Corresponding Author: Agung Pramudito�
Email: [email protected]�������
INTRODUCTION
Through Presidential Decree No. 12 of 2020, the
government determined the COVID-19 pandemic as a non-natural national disaster.
Based on Law No. 24 of 2007 concerning Disaster Management, a disaster is an
event or series of events that threatens and disrupts people's lives and
livelihoods caused, both by natural factors or non-natural factors as well as
human factors resulting in human casualties, environmental damage, loss of
property, and psychological impact (Umeidini et al., 2019). Non-natural disasters are caused by non-natural
events or series of events, including technological failures, modernization
failures, epidemics, and disease outbreaks (Samin, 2021).
The impact of the COVID-19 pandemic on the stock
market, IHSG experienced a sharp correction in February 2020, which was the
lowest closing value during 2020. On the other hand, pharmaceutical companies
listed in the IDX-IC F211 category consistently showed an increasing trend in
share prices during the year. 2020. The pharmaceutical company's share price
was consistent until the end of 2021. It did not decline again to the price at
the beginning of 2020. A comparison graph of joint stock price fluctuations
with several pharmaceutical companies can be seen in the following image:
Figure 1. Comparison of Pharmaceutical Company Share
Prices and IHSG
Source: Results of stock market data processing, 2021
Figure 1 shows the average movement of pharmaceutical
company share prices at the beginning of 2020 in contrast to the IHSG.
Pharmaceutical company share prices in the first quarter of 2020 remained
stable, while the JCI experienced a sharp decline. There was a significant
increase in the third quarter of 2020, while the JCI was still fluctuating and
tended to decline. In 2021, even though the JCI movement has improved, IDX-IC
F211 shares remain constant, have not experienced a decline, and have returned
to their initial position before the pandemic.
As explained in the definition of disaster, COVID-19
is an event or series of events that disrupt people's lives and livelihoods. Covid-19 directly affected
Indonesia's economic growth in 2020. Based on the release of the Central Bureau
of Statistics, Indonesia experienced a decrease in GDP growth of -2.19%
compared to 2019. Gross domestic product influences stock prices on Latin
American stock exchanges (de Sousa et
al., 2018). Based on previous research, the poor condition
of Indonesia's GDP should affect the stock prices of pharmaceutical companies (de Sousa et
al., 2018). The results of previous research are not in
line with other research that states. The influence of gross domestic product
on the stock price index on two stock exchanges, India and America (Sahoo et
al., 2020) ; (de Sousa et
al., 2018). This research shows that gross domestic
product has a different influence on stock prices on the two exchanges. Gross
domestic product does not affect stock prices on the American stock exchange.
However, it has an influence on stock prices in India.
Previous research has been
conducted on the influence of macroeconomic indicators on stock prices. Macroeconomic indicators are one of the factors that
investors consider in making decisions. GDP, the object of research, is only
one macroeconomic indicator that can influence stock prices (de Sousa et al., 2018)
; (Sahoo et al., 2020). However, the results of previous research regarding
the influence of macroeconomic indicators other than GDP on stock prices also
produce different conclusions.
Previous research states that inflation and interest
rates influence stock prices in Tanzania (Epaphra, 2018) ; (Gwahula, 2018). Other research also states that the inflation rate
and interest rates affect stock prices in Indonesia (Utomo et al., 2019) ; (Mawardi et al., 2019). Other research on interest rates stated that
interest rates affect stock prices in Malaysia (Qing & Kusairi,
2019). However, the results of previous research state that
the inflation rate and interest rates do not affect the American or Indian
stock price index (Sahoo et al., 2020). Likewise, others also stated that the inflation and
interest rates do not affect the share prices of palm oil companies in
Indonesia (Putri et al., 2019).
Macroeconomics is a general economic problem that
affects the lives of individuals. This problem involves the overall economic
performance of a country. Macroeconomics not only has an influence on stock
prices but also affects the company's financial performance, as the results of
research (Rao, 2016), (Issah & Antwi,
2017), (Gautam, 2018), (Hadi et al., 2018). The results of other studies state that several
macroeconomic indicators do not affect financial performance, including
inflation and interest rates (Egbunike &
Okerekeoti, 2018) ; (Dewi et al., 2019).
