Proceedings of 7th Asia-Pacific Business Research Conference
25 - 26 August 2014, Bayview Hotel, Singapore ISBN: 978-1-922069-58-0
The Relationship of Financial Performance and Macro
Economic on Stock Return in Indonesia
Karin Natasyah1 and Ana Noveria2
Most investors invest for anticipated future return, but those returns rarely can be
predicted precisely and also very volatile. Because of that, investors need to predict
the fluctuations that would occur through analysis. There are two factors that affect
the behavior and performance of stocks, internal factors and external factors. Internal
factors represented by the condition and position of the company, which in this
research is assessed by profitability ratio, such as earning per share (EPS), return on
assets (ROA), return on equity (ROE), and profit margin (PM). Then, external factors
represented by macro economic condition, which in this research are inflation, interest
rate, and exchange rate. This paper aims to know the influence of firm’s financial
performance and macro economic factors to stock return of manufacturing companies
that listed on Indonesia Stock Exchange (IDX) and also listed on Kompas 100 stock
index. The samples were obtained with judgment sampling method from
manufacturing companies that listed on Kompas 100 on the period of 2009-2013. As
a result, the sample of data is taken from 10 issuers. To determine which independent
variables that have significant influence on the stock return of the 10 companies,
multiple linear regression method is used.
The results show that interest rate and inflation have significant and positive
relationship with stock return. In the other hand, exchange rate has significant and
negative relationship with stock return. Then, EPS, ROA, ROE, and PM have no
significant relationship with stock return. Furthermore, interest rate has the strongest
influence among other variables toward stock return.
Keywords: Ratio Analysis, Stock Return, Macro Economic, Multiple Linear Regressions.
Field of Research: Finance
1. Introduction
Capital Markets acts as a connecting between investors and companies or government
institutions through long-term trading instruments such as stocks. In relation to stock
investing, investors choose the stocks of several companies that eligible to be selected
based on certain criteria. Most investors invest for anticipated future returns, but those
returns rarely can be predicted precisely. Because of the fact that the stocks expected
returns are very volatile, investors need to predict the fluctuations that would occur through
analysis to support their investment decision. There are two factors that affect the behavior
and performance of stocks, internal factors and external factors.
_______________________________________________________________________
1
Karin Natasyah, School of Business and Management, Institut Teknologi Bandung, Indonesia. Email:
karin.natasyah@sbm-itb.ac.id,
2
Ana Noveria, SE, MBA, School of Business and Management, Institut Teknologi Bandung, Indonesia.
Email: ana.noveria@sbm-itb.ac.id,
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Proceedings of 7th Asia-Pacific Business Research Conference
25 - 26 August 2014, Bayview Hotel, Singapore ISBN: 978-1-922069-58-0
Internal factors represented by the condition and position of the company, including growth
rate, ability to sell products, the level of competition. Then, external factors represented by
macro economic condition, including inflation, interest rates, currency fluctuations, global
competition, political factors. This discussion will be applied to the manufacturing sector
that includes basic and chemical industry, miscellaneous industry, and consumer goods
industry, with the consideration that the manufacturing industry is an industry that
dominates the companies listed on Indonesia Stock Exchange (IDX). The amount of
manufacturing companies that listed on Indonesia Stock Exchange until 2013 is 136 out of
the 486 companies (www.sahamok.com). This suggests that the role of the manufacturing
industry in Indonesia Stock Exchange occupy a dominant position.
This paper aims to know the influence of firm’s financial performance, that represented by
financial ratios, such as Earning per Share, Return on Assets, and Return on Equity, and
also macro economic factors, such as inflation rete, interest rate, and exchange rate, to
stock return of manufacturing companies that listed on Indonesia Stock Exchange (IDX)
and also listed on Kompas 100 stock index. The shares of the company that are listed on
the Kompas 100 is reflecting share price movements of the most actively traded and also
affect the state of the market, consisting of stocks with high liquidity and market
capitalization and good growth prospects and financial condition. Furthermore, another
purpose is to identify the dominant factor that influences the stock return changes of
companies in the manufacturing industry.
