firm size. However, we extend the study by adding another financial ratio in predicting the stock return which is the earning per share. The empirical findings of this study indicate that financial ratios do have the predicting power on stock return in Malaysia’s plantation industry. Meanwhile, the results also show that firm size has the strongest forecasting power amongst the four variables.

Therefore, we can conclude that our findings are somehow in line with past studies conducted by Fama and French (1988) which revealed that dividend yield was a good forecasting tool in predicting stock return in China, Canada and U.S stock market. The remainder of the paper is organized as follows. In section 2, we discussed the previous studies and provide a review of existing literature regarding on predictive ability of financial ratios for stock return. Data and methodology for constructing stock return predictors is discussed in the third section. Section four reveals the empirical findings and lastly followed by conclusion.

Objective of study

Main:

To predict stock return using financial ratios

General:

To reveal more information regarding financial ratio acts as the predictor of stock return. To investigate how significant is the selected variables in forecasting the stock return. To determine which independent variables has greater predictive power.

Significance of study

Investing in stock market is risky. Therefore, a predicting tool is important for a wise investor to estimate the appropriate return of an investment. This research is significance in revealing the use of financial ratio as a forecasting tool of stock return. Previously, studies on the determinant of stock return are widely discussed by many of the researchers from all over the world. This study also tends to test whether our empirical results are parallel with previous research. Financial ratio is one of the most common tools that act as a financial analysis to compare the performance between companies or between industries.

Currently, financial ratio analysis is not only can be used to evaluate the performance of company but also a predictor tool of the stock return. Financial ratio is computed through the items presented in financial statement of the company. For instance, financial ratio can be divided into several categories such as market debt ratio, liquidity ratio, profitability ratio, investment ratio and others. In addition, this study also acts as guidance and reference for further research on similar topic. By referring this study, interested investor and researcher can apply different indicator, and other relevant factors to do further research.

Theoretical Framework

Section 2 Literature Review

In this section is described the results of some of the most important researches which conducted in the context of financial ratios and the stock return. The financial ratios as empirical predictors of stock returns in the selected 23 plantations companies listed on the Malaysian Stock Exchange during the period 2008 to 2012. For this research, we used stock price as a dependent variable while dividend yields, book market, earning per share and asset size as independent variables. Stock returns, dividend yield (DY), asset size, earning yield (EY) and book-to-market ratio (B/M) have a strong theoretical background based on the predictive models. Some of the studies such as Fama and French (1988), Stattman (1980), Kothari and Shanken (1997) has done research on predictive variables, including, dividend yield, book to market, earning per share and asset size forecast stock return. Hodrick (1992), Fama and French (1988) has been study that DY has the predictive power on stock returns, as the relationship between DY and return are developed by the appealing patterns. Moreover, DY track variation in return and can predict future return in 36 international markets. To illustrate the predictive power of DY, they introduced an explosive new test to improve the predictive ability of financial ratios especially DY during 55 years.

Therefore, DY is regarded as a good predictor of stock returns in China, Canada and U.S stock market. Consequently, the DY as a strong predictor can contribute to stock return predictability. Banze (1981) and Reinganum (1981) found out that relationship between sizes (market value) has a significant effect on stock return. Smaller companies have more return than bigger companies. It is because first, intentional or unintentional errors are less likely to happen because of installing strong internal controlling systems in big companies, consequently audits can rely more on the company internal controlling systems and decrease increasingly the amount of content test. Second, big companies can recruit more accountants with more expertise and higher education, and more advanced informational systems. According to study done by Fama and French (1988), they presented a firm background for the relationship between market size and stock return. Fama and French using Running single and multiple tests, they found a positive relationship between markets size and stock return.

In fact, they doubt on beta sensitivity in capital assets pricing model, and generally stock return. Stattman (1980) has done study on indicated the positive relationship between return and the book-to-market ratio (B/M). Considerable evidence they suggested that B\M ratios are related to future returns, and denoted the predictive power of B/M ratio on stock returns caused by the relationship between book value and future earnings, and provided evidence that the B/M ratios predict negative expected returns and track variation in return. The results of recent survey confirmed previous results that the B\M ratio is positively related to stock returns. According to Hakkio and Rush (1991) have study on the relationship between stock return and earnings per share. They found that the subdivision do not improve the test power. Besides, there exists a non-stationary problem for stock prices and EPS, the non-stationary may lead to the problem of spurious regression for previous studies. Auret and Sinclaire (2006) has been studied the relationship between the ratio of book value to market value (BTM) and stock return in the years 1990 to 2000 in the companies listed in the Johannesburg Stock Exchange (JSE). In this study is used from the ratio of book value to market value (BTM), price to Earnings (P/E), dividend yield (DY), and firm size as independent and control variables.