On the other hand, the company's financial performance
is an important instrument in decision-making by investors. The effectiveness
of company finances results from management activities (Siswanti et al., 2021). To assess the success of company management in
achieving company goals set within a certain period, using the results of
management activities as parameters or benchmarks. Financial reports, as a
source of information for investors regarding the company's financial
condition, are a resource for decision-making. This is supported by other
research, stating that the company's financial performance influences share
prices (Pranata & Pujiati,
2015), (Putri et al., 2019), (Nasarudin &
Anggraini, 2019) ; (Lusiana, 2020). Previous research shows that ROA does not affect
share prices (Prayogo & Lestari,
2018).
The differences in previous research results regarding
the influence of macroeconomics on stock prices and the increasing share prices
of pharmaceutical companies during the pandemic need to be clarified. Further
research is needed to examine the direct effect of macroeconomics on stock
prices. Apart from research on direct influences, research on the ability of
financial performance to mediate macroeconomic influences on stock prices is
also necessary. This is based on some previous research which concluded that
financial performance can influence stock prices and can be influenced by
macroeconomics. Therefore, this research aims to determine and analyze the
influence of macroeconomics on stock prices in the pandemic era through
financial performance as an intervening variable in pharmaceutical companies
listed on the Indonesian stock exchange. Therefore, the benefits of this
research are as follows: this research helps to gain a deeper understanding of
how macroeconomic factors can affect stock prices through financial
performance. It provides insights into the possible mechanisms involved. The
results of this research can be used by investors, financial analysts, and
financial managers to make better investment decisions. Additionally, the
benefit of this research is that companies can use the results of this research
in strategic corporate planning.
METHOD
Research is quantitative, with strategies oriented toward data and
policy analysis to answer research questions. The
population of this study is the IDX Classification of the Health sector
(IDXHEALTH) with the pharmaceutical industry subsector (Pharmaceutical Industry
subsector F211). Pharmaceutical industry subsector, which conducted an IPO
before January 1, 2020, and continued to list until December 2021. The
background and period of the research were the basis for consideration in
determining the sample where the pandemic conditions began at the beginning of
2020, so companies that conducted an IPO after January 1, 2020, are not
affected by this condition. Companies delisted within the research period were
also not used as research samples because they could not fully describe the
conditions in the research. The data collection results showed that 1 company
in the F211 subsector was delisting, namely SCPI. The data analysis techniques
used in this research include tests for normality, heteroskedasticity,
multicollinearity, and hypothesis testing.
RESULTS AND DISCUSSION
Classical Assumption
Testing
a. Normality
test
The normality test in panel data regression can be
done by looking at the probability value of the Jarque - Bera normality test
results. In this test, if the probability value obtained is > 0.05, it can
be concluded that the regression residual is normally distributed so that the
normality assumption is met, whereas if the probability value obtained is <
0.05, then it can be concluded that the residual from the regression results is
not normally distributed.
Figure 2. Normality Test Results of the Effect of
Inflation, GDP,
BI7DRR and ROA to Share Prices
Source: processed data (2023) in Appendix 3
Based on Figure 2 above, the probability value of the
Jarque - Bera normality test result is 0.068256 > 0.05, which indicates that
the residual regression data is normally distributed.
b. Heteroscedasticity Test
The heteroscedasticity test can be carried out using
the Gletsjer test. The model is declared to contain heteroscedasticity in this
test if the Chi-Square probability is <0.05. In contrast, if the Chi-Square
probability is > 0.05, it is stated that the model does not contain
heteroscedasticity. Based on the results of the heteroscedasticity test in
Appendix 2, it can be seen that the chi-square probability value obtained is
0.0492 <0.05. This means that there is heteroscedasticity in the regression
model. Based on the overall classical assumption test results above, it is
concluded that the regression model meets all classical assumptions.
c. Multicollinearity Test
The partial
correlation test between independent variables is carried out to detect
multicollinearity. Then, it can be decided whether the data is affected by
multicollinearity, namely by testing the correlation coefficient between
independent variables. The results of the multicollinearity test show the
following:
Table 1 Multicollinearity Test Results for Inflation,
GDP, and BI7DRR
|
|
INFLATION
|
GDP
|
BITRATE
|
|
INFLATION
|
1,000000
|
-0.372522
|
0.866948
|
|
GDP
|
-0.372522
|
1,000000
|
-0.663566
|
|
BITRATE
|
0.866948
|
-0.663566
|
1,000000
|
The
results of the multicollinearity test showed no correlation value between the
independent variables that exceeded 0.90. Based on Table 1 of the
multicollinearity test results processed above, all correlation coefficient
numbers are less than 0.9, indicating no correlation value between the
independent variables. Thus, it can be concluded that the model is free from
multicollinearity problems.��
Hypothesis
test
In this research, the regression model is divided into 2 models,
namely the relationship between the influence of GDP, BI Seven Day Reverse
Repo Rate, Inflation, and ROA on company share prices, while the second
model is the influence of GDP,
BI7DRR, and Inflation on ROA. The results of the panel regression analysis,
including the partial influence test (t-test) for each model using random
effects, are as follows.
