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INFORMATIVENESS OF EARNINGS AND CASH FLOWS: EVIDENCE
IN INDONESIA, MALAYSIA, AND THAILAND BANKING INDUSTRY
Elisa Tjhoa, University of Indonesia
Ancella Anitawati Hermawan, University of Indonesia
Abstract
Financial statements’ information, particulary net income and cash flows from
operations has been widely used by investors as one of the basis in making
investment decisions. Interests are the main source of income in the banking
industry, and therefore the information of which are considered to have a
significant role for the investors. The objective of this study is to examine the
informativeness of earnings, cash flows from operations, and net interest income
in the banking industry in three South East Asian countries, i.e. Indonesia,
Malaysia, and Thailand. The hypothesis testing is carried out using multiple
regression method with the sample of publicly listed Banks in each country during
the year of 2006 to 2010. The empirical results show that net income of banking
industry is informative in Indonesia and Thailand, but not in Malaysia. In
Malaysia, cash flows from operations is more informative, similar to Thailand. In
term of interest icome, Malaysia and Thailand indicates that this information is
informative, but not in Indonesia. In Thailand, the cash flows for interest is also
informative.
Key words : earnings response coefficient, net interest income, cash flows from
operations, cash flows for interest, bank.
2
1. Introduction
The information about the company or the market condition is very
crucial for capital market investors in making their investment decisions. Optimal
decisions need high quality information, i.e. relevant and reliable information.
One source of information that is available for the investors to evaluate the
company’s prospective performance is the income statement and cash flows
statements. Bruns dan Merchant (1990) state that the cash flows statement provide
better information, since the accrual basis used in the income statements allows
the company’s management to manage the earnings reported. But Cheng et al.
(1997) conclude that net income still have value relevance, and cash flows from
operations contribute an incremental value relevance on top of the net income.
The quality of earnings reported in the financial stements is considered
high if it can be a valid base to predict to future company’s performace, but this
quality is often difficult to measure (Dechow et al., 2010). One approach to
measure the earnings quality is based on the earnings response coefficient (ERC).
Investors perceptions about the quality of earnings is captured by how the
investors react to the earnings information in the capital market. Teoh and Wong
(1993) shows that investors are willing to pay a higher price for earnings of "high
quality" because the high-quality earnings are seen as sustainable profits.
Therefore, earnings quality is measured based on the response of investors on the
information content of accounting earnings (informativeness of accounting
earnings). The magnitude of the change of abnormal retuns associated with the
change in unexpected earnings is called the earnings response coefficient (ERC).
The ERC will be high if investors perceive the informativeness of earning is high,
meaning that the earnings quality is high.
Banks have a unique business process with its intermediaries roles in the
financial market. Eventhough the industry is very highly regulated due to the
nature of the business, the business risk of banking industry is relatively high.
The standard of financial reporting format is different from other industries to be
able to present the relevant business performance results. Therefore, it is
3
interesting to know which information regarding the result of the operating
performance that represents higher quality information from the investors’
perspective. As one of the emerging countries, Indonesian economy is still rely
more on banks for the financial system than the capital market. The banking
industry has shown a high growth rate in the past two decades. The performance
of the banks stock price in the market is usually better than other companies,
therefore banks stocks are usually taken as the underlying asset of a mutual fund.
But some Indonesian banks have also experienced financial difficulties, which
ended up with merger or acquisition by other banks, or declared bankruptcy. In
order to evaluate the bank’s prospect in profitability and risks, investors may have
different perception for every information item in the financial statement
depending on their perceived quality of such information. This study examines
how the investor’s response for the information of earnings, cash flows from
operations, and net interest income reported by banks in Indonesia. In addition, to
be able to understand how the quality of banks financial report in Indonesia
compared to other countries, the study includes the banking industry in Malaysia
and Thailand. As the member of South East Asian Nations, the three countries in
this study assumed to have some similarities and differences in the
macroeconomics conditions, government regulations, and financial reporting
standards, therefore comparing among those countries for this study will provide
some more insight about the banking industry financial reporting quality.
2. Literature Review and Hypothesis Development
Research and empirical studies on the effect of earings on stock returns
has been done many times before. Ball dan Brown (1986) are one of the pioneers
in the research, and found that there were movements in stock price around the
company’s accounting income announcements. Kothari (2001) also finds strong
correlations between the stock price movements with the company’s income
movements. Dastgir et al. (2004) show that the correlation between net income
and stock returns is stronger than the correlation between cash flows and stock
returns. But in a research on effect of SFAS No. 95 Statement of Cash Flows on
4
stock price movements, Cheng et al. (1997) find that both net income and cash
flows from operations have positive and significant impact on stock returns.