The results indicate that there is a positive and significant relationship between the ratio of book value to market value and stock return. But there is no significant relationship between the ratio of price to earnings and stock returns. According to Kheradyar, Ibrahim and Mat (2011) has been study on investigated the role of financial ratios as empirical predictors of stock returns in the 100 companies listed on the Malaysian Stock Exchange during the period 2000 to 2009. In their study is used from the variables of dividend yield (DY), earnings yield (EY) and Book-to-market ratio (BTM) as financial ratios to predict stock returns. To estimate the regression model used from panel data and generalized least squares (GLS) methods. Research findings indicate that there is a significant and positive relationship between financial ratios and stock return of next year. Also, the results showed that the ratio of book value to market value is superior against dividend yield and earnings yield in explaining stock return of next year. Lau, Lee and Mclnish (2002) has been study on the relationship between stock returns and systematic risk with firm size, the ratio of book value to market value of equity, price to earnings ratio, the ratio of cash flow to price and sale growth in both Malaysia and Singapore.

Their studied sample is 82 companies listed in the Singapore Stock Exchange and 163 companies listed in the Kuala Lumpur Stock Exchange during the period 1988-1996. Results for Singaporean companies are indicating that there is no significant relationship between the ratio of book value to market value (BTM) and earnings to price ratio (E/P) with stock returns. The results for Malaysian companies show that there is significant and positive relationship between the ratio of earnings to price (E/P) and stock returns. But the relationship between the ratio of book value to market value (BTM) and stock returns is not significant. Kothari and Shanken (1997) has been study on the relationship between the ratio of book value to market value and dividend yield with the expected market return. Results have shown that there is a significant and positive relationship between the ratio of book value to market value (BTM) and the dividend yield with market returns of future year.

Also, the results indicate the superiority of book value to market value ratio against dividend yield in explaining future market returns. According to study done by Fama and French (1988), Hodrick (1992) and Stambaugh (1999) have shown that the variables of earnings to price ratio, the ratio of dividends to the price and short-term interest rates can better predict stock returns. As a conclusion, financial theories lay great emphasis on the role of risk in stock returns so the relationship between stock returns and financial ratios is because the ratios captured information about the risk. Therefore, these three financial ratios are supported by financial theoretical basis.

Section 3 Data and Methodology

Data Collection Methods

The data collected are mainly from secondary data. The secondary data that used in this paper are included the closing price, dividend yield, book to market, earning per share and asset size of each plantation company from year 2008 to 2012. These closing prices will be collected from yahoo finance but for the dividend yield, book to market, earning per share and asset size will be collected from data stream.

Target Population

The secondary data will be used in this paper to test whether dividend yield, book to market, earning per share and asset size forecast stock return or not. Therefore, the 23 stocks listed on Bursa Malaysia will be obtained. They are included: 1． UNITED MALACCA

2． NPC RESOURCES

3． KWANTAS

4． SARAWAK OIL PALMS

5． TH PLANTATIONS

6． TSH RESOURCES

7． CEPATWAWASAN GROU

8． CHIN TECK PLANTATIONS

9． KIM LOONG RESOURCES

10． FAR EAST HOLDINGS

11． KLUANG RUBBER

12． NEGRI SEMBILAN OIL PALMS

13． SUNGEI BAGAN RUBBER

14． UNICO-DESA PLANTATIONS

15． GOLDEN LAND

16． RIVERVIEW RUBBER ESTS.

17． UNITED PLANTATIONS

18． TRADEWINDS PLANTATION

19． MHC PLANTATIONS

20． IJM PLANTATIONS

21． HAP SENG PLTNS.HDG

22． CHIN TECK PLANTATIONS

23． GENTING PLANTATIONS

Data Analysis

The collected data were analyzed by using Microsoft Excel and Eview.

Microsoft Excel will be used to calculate the stock returns for each stock for a period of around 5 years which are the year from 2008 to 2012. Besides, pool ordinary least squares regression, descriptive statistic, correlation and Hausman test from Eview will be used to run the result of our research.