a. T Test of the Effect of Inflation, GDP, BI7DRR, and ROA on Stock
Prices
In panel data regression analysis, the
t-test is used to partially test the influence of the independent variable on
the dependent variable. The test hypothesis used in this partial test is as
follows:
Ho: The independent variable does not affect stock prices
Ha: The independent variable influences stock prices
With a
significance level of 0.05, Ho is rejected if the probability value is
<0.05. Ho will be accepted if the probability value is >0.05.
Table 2 T-TEST RESULTS
|
Dependent Variable: Stock Price
|
|
|
Method: EGLS panel (Period random effects)
|
|
Date: 05/16/23 Time: 14:29
|
|
|
Sample: 2020Q1 2021Q4
|
|
|
|
Periods included: 8
|
|
|
|
Cross-sections included: 9
|
|
|
|
Total panel (balanced) observations: 72
|
|
|
Swamy and Arora estimator of component variances
|
|
Cross-section SUR (PCSE) standard errors & covariance (df
corrected)
|
|
Variables
|
coefficient
|
std. Error
|
t-Statistics
|
Prob.
|
|
Inflation
|
-63.30883
|
17.58060
|
-3.601062
|
0.0006
|
|
BI7DRR
|
11.26198
|
22.85555
|
0.492746
|
0.6238
|
|
GDP
|
1.450579
|
0.745380
|
1.946094
|
0.0558
|
|
ROA
|
-4.390819
|
0.900257
|
-2.310644
|
0.0239
|
|
C
|
-1.392024
|
2.519759
|
-0.552443
|
0.5825
|
Source: processed data (2023)
Based on the t-test results in the table
above, the following results were obtained:
1)
Stock Price
Inflation�
The significant value of the influence of inflation on stock prices is
0.000 because of the sig value. < 0.05 and a negative regression coefficient
of -63.30883, it is concluded that inflation has a negative and significant
effect on stock prices, meaning that high inflation can risk reducing the
company's share price.
2)
GDP �Stock Prices
The
significant value of the influence of GDP on stock prices is 0.0558 because of
the sig value. > 0.05, it is concluded that high and low GDP influences high
and low stock prices
3)
BI7DRR �Share Price
The significant value of the influence of BI7DRR on stock prices is
0.6238 because of the sig value. < 0.05, it is concluded that the high and
low BI7DRR does not affect the high and low share prices.
4)
ROA �Share Price
The significant value of the influence of ROA on share prices is 0.0239
because of the sig value. < 0.05 and a negative regression coefficient of
-4.390819, it is concluded that ROA has a negative and significant effect on
share prices, meaning that the higher the ROA, the higher the share price, and
vice versa, the lower the ROA, the lower the share price
Based on the results of the analysis in
the table above, the following regression equation is obtained:
Y = -1.392024 + - 63.30883 (X1) + 1.450579 (X2) + 11.26198 (X3) �
4.390819 (X4)
Information :
X1 = Inflation
X2 = GDP
X3 = BI7DRR
X4 = ROA
Y = Share Price
Based on the regression equation, the relationship between
variables is obtained as follows:
1.
In conditions
where the GDP, BI7DRR, and ROA variables are fixed, a decrease in inflation by
1 will reduce stock prices by -63.30883
2.
Under
conditions where the variables Inflation, BI7DRR, and ROA are fixed, an
increase in GDP by 1 will increase stock prices by 11.26198
3.
Under
conditions where the GDP, Inflation, and ROA variables are fixed, an increase
in BI7DRR by 1 will increase share prices by 1.450579
4.
Under
conditions where the GDP, BI7DRR, and Inflation variables are fixed, a decrease
in ROA of 1 will reduce the share price to -4.390819.
b.
T Test of the
Effect of Inflation, GDP, and
BI7DRR on ROA
In panel data regression analysis, the t-test is used to partially test
the influence of the independent variable on the dependent variable. The test
hypothesis used in this partial test is as follows:
Ho: The independent variable does not affect ROA
Ha: Independent variables influence ROA
With a significance level of 0.05, Ho is rejected if the probability
value is <0.05. Ho will be accepted if the probability value is >0.05.