Chen (2009) concludes that both accounting income and cash flows from
operations has significant effect on price movements. But the effect of accounting
income is stronger in predicting stock returns in longer period, while the cash
flows from operation is stringer in predicting stock returns in shorter period.
Dastgir et al. (2009) performed a research to see the effect of income statements
and cash flows statements informations on the stock returns for Tehran Stock
Exchange, using the components of the reports as independent variables of the
research. The components of income statements used are gross profit, operating
income, income before tax and net income. While the cash flows statements
componenets used are cash flows from operating activities, cash flows from
investing activities and cash flows from financing activities. The result of the
study showed that the component of income statements with the most significant
effect on stock returns is net income, whereas the component of the cash flows
statements with the most significant effect on stock returns is cash flows from
investing activities.
The quality of earnings refers to the relevance of earnings in measuring a
company’s performance (Subramanyam and Wild, 2009). Besides, the quality of
earnings also can be defined as the conservatism level of reporting by a company,
in which the company with higher price to earnings ratio will indicate a higher
quality of earnings. Statement of Financial Accounting Concepts No. 1 (SFAC
No. 1) stated that financial reporting should provide information regarding the
company’s financial performance in certain period. Dechow et al. (2010) defined
the quality of earnings as earnings that provide information regarding a company;s
financial performance, which could influence the decision made by a decision
maker.
Earnings response coefficient could be defined as the measure of abnormal
market return of a stock as the response of unexpected component of earnings
announced by the company (Scott, 2009). Ambarwati (2008) describes that
5
earnings response coefficient will be based in the investor’s expectation on the
earnings before its announcement. Approaching the earnings announcement date,
the information obtained and gathered by investors will also increase. If the actual
earnings is higher than the investor’s expectation, then there would be good news,
and investors will decide to buy the shares. On the other hand, if the actual
earnings is lower than what was expected, there would be bad news, and the
investors will decide to sell the shares.
Earnings response coefficient will be different for each company, and is
influenced by a number of factors. Biddle and Seow (1991) and Ahmed (1994)
show that earnings response coefficient will be significantly influenced by the
company’s characteristics. Teoh and Wong (1993) state that the auditors also
influence the company’s earnings response coefficient. Their study show that the
auditor’s quality, or auditor with bigger scale of reputation will be more reliable,
which is proved by the higher earnings response coefficient in companies audited
by Big Six audit firms. This is caused by the perception of the investor that the
financial reports audited by the big six audit firms are less vulnerable to
misstatements compared to those who were audited by non Big Six audit firms.
Study of earnings response coefficient on banking sector has been done by
Ariff dan Cheng (2011) for Asia Pacific countries such as Australia, South Korea,
Malaysia, and Thailand. In the study, in addition to observe the effect of total
earnings information on stock price movements, they also examine the effect of
disaggregated non-interest fee income information.This study finds that the total
earnings movement in the financial reports have a positive and significant effect
on stock price movement in all four countries. As for the effect of the change in
disaggregated non-interest fee income to the stock price, this study shows a
positive effect in Australia, South Korea, and Malaysia, but a negative effect in
Thailand. They also find that there is no association between the level of
disaggregated non-interest fee income and stock price movement.
Based on the study of Ariff dan Cheng (2011), the first hypotheses in this
study is:
6
H1a : Unexpected earnings is positively associated with cumulative abnormal
return
Interest revenue and expense are the results of main operational activities
in banks. Therefore the financial statements users often reflect the operational
performance of banks for the net interest income achieved during a ertain period.
Based on the above, the second hypotheses of this study is:
H2a : Unexpected net interest income is positively associated with cumulative
abnormal returns.
This study would also observe the quality of components on cash flows
statements, so the third and fourth hypotheses are:
H3a : Unexpected cash flows from operations is positively associated with
cumulative abnormal returns.
H4a : Unexpected net cash flows from interest is positively associated with
cumulative abnormal returns.
3. Research Method
3.1 Data and Sample
The sample of this study are publicly listed banks in the stock exchange of
Indonesia, Malaysia, and Thailand during the period of 2006 to 2010. Table 1
shows that total sample is 30 banks, therefore the total observation for five-year
period for all countries is 150 observations. The list of the banks used as the
sample in this study is presented in the appendix.