2. Literature Review
2.1 Investment
According to Bodie, Kane, and Marcus (2013) in Essentials of Investments, an investment
is the current commitment of money or other resources in the expectation of gaining
benefits in the future. Stocks and bonds are categorized as financial assets. While real
assets generate net income to the economy, financial assets are the allocation of income
among investors. Individuals can choose to make a purchase today or investing their
money for the future. When they choose to invest, they will place their money in financial
assets by purchasing any kind of securities. Then, when the securities is bought by
investors from the companies, the firm will use the money to pay for real assets, such as
equipment and inventory. As a result, the return that is generated for the investors is
actually come from the income produced by those real assets.
2.2 Stocks Analysis
According to Bhat (2007) on Security Analysis & Portfolio Management, there are two
methods that used to analyze securities and make investment decisions: fundamental
analysis and technical analysis. Fundamental analysis involves analyzing the
characteristics of a company in order to estimate its value. Fundamental analysts usually
start with a study of past earnings, examine the company’s financial statements, economic
analysis, evaluation of firm’s quality management, and also the prospects for the industry
(Bodie, Kane, Marcus, 2013). Based on Bhat (2007) on Security Analysis & Portfolio
Management, technical analysis is based on past information on prices and trading
volume, and it gives picture to investor about what lies ahead.
2.3 Return
A return is the income of an investment. It’s a change in the investment’s value over each
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25 - 26 August 2014, Bayview Hotel, Singapore ISBN: 978-1-922069-58-0
period and divided by the amount of the investment at the beginning period (Fabozzi and
Drake, 2009). Based on Chance & Brooks on Introduction to Derivatives and Risk
Management, In the case of stock, the return is the percentage change in price plus the
dividend yield. Then, stock return is usually measured by:
eturn
nding price
eginning price
eginning price
2.4 Macroeconomic
The macro economy is the environment in which all firms operate. The first step in
forecasting the performance of the broad market is to assess the status of the economy as
a whole. Some of the keys economic statistics used to describe the state of the macro
economy are:
2.4.1 Exchange Rate
The exchange rate is the rate at which domestic currency converted into foreign currency
(Bodie, Kane, Marcus, 2013). With a higher exchange rate, the world price of produced
goods will be low (Colander, 2013). As exchange rates fluctuate, the dollar value of goods
priced in foreign currency similarly fluctuates. Consequently, the cost of the imported raw
materials and equipment that needed by the companies is also increasing which will
increase the production cost. In other words, the depreciation of Rupiah has a negative
effect on the national economy, which ultimately will lower the company's stock return.
2.4.2 Inflation
Based on Bodie, Kane, Marcus (2013) on Essentials of Investments, inflation defined as
the rate at which the level of prices is rising. The high interest rate makes the price of
goods have a tendency to increase. The increase of goods price will also increase the cost
of production. As a result, it will decrease the sales, which will reduce the company’s
earnings. Then, will adversely affect the performance of the company as reflected by the
decline in the company’s stock price (Djayani, 1999).
2.4.3 Interest Rates
The high interest rates reduce the present value of future cash flows, so it’s reducing the
attractiveness of investment opportunities. In investors’ investment analysis, the level of
interest rates is the most important macroeconomic factor to be considered. In addition,
unexpected increases in rates are associated with stock market decline (Bodie, Kane,
Marcus, 2013)
2.5 Ratio Analysis
Ratio analysis relates income statement, balance sheet, and cash flow statement items to
one another. atio analysis gives information in evaluating a firm’s current position and
evaluating future performance (Hooke, 1998).
2.5.1 Earnings per Share
EPS ratio measures the earning capacity from the owner’s point of view and it is helpful in
determining the price of the equity share in the market place. It indicates the profits
available to the ordinary shareholders on a per share basis (Periasamy, 2009). Earning
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Proceedings of 7th Asia-Pacific Business Research Conference
25 - 26 August 2014, Bayview Hotel, Singapore ISBN: 978-1-922069-58-0
per share ratio can be calculated as:
arnings per hare
et income
um ers of shares outstanding
2.5.2 Return on Assets (ROA)
Return on assets (ROA) defined as a measure of profit per dollar of assets (Bodie, Kane,
Marcus, 2013). Firms with higher return on assets or equity should be better able to raise
money in security markets ecause they offer prospects for etter returns on the firm’s
investments. ROA is usually measured as:
et income
eturn on assets
Total assets
2.5.3 Return on Equity (ROE)
Return on equity (ROE) is a measure of how the stockholders fared during the year.