Table
3. Results of the T-TEST ON THE INFLUENCE OF INFLATION,
GDP, AND BI7DRR on ROA
|
Dependent Variable: ROA
|
|
|
Method: Panel EGLS (Cross-section random effects)
|
|
Date: 05/16/23 Time: 15:11
|
|
|
Sample: 2020Q1 2021Q4
|
|
|
|
The period included: 8
|
|
|
|
Cross-sections included: 9
|
|
|
|
Total panel (balanced) observations: 72
|
|
|
Swamy and Arora estimator of component variances
|
|
Cross-section weights (PCSE) standard errors & covariance
(df corrected)
|
|
Variables
|
coefficient
|
std. Error
|
t-Statistics
|
Prob.
|
|
Inflation
|
-2.984988
|
1.322274
|
-2.257467
|
0.0272
|
|
BI7DRR
|
2.482136
|
1.779149
|
1.395125
|
0.1675
|
|
GDP
|
0.123508
|
0.056272
|
2.194823
|
0.0316
|
|
C
|
-0.331406
|
0.194531
|
-1.703614
|
0.0930
|
Source: processed data (2023)
Based on the results of the t-test in the
table above, the following results are obtained:
1.
ROA inflation�
The significant value of the effect of inflation on ROA is 0.027 because
of the sig. <0.05 and a negative regression coefficient of -2.985, it is
concluded that inflation has a negative and significant effect on ROA, meaning
that the higher the inflation, the lower the company's ROA, and vice versa, the
lower the inflation, the more it supports the company's high ROA.
2.
GDP �ROA
The
significant value of the influence of GDP on ROA is 0.031 because of the sig
value. < 0.05 and a positive regression coefficient of 0.124, it is
concluded that GDP has a positive and significant effect on ROA, meaning that
the higher the GDP, the higher the ROA, and vice versa, the lower the GDP, the
lower the ROA.
3.
BI7DRR �ROA
The
significant value of the influence of BI7DRR on ROA is 0.167 because of the sig
value. > 0.05, it is concluded that the high and low BI7DRR do not affect
the high or low ROA
Based on the results of the analysis in
the table above, the following regression equation is obtained:
Y = -0.331 � 2.985 (X1) + 0.124 (X2) + 2.482 (X3)
Information :
X1 = Inflation
X2 = GDP
X3 = BI7DRR
Y �� = ROA
The explanation of the regression equation is
1. In conditions where the GDP variables and interest rates are
fixed, a decrease in inflation by 1 will reduce ROA by -2.985,
2. Under conditions where the interest rate and inflation variables
are fixed, an increase in GDP by 1 will increase ROA by 0.127,
3. Under conditions where the GDP and inflation variables are fixed,
increasing BI7DRR by 1 will increase ROA by 2.482.
The
Effect of Inflation on Stock Prices
Hypothesis 1 in this research is accepted, and it can be concluded that
inflation harms stock prices, which means that the higher the inflation, the lower
the stock prices, and vice versa, the lower the inflation, the higher the stock
prices. This research aligns with APT theory, which states that macroeconomic
indicators influence stock returns.
An increase in the average price of all goods and services in the economy
must be distinguished from an increase in the relative prices of individual
goods. Therefore, an increase in inflation can trigger a decline in company
stock prices, especially for companies in the industrial sector. Inflation has
a negative relationship with stock prices. Inflation increases a company's
revenue and costs. If the increase in production costs is higher than the price
increase that the company can enjoy, the company's profitability will decrease.
Suppose the profit earned by the company is small. In that case, this will make
investors reluctant to invest their funds in the company, decreasing the stock
price (Wardani
& Andarini, 2016).
The results of this research are in line with previous research, which
found that inflation had a significant effect on stock prices (Gwahula,
2018) (Utomo
et al., 2019), but this is not in line with
other research which found that inflation did not have a significant effect on
stock prices on the Indian and American stock markets (Sahoo
et al., 2020).
The Effect of GDP on Stock Prices
Hypothesis 2 in this research is accepted, and it is concluded that GDP
positively affects stock prices, which means that the higher the GDP, the
higher the stock price.