The data used are from the companies annual report taken from the stock
exchange or company’s website, and also from Yahoo finance and Bloomberg..
7
Table 1 Sample Determination
No. Sample Criteria Indonesia Malaysia Thailand
1 Number of Banks listed on the
stock exchange as of May
2012.
42 27 47
2 Banks that are listed during
the whole period of study
(2006-2010)
(10) 0 (2)
3 Banks with negative equity (1) 0 0
4 Banks with incomplete data (6) 0 0
5 Total sample 13 8 9
3.2.Research Model
The test on the above hypotheses are performed using the multiple
regression method, that is the effect of unexpected earnings and unexpected cash
flows from operations, and also unexpected net interest earnings and unexpected
net cash flows from interests on stock returns.
Hypotheses 1 to 4 will be tested using the following 2 models :
= + . + . + . + . +
. + . +
= + . + . + . + . +
. + . +
Where:
= cumulative abnormal return stock company i in year t
= unexpected earnings company i in year t
= unexpected cash flows from operations comapany i in year t
= unexpected net interest earnings company i in year t
= unexpected net cash flows from interest company i in year t
8
= risk of company i measured by beta in year t
= loan to deposit ratio of company i in year t
= price to book value (PBV) ratio of company i in year t
= size of company i measured by outstanding shares times closing
price in year t
3.3 Variable Measurements
The dependent variable in this study is the company’s market adjusted
stock return proxied by the cumulative abnormal market adjusted return. Stock
price data used are the weekly closing price of public companues in banking
industry and weekly closing rice of the composite index on each country
observed. For companies with reporting period ended 31 December, the stock
return period used are from 1 April 2006 to 31 March 2011. For companies with
reporting period ended 31 March, the stock return period used are from 1 July
2006 to 30 June 2011. While for companies with reporting period ended 30 June,
the stock return period used are from 1 October 2006 to 30 September 2011.
( )
( )
( )
( )
From the above we could get weekly market adjusted return which were
cumulated for one year to obtain cumulative abnormal return which is the
dependent variable in this study.
∑
Where:
= stock return of company i in week w
= market return in week w
= stock price of company i in week w
9
( ) = stock price of company i in week (w-1)
= stock exchange index in week w
( ) = stock exchange index in week (w-1)
= market adjusted return company i in week w
= cumulative abnormal return company i in year t
The independent main variables in this study comprised of unexpected
earnings, unexpected interest earnings, unexpected cash flows from operations
and unexpected cash flows from interests.
Proxy for unexpected earnings was calculated as follows:
( )
( )
Proxy for unexpected net interest earnings was calculated as follows:
( )
( )
Where:
= proxy unexpected earnings company i in year t
= earnings per share company i in year t
( ) = stock price company i in year (t-1)
= proxy unexpected net interest earnings company i in year t
= net interest earnings per share company i in year t
In this study, the proxy for unexpected cash flows from operations was
calculated as follows:
1
0
( )
( )
While the calculation for the proxy of unexpected cash flows from
interests will be as follows:
( )
( )
Where:
= proxy unexpected cash flows from operations company i in year t
= cash flows from operations per share company i in year t
= proxy unexpected net cash flows from interest company i in year
t
= net cash flows from interest per share company i in year t
The control variables includes:
Loan to Debt Ratio
Based on Mulyono (1995:101), the loan deposit ratio is the ratio that
compares funds distributed to the society as loans with the funds gathered from
the market and its own capital. The ratio describes the ability of the bank to repay
the depositor using the loans as its source of liquidity. The higher the ratio, the
lower the liquidity of the bank (Dendawijaya, 2000:118). The loan to deposit ratio
is calculated as follows:
1
1
Company’s Risk
The research by Murwaningsari dan Rachmanto (2011) showed that a
company’s risk can significantly influence the stock return. The company’s risk is
reflected in the company’s beta obtained by performing regression on weekly
stock return with the market return for each company observed. The beta value is
obtained using the following formula (Bodie et al., 2008):
Where:
= stock return company i for period t
= market return for period t
= intercept of regression between stock and market return
= slope of regression between stock and market return which
shows the response of stock return to movement of market price
regresi
Growth Opportunity
Senthilkumar (2009) and Tresnaningsih (2007) in their research proxied
the company’s growth opportunity using market price to book equity ratio. The
ratio is calculated as follows:
Company’s Size
Quiroz and Timmermann (1999) stated that the stock return is also
influenced by the size of the company, whereas the smaller the size of the
company, the more the chance to have asymmetric information which can
influence the company’s stock return.Based on the study of Siregar and Utama
(2008), the size of the company can be proxied by the market value of equity in
1
2
end of year, which is obtained by multiplying outstanding shares with closing
price at end of year.