Because of benefiting shareholders is a goal, ROE becomes the measure of performance
(Ross, Westerfield, Jaffe, 2010). ROE is usually measured as:
et income
eturn on equity
Total equity
2.5.4 Profit Margin (PM)
Profit margin tells how much profit is generated from sales, so it makes profit margin
become a key ratio because the final goal of business is profit (Tracy, 2012). Based on
Ross, Westerfield, and Jaffe on Corporate Finance, an increase in profit margin will
increase the firm’s a ility to generate funds internally and then increase it sustaina le
growth.
rofit margin
et income
ales
3. The Methodology and Model
3.1 Sampling Methods
This study comprises a period of 5 years, starting from 2009 to 2013, and the units of
analysis include 10 companies that are listed on Indonesia Stock Exchange (IDX) and also
listed on Kompas 100 stock index. The method used in this paper is Judgment Sampling
method, which allows the author to determine the consideration and certain categories for
sampling. There are two criteria and categories established by the author. First, the
company should be manufacturing companies that listed on Indonesia Stock Exchange
(IDX) and also listed on Kompas 100 consistently over a period of 2009-2013. Second, the
companies are not delisting on the observation period, which is 2009-2013. Therefore, this
paper employs a data set of 10 companies that are selected based on those criteria.
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Proceedings of 7th Asia-Pacific Business Research Conference
25 - 26 August 2014, Bayview Hotel, Singapore ISBN: 978-1-922069-58-0
Those firms are:
Table 3.1 List of Firms Sample
No.
Company Name
Stock Code
1
Astra International Tbk
ASII
2
Charoen Pokhpand Tbk
CPIN
3
Gudang Garam Tbk
GGRM
4
Gajah Tunggal Tbk
GJTL
5
Indofood Sukses Makmur Tbk
INDF
6
Indocement Tunggal Prakasa Tbk
INTP
7
Kalbe Farma Tbk
KLBF
8
Holcim Indonesia Tbk
SMCB
9
Semen Indonesia Tbk
SMGR
10
Unilever Indonesia Tbk
UNVR
3.2 Data Description
Data used in this research are secondary data. The dependent variable is stock return that
is calculated using the percentage change in closing price each day every year. Then, the
daily percentage change is averaged each year to get the average stock return each year
from 2009-2013. There are two kinds of independent variable in this paper, which are
financial ratio that represent company performance, and macro economic factor. For the
financial ratio, the author use profita ility ratio that provides the indicators of a firm’s
overall performance, which are Earning per Share (EPS), Return on Equity (ROE), Return
on Assets (ROA), and Profit Margin (PM). Then, the author use inflation rate, interest rate,
and exchange rate for the macro economic factors.
The stock price data is obtained from www.finance.yahoo.com and the company’s financial
ratios that o tained from company’s annual report are from the pu lic site of each
company. Then, data that is related to macro economic factors such as, inflation, interest
rate, and exchange rate are obtained from Statistik Ekonomi dan Keuangan Indonesia
(SEKI) that published by Bank Indonesia, BPS (Badan Pusat Statistik), and from
www.data.worldbank.org.
3.3 Data Analysis
For studying the relationship of company performance and macro economic on stock
return, the data analysis method in this paper is using multiple linear regression analysis.
Multiple linear regression attempts to model the relationship between two or more
explanatory variables (www.stat.yale.edu). Because in this study there are several
independent variables, such as inflation, interest rate, exchange rate, Earning per Share
(EPS), Return on Assets (ROA), Return on Equity (ROE), and Profit Margin (PM), multiple
regression analysis is useful to determine which independent variables that have
significant influence on the dependent variable, which in this paper is stock return. In
addition, multiple regression analysis attempts to study the dependence of one variable on
more than one explanatory variable.