Dependent variable

a. Stock return

The total stock return can be gain through the appreciation in the price plus any dividends paid and then divided by the original price of the stock. The dividends can include any of the income sources from a stock. Commonly, it is increase in value. Thus, the first portion of the numerator of the total stock return formula is looks at how much the value has increased (P1 – P0). Then, it needs to remind that the denominator of the formula which is use to calculate a stock’s total return is considered as the original price of the stock which is used due to being the original amount invested. Total stock return calculated as follow:

Total stock return =

where

= Ending stock price (period 1)

= Initial stock price

D = Dividends

Independent variable

b. Dividend yield

Usually, a financial ratio can be used to show how much a company pays out in dividends each year which is relative to its share price. Therefore, it can be said that the dividend yield is the return on investment for a stock in the absence of any capital gains. Dividend yield is calculated as follows:

Dividend yield = Annual dividends per share / Price per share c. Book to market

Sometimes, we also use a financial ratio to find the value of a company. It can be found by comparing the book value of a firm to its market value. Book value can be calculated by looking at the firm’s historical cost or accounting value. On the other hand, market value is determined in the stock market through its market capitalization. Book value is calculated as follows:

Book to market = Book value of firm / Market value of firm

d. Earnings per share

The earnings per share (EPS) can be defined as the portion of a company’s earnings, net of taxes and preferred stock dividends. Usually, all of them are allocated to each share of common stock. EPS is calculated as follows:

EPS = Net earnings / Outstanding shares

e. Asset size

Asset size is defined as the total of the current assets and the non-current assets which is holding by a company. Asset size is calculated as follows:

Asset size = total asset

Pool OLS regression

Stock return = + (dividend yield) + (book to market) + (earning per share) + (asset size) + Pool OLS is to measure whether there is positive or negative relationship between dependent variable (stock return) and independent variable (dividend yield, book to market, earning per share and asset size). R-squared is the total variation dependent Y is explained by the total variation of independent X. F-statistic is to test whether the overall goodness of fit is good or not. The significant level is set at 1%, 5% or 10%.

Descriptive Statistic

Descriptive statistic is to provide simple summarizes about the sample and the observation that have been made like mean and median.

Correlation

The correlation is called the correlation coefficient (or “r”). It ranges from -1.0 to +1.0. If r is close to 0, it means there is no relationship between the variables. If r is positive, it means that as one variable gets

larger the other gets larger. If r is negative it means that as one gets larger, the other gets smaller (often called an “inverse” correlation).

Hausman test

Hausman test is usually applied to test for fixed versus random effects models. Ho: Cov (λi, xit) = 0 (Random Effect)

H1: Cov (λi, xit) ≠ 0 (Fixed Effect)

If the p-value is lower than 0.01, we reject Ho. This indicated that the fixed effects model is preferred. If p-value greater than 0.01. We do not reject Ho. This means that the random effect is preferred. Random effect model is to utilize in meta-analysis. It is using both study sampling error and variances. The variations between studies are included in the assessment of the uncertainty or confidence interval of the results of a meta-analysis. In addition, random effects model is apply when there is no correlation between the regresses and the individual effects.

On the other hand, fixed effect model stipulates the units under analysis such as people in a trial or study in a meta-analysis are the ones of interest. Thus, this model constitutes the entire population of units. The variation between the estimates of effect from each study name as heterogeneity. It does not affect the confidence interval. Besides, this model is applied when there is allow for arbitrary correlation between the regresses and the individual effects.

Section 4 Data and Empirical Results

Research Findings:

Descriptive statistics

Variables

N

Mean

Maximum

Minimum

Standard Deviation

Stock Return

115

0.069304

1.170000

-0.600000

0.308345

Dividend yield

115

3.356435

10.31000

0.370000

2.220661

Earnings per share

115

0.345304

1.800000

0.040000

0.300544

Book to market value

115

1.193478

2.950000

0.340000

0.542936

Firm Assets

115

13.64433

15.36144

12.01738

0.816106

From the table above, on average or the mean stock return level for firms is 0.07% with a maximum value of 1.17% from 2008 to 2012. As we can see, average dividend yield for the plantation firms in Malaysia is the highest which mean 3.36% return of plantation firms in Malaysia are generated by dividend yield. Looking for the earnings per share, it shows low earnings per common share. On average Malaysian plantation firms only make earnings about 0.04% and the highest is 1.8%. This amount of earnings per share is very low compared to the dividend yield. Average book to market value is 1.19% with a maximum value of 2.95%.