4. Results
4.1 Descriptive Statistics
Table 2 shows that on average, the value of cumulative abnormal return CAR for
Indonesian banks in the sample is higher than the other two countries. Higher
return also means higher risks, and it is represented by higher standard deviation
Table 2 Descriptive Statistics
MINIMUM MAXIMUM
MEAN STANDARD DEVIATION
Indonesia Malaysia Thailand Indonesia Malaysia Thailand
Indonesia Malaysia Thailand Indonesia Malaysia Thailand
CAR -0,75 -0,34 -1,03 2,94 0,94 1,16 0,28 0,17 0,05 0,63 0,30 0,38
UE -0,09 -0,09 -1,28 0,22 0,12 4,02 0,02 0,02 0,08 0,05 0,04 0,65
UNIE -2,64 -0,13 -3,08 0,46 0,14 0,48 -0,05 0,01 -0,07 0,47 0,04 0,48
UCFO -2,21 -1,96 -11,10 2,04 2,63 2,35 0,03 0,08 -0,26 0,86 0,91 2,02
UNCFI -0,31 -0,13 -2,90 0,28 0,14 1,43 0,03 0,01 -0,04 0,09 0,04 0,50
RISK -0,02 0,69 0,40 1,30 1,53 1,25 0,71 1,06 0,84 0,30 0,18 0,20
LDR 0,35 0,50 0,57 1,18 0,88 1,59 0,67 0,71 0,98 0,17 0,10 0,18
GROWTH 0,56 0,46 0,32 6,07 3,73 4,37 1,97 1,60 1,42 1,03 0,81 0,79
SIZE (in
million LC) 172.638 2.017 1.557 157.792.064 66.855 351.136
25.060.550 18.622 110.419 33.162.458 17.176 93.343
Number of observation: 150
CAR = cumulative annual weekly abnormal return, UE = unexpected earnings, UNIE = unexpected net interest earnings, UCFO = unexpected cash flows from
operations, UNCFI = unexpected net cash flows from interests, RISK = company’s beta, LDR = loan to deposit ratio, GROWTH = company’s growth opportunity
measured by price to book value, SIZE = company’s size measured by the market value of equity at the end of fiscal year in local currency
of Indonesian banks in the sample compared to Malaysia and Thailand. Banks.
This reflects that the Indonesian banks have higher risks than Malaysian and
Thailand banks..
For the value of the UE, Thailand banks which are included in the sample
have the highest average UE compared to the other two countries. This suggests
that investors in Thailand have more uncertainties which are not able to be
identified beforehand and therefore these factors are not determined in the
expected earnings.
UNIE value in Indonesia and Thailand on average is negative, which
indicates that there is a decline in net interest income during the period of 2006-
2010. This is due to a decrease in interest rates in the two countries during that
period. As for Malaysia the average net interest income positive, so maybe the
situastion in Malaysia is somewhat different. In addition, Thailand banks average
UCFO and UNCFI are also negative, which reflects that their economic condition
may not as good as the other two countries. In term of LDR, Thailand banks have
the highest ratio compared to Indonesia and Malaysia. But in general, LDR from
all countries in the sample shows that the banks have conducted the intermediaries
role quite well.
The correlation between each variables used in the research model is
presented in the appendix 2.
4.2. Regression Result
The regression results are presented in table 3 and 4 and the hypothesis testing
analysis is discussed in the following section.
4,2,1 Informativeness of Net Income
Test on hypotheses 1a is performed to gain knowledge on quality of net
income based on the investor’s perspective, where the coefficient of the test will
indicate the quality on informativeness of net inceome to the investors.
Corresponds to the the study by Ariff and Cheng (2011) and other previous
researches regarding the effect of net income on stock price movements, the
results for Indonesia and Thailand showed positive signs, with p-value
Table 3: Regression Result Model 1
= + . + . + . + . + . + . +
Indonesia Malaysia Thailand
Variable
Exp
Sign
Unstd
Coef t-Stat Sig. Exp
Sign
Unstd
Coef t-Stat Sig. Exp
Sign
Unstd
Coef t-Stat Sig.