An increase in GDP is a good signal (positive) for investment and vice
versa. Increasing GDP has a positive effect on consumer purchasing power so
that it can increase demand for company products. An increase in GDP reflects a
country's consumer purchasing power. An increase in consumer purchasing power
causes an increase in public demand for company goods and services, which will
increase company profits.
The results of testing Hypothesis 2 align with the APT theory, which
states that economic factors influence the level of stock prices. This study
uses general Indonesian GDP data, where the pandemic conditions have worsened
Indonesia's GDP. GDP reflects the added value generated by all economic
production activities (Dama,
2016). This means that an increase
in GDP also reflects an increase in remuneration for the production factors
used in these activities. This shows that an increase in GDP also reflects an
increase in people's welfare. Sukarno (2013) An increase in state income will
encourage more investment.
This research aligns with previous research, stating that inflation and
interest rates influence stock prices in Tanzania (Epaphra,
2018) ; (Gwahula,
2018). Other previous research
researched the influence of gross domestic product on the stock price index on
two stock exchanges, namely India and America (Sahoo
et al., 2020). This research shows that
gross domestic product has a different influence on stock prices on the two
exchanges. Gross domestic product does not affect stock prices on the American
stock exchange. However, it has an influence on stock prices in India.
Differences in stock market conditions, which are the focus of research (Sahoo
et al., 2020), can also determine the
influence of GDP on stock prices.
The Effect of BI7DRR on Stock Prices
Hypothesis 3 in this study is not accepted, and it can be concluded that
the BI7DRR has no effect on stock prices, which means that the high or low
BI7DRR does not affect stock prices.
Changes in BI7DRR affect deposit rates and bank lending rates. BI lowered
BI7DRR to encourage economic activity (Susilowati &
Wahyuningdyah, 2018). The reduction in BI7DRR will
affect consumption and investment. This transmission process requires a certain
time lag. Investment is a prediction of the state of
the economy in the future. Forecasts indicating that the economic situation
will improve even more, namely predictions that prices will remain stable and
economic growth and increases in people's incomes will develop rapidly, are
conditions that will encourage investment growth.
Based on BI7DRR data, it shows that on January 23, 2020, BI set a BI7DRR
of 5%. However, this policy continues to decrease until January 21, 2021, to
3.75%. BI reduced the BI7DRR again on February 18, 2021, to 3.5%. This policy
remains constant until the end of 2021. This insignificant variation in data
may be one of the reasons that the BI7DRR variable does not affect stock
prices.
BI policies that tend to reduce the BI7DRR carry the risk of rising
inflation. Prices of goods will tend to rise, increasing the company's
production costs. People's purchasing power, reflected in GDP, tends to
decrease during the pandemic. This illustrates the uncertainty of economic
conditions during a pandemic. In addition, in the 2022 economic development
report, BI reports that there is a tendency for investors to be careful in
making investments and tend to invest in safer sectors.
Based on this explanation, it can be concluded that several factors may
have made BI7DRR not affect stock prices, namely (1) the behavior of investors
who are cautious in making these investments so that they prioritize the
consumption sector or other safer investment sectors, and (2) uncertain
forecasts of economic conditions during a pandemic.
The results of this research are in line with previous research, which states that interest
rates affect stock prices (Putri
et al., 2019), but this is not in line with other research, which states that interest
rates affect stock prices (Utomo
et al., 2019), (Sahoo
et al., 2020), (Gwahula,
2018).
The Effect of Inflation on ROA
Hypothesis 4 in this research is accepted, and it can be concluded that
inflation harms ROA, which means that the lower the inflation, the higher the
ROA, and vice versa; the higher the inflation, the lower the ROA.
ROA is a ratio that compares profit (before tax) and total bank assets.
This ratio shows the efficiency level of asset management carried out by the
bank concerned (Katuuk
et al., 2018). High inflation reflects an
increase in goods, which reduces the value of the money supply due to rising
prices, and high inflation reduces assets. The result of high inflation will
reduce people's purchasing power because this will reduce the assets owned by
companies. On the other hand, with increasing inflation, the purchasing power
of the invested rupiah will decrease. So, the risk of inflation is also called
purchasing power risk. If inflation increases, investors usually demand an
additional premium to compensate for the decline in people's purchasing power;
this will further affect the company's ROA.