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Proceedings of 7th Asia-Pacific Business Research Conference
25 - 26 August 2014, Bayview Hotel, Singapore ISBN: 978-1-922069-58-0
Before running the multiple linear regression, classical assumption test is the statistical
requirements that must be met. These were required to show that the technique, ordinary
least squares (OLS), had some desirable properties, and also the hypothesis tests could
validly be conducted (Brooks, 2008). The assumptions are needed to make the OLS
procedure BLUE (Best Linear Unbiased Estimator) (Wang & Jain, 2003). The ordinary
least squares estimator will be optimal only in standard situation. If one or more
assumptions do not hold, the standard OLS estimation is no longer reliable (Palmrich,
2009). The classical assumption tests that will be use in this research are normality test,
auto-correlation test, multicollinearity test, and heteroscedasticity test.
Normality test is to see whether the residual values are normally distributed or not using
Kolmogorov-Smirnov test. Having a normal distributed data is the characteristic of a good
regression model (Brooks, 2008). In cross-sectional, data from one group may reflect the
characteristics of the other groups, so auto-correlation test must be employed, using
Durbin-Watson test for recognizing the autocorrelation. Then, adding and removing a
variable from a regression would cause the values of the coefficients on the other
variables to change, which called multicollinearity. Multicollinearity test is used to see
whether there is a high correlation between variables in multiple linear regression model.
Furthermore, regression models that meet the requirements are where there is equality of
residuals’ variance of one observation to another observation or called homocedasticity.
Heterocsedasticity is the unequal spread. Heteroscedasticity test is to see whether there is
inequality residuals’ variance of the o servations to other o servations (Gujarati, 2003).
To test the hypothesis, the author employed F-test and t-test. F test is to test the joint
hypothesis. Based on Wang and Jain on Regression Analysis, F test is a statistical test of
significance of the overall relationship between Y and X. The F test is useful in testing
multiple regression models, which include more than one independent variable. Then, t
test is used to test a hypothesis about any individual partial regression coefficient. The t
test can tell the significance of each coefficient.
4.The Findings
4.1 Classical Assumption Test
4.1.1 Normality Test
Table 4.1 Normality Test Result
One-Sample Kolmogorov-Smirnov Test
N
Normal Parameters a,b
Most Extreme
Dif f erences
Mean
Std. Dev iat ion
Absolute
Positiv e
Negativ e
Kolmogorov -Smirnov Z
Asy mp. Sig. (2-tailed)
Unstandardiz
ed Residual
40
.0000000
.00178480
.084
.078
-.084
.530
.942
a. Test distribution is Normal.
b. Calculated f rom data.
Based on the table above, the value of Asymp. Sig obtained from Kolmogorov-Smirnov
test is 0.942. The data can pass the test if the significance value is more than the alfa
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Proceedings of 7th Asia-Pacific Business Research Conference
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value, which is 0.05. So it can be concluded that the data is distributed normally because it
passed the Kolmogorov-Smirnov test.
4.1.2 Multicollinearity test
Table 4.2 Multicollinearity Test
Result a
Coeffici ents
Model
1
EPS
ROA
ROE
PM
Inf lasi
Interest rate
Exchange Rate
Collinearity Statistics
Tolerance
VIF
.930
1.076
.141
7.107
.188
5.328
.510
1.960
.933
1.072
.599
1.670
.632
1.584
a. Dependent Variable: Ret urn
Based on the table above, the VIF value of each variable is more than 10 and also the
tolerance value of each varia le is more than 0.1. o it can e concluded that there’s no
multicollinearity on the data.
Table 4.3 Auto-Correlation Test Result
4.1.3 Auto-correlation test
Model Summaryb
Model
1
DurbinWat son
1.896
b. Dependent Variable: Return
Based on the table above, the value of DW is 1.896. With the sample size of 50 (n=50), 
0.05, and the num er of independent varia les of 7 (k 7), it’s o tained that the critical
value is dL = 1.286 dan dU =1.875. Based on the criteria as stated before, the DW value is
dU (1.875) < DW (1.896) < 4-dU (2.125). So it can be concluded that there is no is autocorrelation on the data.