B
(Constant) 1,568 1,649 0,052* 0,658 0,806 0,213 -0,793 -0,905 0,186
UE + 2,973 1,884 0,032** + 0,225 0,262 0,397 + 0,430 3,990 0,000***
UCFO + -0,088 -1,106 0,137 + 0,079 1,893 0,034** + 0,066 1,521 0,069*
RISK + 0,488 1,760 0,042** + -0,484 -1,832 0,038** + 0,170 0,625 0,268
LDR + 0,808 1,648 0,053* + 1,005 1,975 0,028** + 0,109 0,329 0,372
GROWTH + 0,043 0,552 0,291 + 0,254 3,961 0,000*** + 0,106 1,354 0,092*
LNSIZE - -0,147 -2,244 0,014** - -0,068 -1,199 0,120 - 0,039 0,605 0,274
R-squared 0,417 0,510 0,408
Adjusted R-squared 0,344 0,421 0,293
F-statistic 5,726 5,735 3,543
Prob(F-stat) 0,000 0,000 0,005 *** Significance at the level of = 1% (1-tailed)
** Significance at the level of = 5% (1-tailed)
* Significance at the level of = 10% (1-tailed)
CAR = cumulative annual weekly abnormal return, UE = unexpected earnings, UNIE = unexpected net interest earnings, UCFO = unexpected cash flows from
operations, UNCFI = unexpected net cash flows from interests, RISK = company’s beta, LDR = loan to deposit ratio, GROWTH = company’s growth opportunity
measured by price to book value, SIZE = company’s size measured by the market value of equity at the end of fiscal year in local currency
16
Table 4: Regression Result Model 2
= + . + . + . + . + . + . +
Indonesia Malaysia Thailand
Variable
Exp
Sign
Unstd
Coef t-Stat Sig. Exp
Sign
Unstd
Coef t-Stat Sig. Exp
Sign
Unstd
Coef t-Stat Sig.
B
(Constant) 1,689 1,759 0,042** 0,745 0,980 0,167 -0,957 -1,478 0,074*
UNIE + -0,197 -0,737 0,232 + 2,575 2,363 0,012** + -0,449 -7,153 0,000***
UNCFI + 0,126 0,127 0,450 + 0,014 0,160 0,437 + 0,315 2,784 0,004***
RISK + 0,610 2,069 0,022** + -0,436 -1,654 0,054* + 0,228 0,806 0,213
LDR + 0,802 1,812 0,038** + 0,980 2,039 0,025** + 0,231 0,854 0,199
GROWTH + 0,044 0,539 0,296 + 0,269 4,467 0,000*** + 0,112 1,102 0,139
LNSIZE - -0,158 -2,294 0,013** - -0,077 -1,474 0,075* - 0,037 0,686 0,249
R-squared 0,368 0,570 0,416
Adjusted R-squared 0,289 0,492 0,323
F-statistic 4,666 7,285 4,505
Prob(F-stat) 0,000 0,000 0,002 *** Significance at the level of = 1% (1-tailed)
** Significance at the level of = 5% (1-tailed)
* Significance at the level of = 10% (1-tailed)
CAR = cumulative annual weekly abnormal return, UE = unexpected earnings, UNIE = unexpected net interest earnings, UCFO = unexpected cash flows from
operations, UNCFI = unexpected net cash flows from interests, RISK = company’s beta, LDR = loan to deposit ratio, GROWTH = company’s growth opportunity
measured by price to book value, SIZE = company’s size measured by the market value of equity at the end of fiscal year in local currency
= 5% for Indonesia, and = 1% for Thailand. The earnings response coefficient
value for Indonesia and Thailand are 2.973 and 1.443, respectively. The results
indicate that the information of net income on banking industry for those countries
perceived to have a good quality by the investors. The ERC value for Indonesia is
higher than Thailand, which suggests that the earnings quality of Indonesian
earnings report in banking industry is better than Thailand. The finding in this
study for Malaysian context does not support Arrif and Cheng (2011) which state
that ERC of banking industry in Malaysia is significant. The different results
could be due to different time range and sample of study. Therefore the result for
Malaysia is still mixed.
4.2.2 Informativeness of Net Interest Income
Test on hypotheses 2a is performed to gain knowledge on the
informativeness of net interest income as one of the main componenet for banks.