Inflation generally has an unfavorable impact on the economy; however, as
one of the economic principles states that in the short term, there is a
trade-off between inflation and unemployment, this shows that inflation can
reduce the unemployment rate, or inflation can be used as a way to balance the
country's economy, etc. Among the negative impacts caused by inflation is a
decrease in people's purchasing power, with prices generally continuing to
rise. In contrast, people's income sources remain constant. Second, producers
tend to be forced to increase selling prices due to increased purchasing prices
for raw materials. However, on the other hand, people's purchasing power
decreases. Third, the distribution of goods could be more fair because there is
accumulation and concentration of products in areas where people are close to
production sources and have much money. Based on these three negative impacts,
inflation can significantly affect ROA in a negative direction, meaning that
high inflation can reduce a company's ROA.
The results of this study are in line with the results of previous
studies, which stated that inflation has a positive effect on ROA (Siswanti
et al., 2015) ; (Hadi
et al., 2018), but this is not in line with
the results of other studies which show insignificant results on the effect of
inflation on ROA (Dewi
et al., 2019).
Effect of GDP on ROA
Hypothesis 5 in this study is accepted, and it can be concluded that GDP
positively affects ROA, which means that the higher the GDP, the higher the
ROA, and vice versa; the lower the GDP, the lower the ROA.
GDP measures the market value of final goods and services produced by
resources located in a country during a certain period, usually one year. GDP
can also be used to study the economy over time or simultaneously compare
several economies. Gross domestic product or GDP is the value of goods and
services produced in a country using production factors owned by
residents/state companies (Sahara,
2013). GDP only includes final goods
and services, namely goods and services sold to final users. Goods and services
purchased to be processed and sold again (intermediate goods and services) are
not included in GDP to avoid the problem of double counting, namely counting a
product more than once. Therefore, a high GDP can support a high company ROA.
The results of this research are in line with the results of previous
research, which found that ROA (Egbunike
& Okerekeoti, 2018), (Hadi
et al., 2018), (Issah
& Antwi, 2017) and (Gautam,
2018) but are not in line with the
results of other studies which states that the
profitability of Islamic banks is not influenced by GDP and inflation.
Influence of BI7DRR on ROA
Hypothesis 6 in this study is not accepted, and it can be concluded that
BI7DRR does not affect ROA, which means that high and low BI7DRR do not affect
high or low ROA.
BI7DRR changes affect deposit and bank lending rates (Susilowati
& Wahyuningdyah, 2018). BI lowered BI7DRR to
encourage economic activity. A decrease in BI7DRR will impact the increasing
demand for credit from households or companies. This decrease will also reduce
the company's cost of capital to invest. However, the results of this study
show that there is no significant effect of BI7DRR on ROA; ROA is more
influenced by factors other than BI7DRR, such as inflation and GDP or other
factors that are not used as objects in this study.
Based on BI7DRR data, it shows that on January 23, 2020, BI set BI7DRR at
5%, but this policy continued to decrease until January 21, 2021, to 3.75%. BI
lowered BI7DRR again on February 18, 2021, to 3.5%. This policy is constant
until the end of 2021. This insignificant variation in data may be one of the
reasons why the BI7DRR variable does not affect ROA.
BI reports that there is a tendency for investors to be careful in making
investments; this behavior also applies to business actors. Even though the
reduction in BI7DRR is intended as a credit stimulus for entrepreneurs, the
uncertainty of economic conditions and the impact of the reduction in BI7DRR on
inflation have made business actors prefer not to expand their business by
purchasing assets and increasing production through purchasing these assets.
This research is in line with what states that interest rates do not
affect ROA (Egbunike
& Okerekeoti, 2018) but is not in line with other
research which states that interest rates affect ROA (Hadi
et al., 2018) (Khan
& Khan, 2018 ) ; (Student
et al., 2015).
The Effect of ROA on Share Prices
Hypothesis 7 in this research is accepted, and it can be concluded that
ROA hurts share prices, which means that the higher the ROA, the higher the
share price, and vice versa, the lower the ROA, the lower the share price.
Signaling theory states that there is asymmetric information between
external and internal parties of the company. This condition causes companies
with more information to provide signals of actual conditions to external
parties, including investors, through financial reports. ROA shows the extent
to which a company's ability to use the assets owned by the company to generate
profits. The ROA ratio is calculated by comparing the net profit with the
company's total assets. The higher the ROA ratio, the better the company's
ability to generate profits, thereby increasing the interest of investors
because it affects the greater the rate of return so the ROA will affect the
company's stock price. The results of this study indicate that investors make
good use of the information described through the company's ROA in making
investment decisions.