Firm asset is one of the most important bank specific variables that will affect stock return. Total assets value for Malaysian plantation firms ranges from 12.02% to 15.36%. The range is big and this may due to the sample firms having operated for different lengths of time.

Correlation

SR

DY

EPS

LSIZE

MVB

SR

1.000000

DY

0.188256

1.000000

EPS

-0.048140

0.084159

1.000000

LSIZE

0.055228

-0.150209

0.239308

1.000000

MVB

-0.313238

-0.014558

0.383026

0.509393

1.000000

The stock returns for two variable that is earning per share and market to book value are moving in totally opposite direction linearly. These are because the correlation between stock return and earning per share and also the correlation between stock return and market to book value are negative relationships which are -0.05 and -0.3. On the other hand, the correlation between stock return and total asset and also the correlation between stock return and dividend yield are positively correlated which are 0.05 and 0.19. As a conclusion, based on the result above the dividend yield recorded the strongest correlated to stock return.

Pooled Ordinary Least Square

Dependent Variable: Stock Return

Variables

Coefficient

Std.Error

t-Statistic

Probability

C

-1.424024

0.492529

-2.891247

0.0046

DY

0.031544

0.011973

2.634631

0.0096

EPS

0.044259

0.094578

0.467969

0.6407

LSIZE

0.125167

0.037734

3.317073

0.0012

MVB

-0.281240

0.058763

-4.786012

0.0000

R-squared

0.214105

Adjusted R-squared

0.185527

F-statistic

7.491945

Prob(F-statistic)

0.000022

SR= -1.4240 + 0.0315 DY + 0.0443 EPS + 0.1252 LSIZE – 0.2812 MVB where

SR = Stock Return

DY = Dividend Yield

EPS = Earnings Per Share

LSIZE =Log Firm Size

MVB = Book to Market Value

The intercept value of -1.4240 means that if the all independent variable are zero, the stock returns will expected to be -1.4240. the R-squared is 0.2141 means that about 21.4% of the total variation dependent Y is explained by the total variation of independent X. the F-statistic is 0.000022 means that this regression model is statistically significant at 5% level of significant.

Therefore, the overall goodness of fit is good. From this regression, dividend yield and firm size showed positive relationship to stock return as shown by the positive coefficient. Both variables of p-value are significant at 1% of significant level. There is negative relationship between book to market value as shown by negative coefficients and the p-value is significant at 1% of significant level. The relationship between stock return and earning per share is negative and the p-value is not significant at 10% of significant level.

Fixed effect model

Dependent Variable: Stock return

Variable

Coefficient

Std. Error

t-Statistic

Probability

C

-4.296162

2.324473

-1.848231

0.0679

DY

0.040577

0.020388

1.990207

0.0497

EPS

-0.153195

0.222027

-0.689983

0.4920

LSIZE

0.361256

0.168448

2.144618

0.0347

MVB

-0.542055

0.096166

-5.636630

0.0000

The table shows the dividend yield, earning per share, firm size and book to market value. The dividend yield, size and book to market value were found be significant, the p-value are 0.0497, 0.0347 and 0.0000 respectively which are significant at 5% of significant level. The earnings per share was found not be significant, since p-value is 0.4920 which is greater than 0.05. Thus, dividend yield, size and book to market value were impact on the stock return of Malaysian plantation sector.

Random effect model

Dependent Variable: Stock return

Variable

Coefficient

Std. Error

t-Statistic

Probability

C

-1.424024

0.450854

-3.158502

0.0020

DY

0.031544

0.010960

2.878165

0.0048

EPS

0.044259

0.086575

0.511226

0.6102

LSIZE

0.125167

0.034541

3.623689

0.0004

MVB

-0.281240

0.053791

-5.228410

0.0000

The table shows the dividend yield, earning per share, firm size and book to market value. The dividend yield, firm size and book to market value were found be significant, the p-value are 0.0048, 0.0004 and 0.0000 respectively which are significant at 5% of significant level. The earnings per share was found not be significant, since p-value is 0.6102 which is greater than 0.05.

Hausman test

Test Summary

Chi-Sq. Statistic

Chi-Sq. d.f.

Prob.