In this test, the hypothesis is only supported for Malaysian banks, with the p-value
= 0.012 and ERC value 2.575. Related to the result for hypothesis 1, this finding
suggests that in Malaysia, the information about interest income is considered to
have higher informativeness than net earning information. This condition is the
opposite of Indonesian situation, where the net earnings information has a high
informativeness, but interest income information is considered low quality and
less informative. On the other hand, the test for Thailand shows opposite results,
with ERC value -0.449 and p-value = 0.000. This findings suggests that the
increase in unexpected interest income has a negative impact on the investor’s
perception.
4.2.3 Informativeness of Cash Flows from Operations
Test on hypotheses 3a is performed to gain knowledge on quality on
informativeness of cash flows from operating activities. Among the three
countries tested, Malaysia and Thailand showed positive and significant results on
= 5% and = 10%, respctively. The results for these countries correspond with
study of Chen (2009) which stated that cash flows information also has significant
effect on stock returns. The findings in this study suggests that informativeness of
cash flow from operations which reflects the quality of cash flow statement only
1
8
happens in Malaysia. Related to the findings for hypothesis 1a for earnings
informativeness in Malaysia which is not supported, it can be concluded that
information about cash flow from operations is perceived to be more informative
for investors than information about earnings. As for Thailand, the
informativeness of cash flows from operations is still weak, therefore investors
rely more on the earnings information. In Indonesia, hypothesis 3a is not
supported, which means that investors do not consider cash flow from operations
to be informative, and rely more on net earnings information.
4.2.4 Informativeness of Cash Flows from Interests
Test on hypotheses 4a is performed to gain knowledge on the
informativeness of cash flows from interests. The results of the tests shows that
the hypothesis is only supported by Thailand’s result with the level of = 1%.
This findings suggests that the information about cash flow from interests in
Thailand is considered informative by the investors., but not the interest income
based on accrual basis. Based on hypothesis 2a, positive unexpected interest
income in Thailand perceived negatively by investors. In contrast, Malaysian
investors consider interest earnings information to be informative, but not the cash
flow form interest. In Indonesia, both information about interest, accrual based
and cash flow based, do not have any informativeness for the investors..
4.2.5 Control Variables Analysis
In the first model, risk factor significantly influences stock return for tests
in Indonesia and Malaysia at level = 5%, while in Thailand the risk factor has
insignificant effect. What is interesting from the result is that the test in Indonesia
and Thailand show positive signs which indicate that the higher the company’s
risk the higher the stock return, while in Malaysia shows negative sign which
indicates that the higher the risk the lower stock return. The difference could be
cause by the investors in Indonesia perceived higher risk in the banks as higher
opportunities forthem to gain higher returns from the uncertainty movement of
stock prices. While the investors in Malaysia’s banking industry view the
company’s risk will have bad influence to the stock price movements. The second
model has slightly different results, where the risk factor has only significant
1
9
effect in Indonesia and Malaysia, with positive effect in Indonesia and negative
effect in Malaysia. These effects are consistent with the results in the first model.
In Thailand, the risk variable in the second model does not have significant
influence on stock returns.
For loan to deposit ratio variable, the first and second model yield similar
results, where the variable has positive and significant effect only for Indonesia
and Malaysia. The result indicate that only the Indonesian and Malaysian markets
view the deposit fund distribution in the form of loans has good impact on the
company’s investments, which in turn wull increase the company’s earnings and
stock return. On the other hand, the tests result for Thailand showed that the loan
to deposit ratio has insignificant effect on stock return.
Growth opportunity variable has a consistent positive effect on stock
returns in Malaysia. For Thailand, growth opportunity has a positive and
significant effect on stock returns only in the first model. In Indonesia, growth
opportunity does not have any effect on stock returns, but company’s size is
consistently has a negative and signifcant effect on stock returns. This result
indicates that the larger the size of the company the higher the company’s stock
returns is. The result could be due to investors’ view that smaller company has
larger opportunities to be developed, therefore the opportunity for increase in
return is also larger. It could also caused by investors’ perception that smaller
company also contains higher risk, which corresponds with the explanation above,
will have significant and contraty effect with the stock return.
In Malaysia, company’s size has a weak negative effect on stock returns only
in the second model. Therefore, in Malaysia growth opportunity has more
influence on stock returns than company’s size. In Thailand, company’s size does
not have any effect on stock returns, but growth opportunity does.
5. Conclusion
This study finds that the informativeness of information from the income
statement and cash flow statement in the banking industry is different for every
2
0
country. The component in each report has also different informativeness level.