However, this research shows that an ROA that is too high can reduce the
company's share price. One of the determining factors for
investment is the forecast of the future state of the economy. If the forecast
shows that the economic situation will be better, including stability in prices
and economic growth, and the increase in people's income will develop rapidly,
this situation will encourage investment growth. Uncertainty in economic
forecasts during the pandemic has changed investment behavior. The anomaly of
increasing the ROA of pharmaceutical companies, which is too high, increases
investors' distrust in investing in their shares.
The results of this study are in line with the results of previous
research that ROA affects stock prices (Putri
et al., 2019) but not in line with the
results of other studies because it shows that ROA has no significant effect on
stock prices (Prayogo
& Lestari, 2018) ; (Rahmani,
2020).
ROA's ability to mediate the effect of the inflation rate in the pandemic
era on pharmaceutical company stock prices
Hypothesis 8 in this research is accepted, and it can be concluded that
ROA can mediate the influence of the inflation rate in the pandemic era on
company share prices. Inflation has an impact on both sides of the company's
financial management. First, raw material prices are increasing, increasing
production costs and reducing profit margins. Second, people's purchasing power
is decreasing, so it will directly or indirectly impact company sales.
Increased cost of production and decreased sales will reduce net profit.
Therefore, the calculation of the ROA ratio will decrease. The results of
testing hypothesis 1 show that inflation impacts stock prices. This is in line
with the APT theory, which states that stocks are affected by inflation. This
shows that investors can use information directly on the inflation rate for
investment purposes. Based on signaling theory, investors can use this
information for their investment interests. The results of testing hypothesis 8
also show that investors use information on the impact of inflation on
investment decisions through information reflected in ROA.
ROA's ability to mediate the influence of GDP in the pandemic era on
pharmaceutical company stock prices
Hypothesis 9 in this study is not accepted, and it can be concluded that
ROA cannot mediate the effect of GDP in the pandemic era on company stock
prices. An increase in the GDP of a business sector indicates that the
production level of companies operating in that sector has increased.
Based on signaling theory, investors can use this information to invest
in this sector. The results of testing hypothesis 2, which tested the direct
influence of GDP on stock prices, were accepted. This shows that investors use
GDP information to make investment decisions. The results of testing hypothesis
7 show that ROA directly influences prices. The coefficient value of the
influence of GDP on stock prices is smaller than that of the influence of ROA
on stock prices. This shows that investors trust GDP data, which is more
dominant than ROA on share prices. This may be due to pharmaceutical companies'
highly fluctuating ROA data during 2020 and 2021. Calculation of ROA movements
per company is as depicted in the following table.
Table 4. Movement in ROA of Pharmaceutical Companies
|
2020
|
2021
|
|
Company
|
Movement from TW 1 to TW 2
|
Movement from TW 2 to TW 3
|
Movement from TW 3 to TW 4
|
Movement from TW 1 to TW 2
|
Movement from TW 2 to TW 3
|
Movement from TW 3 to TW 4
|
|
DVLA
|
136.66%
|
11.67%
|
5.69%
|
60.98%
|
5.29%
|
4.18%
|
|
INFO
|
-80.72%
|
322.33%
|
-100.14%
|
-49.52%
|
139.99%
|
-1640.58%
|
|
KAEF
|
237.77%
|
-12.00%
|
-54.62%
|
245.27%
|
420.77%
|
4.38%
|
|
KLBF
|
108.38%
|
44.80%
|
34.42%
|
113.50%
|
48.31%
|
31.47%
|
|
BRAND
|
-7.29%
|
75.63%
|
30.83%
|
44.39%
|
46.82%
|
0.75%
|
|
PEHA
|
-296.86%
|
74.40%
|
11.73%
|
43.19%
|
10.76%
|
5.54%
|
|
PYFA
|
32.95%
|
160.46%
|
31.14%
|
3.13%
|
29.36%
|
-73.29%
|
|
SIDO
|
93.86%
|
44.17%
|
40.08%
|
108.22%
|
70.02%
|
30.39%
|
|
TSPC
|
32.60%
|
31.01%
|
52.50%
|
43.69%
|
32.62%
|
48.73%
|
|
28.59%
|
83.61%
|
5.74%
|
68.10%
|
89.33%
|
-176.49%
|
Based on the table above, the ROA movement value of pharmaceutical
companies tends to fluctuate. The highest movement was in the second quarter of
2021 and the second quarter of 2020, with average ROA movements of 89.33% and
83.61%, respectively. The highest movement in the second quarter of 2020
occurred in the INAF company at 322.33%; however, in the third quarter, ROA
moved negatively or decreased by 100.14%. This shows that INAF experienced a
decline in income or invested in assets in the 3rd quarter of 2020. In the 3rd
quarter of 2021, the highest ROA movement for KAEF companies was 422.77%, but
in the 4th quarter of 2021, the KAEF ROA movement was only 4.38 %. This
inconsistency in ROA indicates uncertainty in the financial conditions of
pharmaceutical companies in 2020 and 2021. In the 2022 economic report, BI
reports that there is a tendency for investors to be careful in making
investments. Fluctuating ROA and uncertain economic conditions can influence investor
behavior.