Cross-section random

35.021193

4

0.0000

Hausman test is used to test hypotheses in terms of bias or inconsistency of an estimator. For this specification test, H0 and H1 are:

H0: Cov(λ , x ) = 0

H1: Cov(λ , x ) ≠ 0

The result of Hausman Test illustrated the p-value is 0.0000 which is smaller than 0.01. Therefore, it is statistically significant at 1% of significant level. Therefore, the null hypothesis is rejected and concludes that the fixed effect is preferred.

Section 5 Summary and Conclusion

The purpose of this study is to investigate the predictive ability of the selected financial ratios on stock return in Malaysia specifically in plantation sector over the period from 2008 to 2012. Among the financial ratios, three commonly used financial ratios are included which is the dividend yield, firm size, earning per share (EPS) and book to market ratio. As a result, this study has provided evidence that financial ratios played a significant role in predicting stock return. In addition, the empirical findings also revealed that dividend yield, book to market ratio and firm size have significant relationship on stock return of Malaysia plantation sector among the financial ratios. However, the research finding indicate that the dividend yield has the strongest forecasting ability on stock return and it is in line with the past studies by Fama and French (1988) who found out that there is a strong predictive power of dividend yield on stock return. In summary, this study might not applicable to other region or other industry. Nevertheless, it has provided better information regarding the forecasting power of financial ratio on stock return. Therefore, effort shall be made to explore for further research in order to improve on previous work.

References:

Abgineh, M. (2013). The Investigation of the Relation between Changes in Financial Ratios with Changes in Stock Returns on the Tehran Stock Exchange. Journal of Basic and Applied Scientific Research, 3(2), 473-479.

Aono, K., & Iwaisako, T. (2010). Forecasting Japanese Stock Returns with Financial Ratios and Other Variables. Asia-Pacific Financial Markets, 18, 373–384.

Auret. C.J., & Sinclaire R.A. (2006). Book-to-market ratio and returns on the JSE.Investment Analysts Journal, 19, 31-38.

Banze, R. (1981). The relationship between return and market value of common stocks. Journal of Financial Economics , 9, 3-18.

Emamgholipour, M., Pouraghajan, A., Yadollahzadeh, T., Haghparast, M., & Shirsavar, A. (2013). The Effects of Performance Evaluation Market Ratios on the Stock Return: Evidence from the Tehran Stock Exchange. International Research Journal of Applied and Basic Sciences, 4 (3), 696-703.

Fama, E. F., & French, K. (1988). Dividend yields and expected stock return. Journal of Financial Economics, 22, 3-25.

Hodrick, R. (1992). Dividend yields and expected stock returns: alternative procedures for inference and measurement. Review of Financial Studies, 5, 357-386.

Hakkio, C. & Rush, M. (1991), Cointegration: how short is the long run?, Journal of International Money and Finance, 10, 571-581.

Kheradyar, S., Ibrahim, I., & Mat, N. F. (2011). Stock Return Predictability with Financial Ratios. International Journal of Trade, Economics and Finance, 2 (5), 391-396.

Kothari, S. P., & Shanken, J. (1997). Book-to-market, dividend yield, and expected market returns: a time series analysis. Journal of Financial Economics, 44, 169–203.

Lau, S.T., Lee, T.C. & McInish, T. H. (2002).Stock Returns and Beta, Firms Size, E/P, CF/P, Book to Market, and Sales Growth: Evidence from Singapore and Malaysia. Journal of Multinational Financial Management, 12, 207-222.

Lewellen, J. (2002). Predicting Returns with Financial Ratios. MIT Sloan School of Management. Working Paper 4374-02.

Lewellen, J. (2004). Predicting Returns with Financial Ratios. Journal of Financial Economics, 74, 209–235.

McManus, P.A. (2011). Introduction to regression models for panel data analysis. Retrieved from http://www.indiana.edu/~wim/docs/10_7_2011_slides.pdf

Reinganum, M.R. (1981). Misspecification of Capital Asset Pricing: Empirical Anomalies based on earning yield and market values. Journal of Financial Economics, 9(1), 19-46.

SAS Institute Inc. (2013). The model produce. Hausman specification test. Retrieved from http://support.sas.com/documentation/cdl/en/etsug/63348/HTML/default/viewer.htm#etsug_model_sect050.htm.

Stambaugh, R. (1999). Predictive regressions. Journal of Financial Economics 54, 375–421.

Stattman D. (1980). Book values and stock returns. The Chicago MBA: A Journal of Selected Papers, 4:25-45.

Courtney from Study Moose

Hi there, would you like to get such a paper? How about receiving a customized one? Check it out https://goo.gl/3TYhaX