In Indonesian banks, net income is the only component that is perceived to be
informative. On the other hand, in Malaysian banks information from the
income statement that is censidered informative by the investors is net interest
income rather than net income. But from the cash flow statements, cash flows
from operations is informative, rather than cash flows for interests. In Thailand,
both net income and interest income information, based on accrual or cash
flows, are all informative. These findings are interesting because the
informativeness of earnnings and earnings component in the banking industry is
different for each country. Further research can explore more on factors that
could be the determinants for these differences, for example the corporate
governance, the government regulation, the adoption of accounting standards,
etc. Besides, the findings in this study also indicate that the the accrual based
earnings informativeness and cash flows based informativeness can be
substituteable. Also, the component of earnings informativeness can subtititute
the net earnings informativeness. Further research can also explore more on
other components in the income statement which can also informative for the
investors.
2
1
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http://www.elsevier.com/locate/adiac.
Ball, R., Brown, Phillip (1968). An empirical evaluation of accounting income
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Appendix 1: List of Banks Used as Sample
No.
Code
(Bloomberg) Company Name Country
1 BABP:IJ Bank Icb Bumiputera Tbk. Indonesia
2 BBCA:IJ Bank Central Asia Tbk. Indonesia
3 BBNI:IJ Bank Negara Indonesia (Persero), Tbk Indonesia
4 BBRI:IJ Bank Rakyat Indonesia (Persero), Tbk Indonesia
5 BDMN:IJ Bank Danamon Indonesia Tbk. Indonesia
6 BKSW:IJ Bank Qnb Kesawan Tbk. Indonesia
7 BMRI:IJ Bank Mandiri (Persero) Tbk. Indonesia
8 BNII:IJ Bank Internasional Indonesia Tbk Indonesia
9 BNLI:IJ Bank Permata Tbk Indonesia
10 BVIC:IJ Bank Victoria International Tbk Indonesia
11 MEGA:IJ Bank Mega Tbk. Indonesia
12 NISP:IJ Bank Ocbc Nisp Tbk Indonesia
13 PNBN:IJ Bank Pan Indonesia Tbk Indonesia
14 AHB:MK Affin Holdings Bhd Malaysia
15 AFG:MK Alliance Financial Group Bhd Malaysia
16 AMM:MK Ammb Holdings Bhd Malaysia
17 CIMB:MK Cimb Group Holdings Berhad Malaysia
18 HLBK:MK Hong Leong Bank Bhd Malaysia
19 MAY:MK Malayan Banking Bhd Malaysia
2
5
Appendix 1: List of Banks Used as Sample (Continued)
No.
Code
(Bloomberg) Company Name Country
20 PBK:MK PUBLIC BANK BHD Malaysia
21 RHBC:MK RHB CAPITAL BHD Malaysia
22 BAY:TB Bank of Ayudhya PCL Thailand
23 BBL:TB Bangkok Bank PCL Thailand
24 CIMBT:TB CIMB Thai Bank PCL Thailand
25 KBANK:TB Kasikornbank PCL Thailand
26 KK:TB Kiatnakin Bank PCL Thailand
27 KTB:TB Krung Thai Bank PCL Thailand
28 SCB:TB Siam Commercial Bank PCL Thailand
29 TCAP:TB Thanachart Capital PCL Thailand
30 TMB:TB TMB Bank PCL Thailand
Appendix 2: Pearson Correlation – Indonesia Model 1
= + . + . + . + . + . +
. +
CAR UE UCFO RISK LDR GROWTH LNSIZE
CAR 1,00
UE 0,334** 1,00
(0,006)
UCFO -0,205
(1,101)
-0,073
(0,562)
1,00