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4.1.4 Heteroscedasticity Test
Table 4.5 Heteroscedasticity Test Result
Correlati ons
Spearman's rho
EPS
Correlation Coef f icient
Sig. (2-tailed)
N
Correlation Coef f icient
Sig. (2-tailed)
N
Correlation Coef f icient
Sig. (2-tailed)
N
Correlation Coef f icient
Sig. (2-tailed)
N
Correlation Coef f icient
Sig. (2-tailed)
N
Correlation Coef f icient
Sig. (2-tailed)
N
Correlation Coef f icient
Sig. (2-tailed)
N
ROA
ROE
PM
Inf lasi
Interest rate
Exchange Rate
Unstandardiz
ed Residual
-.019
.905
40
.112
.491
40
.105
.518
40
.015
.928
40
.041
.803
40
-.089
.585
40
.045
.785
40
Based on the table above, p-value (Sig) of all independent variable show a higher value
than 0.05, so it can be concluded that there is no heteroscedasticity on the regression
model.
4.2 Multiple correlation and coefficient of determination
Table 4.6 Multiple Correlation and Coefficient of Determination
Model Summary
Model
1
R
.795a
R Square
.632
Adjusted
R Square
.551
St d. Error of
the Estimate
.00197
a. Predictors: (Constant), Exchange Rat e, ROE, EPS,
Inf lasi, PM, Interest rate, ROA
The R-value of 0.795 means there is a strong relationship between seven dependent
variables and stock return. The coefficient of determination, R-square, of 0.632 means that
the EPS, ROA, ROE, PM, inflation, interest rate, and exchange rate has a 63.2% influence
on stock return. It means that the influence from other factor is 36.8%, which is the
variable outside EPS, ROA, ROE, PM, inflation, interest rate, and exchange rate.
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4.2.3 Partial Effect Analysis
Partial effect analysis is used to assess the strength of the relationship between
independent variable to the dependent variable. The partial effect analysis from the SPSS
software is as follow:
Variable
X1
Table 4.7 Partial Effect
Standardized
Correlations
Partial
Coefficients
Effect Value
Beta
Zero-order
0.046
-0.083
-0.004
Partial
Effect Value
(%)
-0.4%
X2
X3
X4
X5
X6
-0.289
0.237
-0.079
-0.275
0.857
-0.011
0.004
-0.089
-0.416
0.632
0.003
0.001
0.007
0.114
0.541
0.3%
0.1%
0.7%
11.4%
54.1%
X7
-0.464
0.067
-0.031
-3.1%
0.632
63.2%
Total
The partial effect value is obtained by multiplying standardized coefficient beta by zeroorder. Based on the table above, the effect of EPS (X1) toward stock return (Y) is -0.4%.
Then, the effect of ROA (X2) toward stock return (Y) is 0.3%. The effect of ROE (X3)
toward stock return (Y) is 0.1%. The effect of PM (X4) toward stock return (Y) is 0.7%. The
effect of inflation (X5) toward stock return (Y) is 11.4%. The effect of interest rate (X6)
toward stock return (Y) is 54.1%. The effect of exchange rate (X7) toward stock return (Y)
is -3.1%. So, the total effect of EPS (X1), ROA (X2), ROE (X3), PM (X4), inflation (X5),
interest rate (X6), and exchange Rate (X7) toward stock return (Y) is 63.2%, this also
shown on coefficient of determination value.
4.3 Hypothesis Testing
4.3.1 Regression Coefficient Simultaneously (F-test)
H0 : EPS, ROA, ROE, PM, inflation, interest rate, and exchange rate simultaneously do
not have significant relationship with stock return
H1 : EPS, ROA, ROE, PM, inflation, interest rate, and exchange rate simultaneously have
a significant relationship with stock return
To test the hypothesis above, the author used statistical test called F-Test that obtained
through ANOVA table as follow:
Table 4.8 F-Test Result
ANOVAb
Model
1
Regression
Residual
Total
Sum of
Squares
.000
.000
.000
df
7
42
49
Mean Square
.000
.000
F
3.910
Sig.