ROA's ability to mediate the influence of BI7DRR in the pandemic era on
pharmaceutical company stock prices
Hypothesis 10 in this study is accepted, and it can be concluded that the
ability of ROA can mediate the influence of BI7DRR in the pandemic era on
company stock prices. ROA is one of the information provided by the company's
internal to outsiders to provide an overview of the company's financial
condition. This is a signal for investors to make investment decisions. As
stated in the Signaling theory, external and internal parties of the company
have information asymmetry, and internal parties provide signals to outsiders
through financial reports. The results of testing hypotheses 3 and 6 show that
BI7DRR does not affect stock prices or ROA. This is inconsistent with the APT
Theory, which states that stock returns are influenced by macroeconomic
factors.
The standard concept of the monetary policy transmission mechanism starts
when the central bank changes instruments, which then influence operational,
intermediate, and final targets (Natsir,
2011). For example, BI increases
BI7DRR; this increase will push up interbank money market interest rates,
deposit interest rates, bank credit, asset prices, exchange rates, and
inflation expectations in the community. These changes will then affect
consumption and investment. This transmission process requires a certain
deadline (time lag). Apart from that, the BI economic report for 2022 states
that there are indications that investors are being careful in investing their
funds. However, the results of testing Hypothesis 10 show that ROA can mediate
the influence of BI7DRR on stock prices. This hypothesis shows that APT and
signal theories are compatible with this phenomenon, where investors use
macroeconomic information and ROA simultaneously to determine their investment
actions.
CONCLUSION
Based on the results of
the research and discussion in the previous section, it can be concluded as
follows: In summary, the research findings and discussions lead to the
following conclusions: 1) Inflation significantly and negatively affects the
stock prices of pharmaceutical companies during the pandemic, in accordance
with the Arbitrage Pricing Theory (APT). 2) Gross Domestic
Product (GDP) has a significant impact on the stock prices of pharmaceutical
companies during the pandemic, aligning with the Arbitrage Pricing Theory
(APT). 3) BI7DRR (Bank Indonesia's 7-Day Reverse Repo Rate) does
not significantly influence the stock prices of pharmaceutical companies during
the pandemic, contrary to the predictions of the Arbitrage Pricing Theory
(APT). This may be attributed to business responses to economic uncertainty,
BI's policy direction, and inflation-related risks. 4)
Inflation significantly and negatively impacts the Return on Assets (ROA) of
pharmaceutical companies during the pandemic, in line with the Arbitrage
Pricing Theory (APT). 5) GDP positively and significantly affects the Return on
Assets (ROA) of pharmaceutical companies during the pandemic, consistent with
the Arbitrage Pricing Theory (APT). 6) BI7DRR does not significantly affect the Return on
Assets (ROA) of pharmaceutical companies during the pandemic, which deviates
from the expectations of the Arbitrage Pricing Theory (APT). This could be
influenced by business behavior in an uncertain economic environment. 7) ROA
negatively influences the stock prices of pharmaceutical companies during the
pandemic, in line with Signaling Theory, which suggests that companies signal
information to investors through financial reports due to information
asymmetry. 8) ROA can mediate the impact of inflation during the
pandemic on the stock prices of pharmaceutical companies, in accordance with
the Arbitrage Pricing Theory (APT) and Signaling Theory. 9) ROA
cannot mediate the impact of Gross Domestic Product (GDP) during the pandemic
on the stock prices of pharmaceutical companies, which contradicts the
expectations of the Arbitrage Pricing Theory (APT) and Signaling Theory. 10) ROA
can mediate the impact of BI7DRR during the pandemic on the stock prices of
pharmaceutical companies, in line with the Arbitrage Pricing Theory (APT) and
Signaling Theory.
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