RISK 0,210 0,348**
0,063 1,00
(0,093) (0,004) (0,617)
LDR 0,240 -0,010 -0,020 0,140 1,00
(0,055) (0,935) (0,875) (0,267)
GROWTH -0,204 -0,129 0,032 0,014 0,034 1,00
(0,104) (0,304) (0,802) (0,911) (0,787)
LNSIZE -0,347**
(0,005)
0,028
(0,824)
0,158
(0,208)
0,407**
(0,001)
-0,042
(0,738)
0,491**
(0,000)
1,00
Pearson Correlation – Indonesia Model 2
= + . + . + . + . + . +
. +
CAR UEI UCFI RISK LDR GROWTH LNSIZE
CAR 1,00
UNIE -0,286* 1,00
(0,021)
UNCFI -0,105 0,547**
1,00
(0,406) (0,000)
RISK 0,210 -0,107 0,000 1,00
(0,093) (0,397) (0,999)
LDR 0,240 0,038 0,054 0,140 1,00
(0,055) (0,762) (0,672) (0,267)
GROWTH -0,204 0,174 -0,008 0,014 0,034 1,00
(0,104) (0,165) (0,952) (0,911) (0,787)
LNSIZE -0,347**
0,277* 0,198 0,407
** -0,042 0,491
** 1,00
(0,005) (0,026) (0,115) (0,001) (0,738) (0,000)
** Significance at the level of = 1% (2-tailed)
* Significance at the level of = 5% (2-tailed)
Number in parantheses is p-value
Pearson Correlation – Malaysia Model 1
= + . + . + . + . + . +
. +
CAR UE UCFO RISK LDR GROWTH LNSIZE
CAR 1,00
UE 0,047 1,00
(0,775)
UCFO 0,159 0,140 1,00
(0,326) (0,388)
RISK -0,333* 0,047 0,119 1,00
(0,036) (0,773) (0,466)
LDR 0,090
(0,583)
0,003
(0,985)
0,008
(0,962)
0,493**
(0,001)
1,00
GROWTH 0,618**
(0,000)
-0,045
(0,781)
-0,115
(0,479)
-0,398*
(0,011)
-0,029
(0,860)
1,00
LNSIZE 0,334* -0,115 -0,136 -0,198 0,305 0,635**
1,00
(0,035) (0,479) (0,402) (0,221) (0,055) (0,000)
Pearson Correlation – Malaysia Model 2
= + . + . + . + . + . +
. +
CAR UEI UCFI RISK LDR GROWTH LNSIZE
CAR 1,00
UNIE 0,284
(0,076)
1,00
UNCFI 0,036
(0,826)
0,542**
(0,000)
1,00
RISK -0,333*
(0,036)
0,020
(0,902)
0,321*
(0,043)
1,00
LDR 0,090
(0,583)
0,013
(0,937)
0,084
(0,604)
0,493**
(0,001)
1,00
GROWTH 0,618**
(0,000)
-0,101
(0,535)
-0,186
(0,250)
-0,398*
(0,011)
-0,029
(0,860)
1,00
LNSIZE 0,334*
(0,035)
-0,060
(0,713)
-0,102
(0,531)
-0,198
(0,221)
0,305
(0,055)
0,635**
(0,000)
1,00
** Significance at the level of = 1% (2-tailed)
* Significance at the level of = 5% (2-tailed)
Number in parantheses is p-value
Pearson Correlation – Thailand Model 1
= + . + . + . + . + . +
. +
CAR UE UCFO RISK LDR GROWTH LNSIZE
CAR 1,00
UE 0,465**
(0,001)
1,00
UCFO -0,059
(0,701)
-0,615**
(0,000)
1,00
RISK 0,132 -0,104 0,239 1,00
(0,386) (0,495) (0,114)
LDR -0,007
(0,965)
-0,196
(0,197)
0,396**
(0,007)
0,076
(0,621)
1,00
GROWTH 0,249 0,045 0,107 0,112 -0,091 1,00
(0,100) (0,769) (0,484) (0,462) (0,554)
LNSIZE 0,212
(0,162)
-0,146
(0,338)
0,297*
(0,047)
0,528**
(0,000)
0,038
(0,803)
0,242
(0,109)
1,00
Pearson Correlation – Thailand Model 2
= + . + . + . + . + . +
. +
CAR UEI UCFI RISK LDR GROWTH LNSIZE
CAR 1,00
UNIE -0,391**
(0,008)
1,00
UNCFI -0,230
(0,129)
0,307*
(0,041)
1,00
RISK 0,132 0,141 -0,015 1,00
(0,386) (0,357) (0,923)
LDR -0,007 0,330* 0,188 0,076 1,00
(0,965) (0,027) (0,216) (0,621)
GROWTH 0,249 -0,140 -0,236 0,112 -0,091 1,00
(0,100) (0,360) (0,118) (0,462) (0,554)
LNSIZE 0,212 0,221 0,215 0,528**
0,038 0,242 1,00
(0,162) (0,144) (0,155) (0,000) (0,803) (0,109) ** Signifikan at the level = 1% (2-tailed)
* Signifikan at the level = 1% (2-tailed)
Number in parantheses is p-value