.002a
a. Predictors: (Const ant), Exchange Rate, ROE, EPS, Inf lasi, PM, Interest rate, ROA
b. Dependent Variable: Return
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Based on table above, the value of F-result is 3.910, which will be compared with the value
of F-table. The value of F-table is 2.237, with α = 0.05 and degree of freedom = 42.
Because the F-result is higher than F-table, it can be concluded in level of error = 5% to
reject H0 and accept H1. That means that in 5% level of error, it can be concluded that
EPS, ROA, ROE, PM, inflation, interest rate, and exchange rate simultaneously have
significant relationship to stock return on manufacturing companies that listed on Indonesia
Stock Exchange and also listed on Kompas 100 stock index during 2009-2013.
4.3.2 Regression Coefficient Partially (T-test)
Table 4.9 T-Test Result
Coeffici entsa
Model
1
(Constant)
EPS
ROA
ROE
PM
Inf lasi
Interest rate
Exchange Rate
Unstandardized
Coef f icients
B
Std. Error
-.006
.006
2.25E-007
.000
-.008
.008
.003
.003
-.004
.007
.000
.000
.513
.083
-2.2E-006
.000
Standardized
Coef f icients
Beta
.046
-.289
.237
-.079
-.275
.857
-.464
t
-1.047
.414
-1.012
.955
-.526
-2.471
6.179
-3.436
Sig.
.303
.682
.319
.347
.602
.019
.000
.002
Correlatio
ns
Zero-order
-.083
-.011
.004
-.089
-.416
.632
.067
a. Dependent Variable: Ret urn
Statistical value for T-test based on the table above is compared with the value from Ttable to show whether the independent variable has significant influence or not. Then, the
criteria to decide whether there is influence on the stock return is:
1. If t result > t table or t result < -t table, then H0 is rejected
2. If t result < t table or t result > -t table, then H0 is accepted
The hypothesis:
 Hypothesis of earning per share
H0 : β1 = 0 Earning per share has no influence on stock return
H1 : β1 ≠ 0 Earning per share has influence on stock return
 Hypothesis of return on assets
H0 : β1 = 0 Return on assets has no influence on stock return
H1 : β1 ≠ 0 Return on assets has influence on stock return
 Hypothesis of return on equity
H0 : β1 = 0 Return on equity has no influence on stock return
H1 : β1 ≠ 0 Return on equity has influence on stock return
 Hypothesis of profit margin
H0 : β1 = 0 Profit margin has no influence on stock return
H1 : β1 ≠ 0 Profit margin has influence on stock return
 Hypothesis of inflation
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H0 : β1 = 0 Inflation has no influence on stock return
H1 : β1 ≠ 0 Inflation has influence on stock return
 Hypothesis of interest rate
H0 : β1 = 0 Interest rate has no influence on stock return
H1 : β1 ≠ 0 Interest rate has influence on stock return
 Hypothesis of exchange rate

H0 : β1 = 0 Exchange rate has no influence on stock return
H1 : β1 ≠ 0 Exchange rate has influence on stock return
Table 4.10 T-Result and T-Table Value
Based on the table above, it can be concluded that inflation, interest rate, and exchange
rate has relationship with stock return on manufacturing company that listed on Indonesia
Stock Exchange and Kompas 100 stock index during the period of 2009-2013. EPS, ROA,
ROE and PM has no relationship with stock return.
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4.4 Regression Estimation
To examine the effect of independent variables on the dependent variable, which in this
study is stock return, the author used multiple linear regression with the equation as follow:
0
1 1
2 2
3 3
4 4
5 5
6 6
7 7
Variable
t-result
df
t-table
Sig.
Statement
Result
EPS
0,414
42
2,037
0,682
Ho
accepted
Not
significant
ROA
-1,012
42
2,037
0,319
Ho
accepted
Not
significant
ROE
0,955
42
2,037
0,347
Ho
accepted
Not
significant
PM
-0,526
42
2,037
0,602
Ho
accepted
Not
significant
Inflation
-2,471
42
2,037
0,019
Ho
rejected
Significant
Interest rate
6,179
42
2,037
0,000
Ho
rejected
Significant
Exchange
rate
-3,436
42
2,037
0,002
Ho
rejected
Significant
Where:
Y
= Return
X1
= EPS
X2
= ROA
X3
= ROE
X4
= PM
X5
= Inflation
X6
= Interest rate
X7
= Exchange Rate
a
= Constant
= Regression Coefficient
i
The result of multiple regression analysis from SPSS software is as follow:
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Table 4.11 Multiple Regression Analysis
Variable
Regression
Coefficient
Std. Error
t
Sig.
(Constant)
-0.006
0.006
-1.047
0.303
X1
0.0000002
0.0000005
0.414
0.682
X2
-0.008
0.008
-1.012
0.319
X3
0.003
0.003
0.955
0.347
X4
-0.004
0.007
-0.526
0.602
X5
0.0003636
0.0001471
-2.471
0.019
X6
0.513
0.083
6.179
0.000
X7
-0.0000022
0.0000006
-3.436
0.002
Based on the result on the table above, the multiple regression equation is obtained as
follow:
Y = -0.006 + 0.0000002 X1 - 0.008 X2 + 0.003 X3 - 0.004 X4 + 0.0003636 X5 + 0.513 X6 0.0000022 X7
From the multiple regression equation a ove, it’s o tained that the constant value is 0.006. it means that if value of independent variable is zero, then stock return (Y) will have
the value of -0.006. The sign on the coefficient regression of independent variable shows
the correlation of that variable with the return. So, the coefficient regression for EPS, ROE,
inflation, and interest rate is positive, which means there is a positive correlation with the
stock return. Then, the coefficient regression for ROA, PM, and interest rate is negative,
which means there is a negative correlation with the stock return.
5. Summary and Conclusions
Based on the research and data analysis, interest rate has the highest correlation with
stock return. This can be shown from the highest partial effect value compared with other
variable with the percentage of 54.1%, which means that every one-unit change in interest
rate will influence the return as much as 54.1%. Then, it can be concluded that stock
return is influenced more by interest rate rather than other variables.
The value of R-square that resulted from the multiple regression model is 0.632 or 63.2%.
It indicated that the independent variable, which are earning per share, return on assets,
return on equity, profit margin, inflation, interest rate, and exchange rate simultaneously
affect to stock return for 63.2%, while the rest, 36.8%, is affected by other factor outside
EPS, ROA, ROE, PM, inflation, interest rate, and exchange rate, that is not studied and
discussed in this research.
The result of F-test show that H0 is rejected. That means that there is significant
simultaneous effect of independent variables toward stock return. The result of T-test for
testing the partial effect of independent variable to stock return show that H0 is accepted
for earning per share, return on assets, return on equity, and profit margin. It means that
profitability ratios do not have significant relationship to the stock return. Furthermore, H0 is
rejected for inflation, interest rate, and exchange rate, which mean that macro economic
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Proceedings of 7th Asia-Pacific Business Research Conference
25 - 26 August 2014, Bayview Hotel, Singapore ISBN: 978-1-922069-58-0
factors have significant relationship to the stock return in manufacturing companies that
listed on Indonesia Stock Exchange and also listed on Kompas 100 stock index during the
period of 2009-2013.
The regression function resulted in this result as follow:
Stock return = -0.006 + 0.0000002 EPS - 0.008 ROA + 0.003 ROE - 0.004 PM +
0.0003636 Inflation + 0.513 Interest Rate - 0.0000022 Exchange Rate
The equation shows the relationship between all variables and stock return. It means that
it shows how much stock return change as the variables change. It shows earning per
share, return on equity, inflation, and interest rate has positive correlation to stock return. It
means if earning per share increase, stock return will act accordingly. While return on
assets, profit margin, and exchange rate has negative correlation with stock return.
As a result, interest rate and inflation have significant and positive relationship with stock
return. Then, exchange rate has significant and negative relationship with stock return.
While earning per share (EPS), return on assets (ROA), return on equity (ROE), and profit
margin (PM) has no significant relationship with stock return. Then, it can be concluded
that the only significant factors are macro economic factors, while profitability ratios has no
significant relationship with stock return of manufacturing company that listed on Indonesia
Stock Exchange and Kompas 100 stock index during the period of 2009-2013.
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