115 FACTORS THAT DETERMINE STOCK RETURNS MODERATED BY STOCK
TRADING VOLUME IN MANUFACTURING COMPANIES LISTED ON THE INDONESIAN STOCK EXCHANGE FOR THE 2017-2021 PERIOD
Siti Rahmi Hidayatullah1*, Elfiswandi2, Zefri Yenni3
1,2,3
Master of Management Program, Faculty of Economic and Business Putra Indonesia University “YPTK” Padang, West Sumatera, Indonesia
Email: *sitirahmihidayatullah@gmail.com
Abstract
The changing or unstable average stock return in manufacturing companies is the driving force behind this study. In order to determine and assess the impact of return on assets, current ratio, and profits per share on stock returns in manufacturing business listed on the Indonesia Stock Exchange for the 2017–2021 timeframe, stock trading volume will be used as a moderating variable. This study is quantitative and includes a total of 191 manufacturing business listed on the Indonesia Stock Exchange for 2017 through 2021.
Purposive sampling was used in this study's sampling process. This study use sample of 56 manufacturing enterprises listed on the IDX and 280 pieces of observation data. The financial reports used for the research can be found on the IDX's official website as secondary data (www.idx.co.id). Using EViews 9, panel data regression was used to evaluate this investigation. The findings of this study revealed that earnings per share, current ratio, and return on assets all had a significant and favorable impact on stock returns. According to the results of the Moderated Regression Analysis test, the current ratio's impact on stock returns is moderated by stock trading volume, while its impact on return on assets and earnings per share is not moderated. The results of this study are expected to provide input and be used as a consideration on the companies that are listed on IDX that is important to pay attention to stock returns distributed to investors, pay attention to the return of assets, ability to pay debt, and the ability to manage assets in order to generate maximum profits for shareholders.
Keywords: Stock Return, Return on Assets, Current Ratio, Earning Per Share, Stock Trading Volume
JEL Classification: G3, M4
Submission date : 1-10-2022 Revised date : 5-12-2022 Accepted date : 7-12-2022
*Corresponding author
INTRODUCTION
Now people are used to carrying out various economic transactions with the aim of investing their assets or wealth, namely by investing through the capital market. So investors need to determine an efficient allocation of funds in the capital market, to determine which investments will provide optimal return for them (Sodikin & Wuldani, 2016). It can be concluded that someone in investing, his goal is to get a satisfactory return. Because The return is a parameter for investors when investors want to invest in the capital market, investors will first evaluate the company's performance in order to determine which company
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shares will provide the maximum expected profit. Companies with high stock returns will certainly be an option for investors to invest their capital (Almira & Wiagustini, 2020).
Returns on shares or the results obtained by investors from the company where they invest their shares are called stock returns, The returns can take the form of dividends and capital gains (losses) in the form of the variation in share prices between the time of acquisition and the period of sale. So that it can be interpreted that stock returns are an advantage that investors get if they invest in stocks, where these profits can come from yields in the form of cash flows or dividends and also capital gains / losses (Hartono, 2017). An investor is someone who has funds and then invests these funds in a company. Investors invest with a specific purpose, namely to earn profits and increase their own money. The higher the stock return provided, the more attractive the investor's interest and the more likely the company's shares will be traded (Siregar & Dani, 2019).
One of the business sectors that is growing very rapidly is manufacturing companies, the manufacturing sector is the object of choice in this study. This sector provides the largest contribution or contribution supporting growth in the Indonesian economy to reach 7.07% in 2021 (quarter II). In addition, the manufacturing sector was the source of the highest growth at 1.35%. The manufacturing sector experienced quite good growth despite being under pressure due to the Covid-19 pandemic, which grew by 6.91% during the Covid-19 period. In addition, the manufacturing sector is also reported to have the largest contribution to the national Gross Domestic Product (GDP) in the second quarter of 2021, which is 17.34%.
Then, the growth of the manufacturing sector also positively impacted investment, resulting in increased investment in the manufacturing sector. It was recorded that from January to June 2021, investment in this sector reached Rp. 167.1 trillion, an increase of 28.94% from the previous same period (Kemenperin, 2021). In this case, it can be concluded that the manufacturing sector is a sector that holds a large contribution in contributing to GDP and supporting economic growth in Indonesia. So this sector was chosen to be the object of this research, because stock returns in this sector experience uncertainty so this needs to be investigated further so that investors can ensure the returns and risks they will face if they invest in this stock. Stock returns in this sector have experienced fluctuating changes in recent years, especially in the Food and Beverage sector.
Table 1.
Average Stock Returns in Manufacturing Companies in the Food and Beverage subsector
Year The average movement of stock returns in manufacturing companies in
the Food and Beverage sub-sector
2015 - 6,10%
2016 31,41%
2017 14,66%
2018 4,76%
2019 6.57%
Source: Data processed from www.finance.yahoo.com (2022)
It can be seen in the table above that in the manufacturing sector in food and beverage companies, the stock returns given experienced quite volatile movements. In 2015 the share return distributed was in the form of minus, namely -6.10%, then experienced a fairly rapid
117 increase in 2016 to reach 31.41%. Furthermore, in 2017 it decreased to 14.66%. Until 2018 and 2019 it decreased again, touching the figures of 4.76% and 6.57%. Based on the above phenomenon, we can conclude that stock returns are uncertainty so investors must really dig up various information and analyze the information so that they are not wrong in making investment decisions. In this case, several factors are important to be considered by potential investors in assessing the company and determining which companies are able to provide satisfactory returns for potential investors if they invest, these factors can include return on assets, current ratio, earnings per share, share, and stock trading volume.
Research by Anggraini & Wijayanto (2021) which found that stock returns are partially impacted by return on assets. Research by Mangantar et al., (2020) reveals contrasting findings, namely that return on assets partially does not have a major impact on stock returns. The researcher then made the decision to carry out research, choosing return on assets as the first independent variable. Furthermore, the gaps in the research results were also obtained from the study by Sinaga et al (2020) showed the current ratio affects stock returns significantly. Meanwhile Hasanudin et al (2020) conducted the same study the current ratio had no impact on stock returns, the findings indicated. Then we decided to conduct research by selecting current ratio as the second independent variable.
The next gap research findings were likewise derived from Febrioni (2018) which found that profits per share significantly affect stock returns. While this is the case, Sausan et al (2020) claim that earnings per share have little to no impact on stock returns. As a result, researchers are interested in studying stock returns by using the independent variable earnings per share as the third variable. Finally, whereas Sustrianah (2020)found that the trading volume activity had no impact on stock return, Effendi & Hermanto (2017) found a strong and positive relationship between trading volume activity and stock return. Furthermore, researcher decided to choose the trading volume activity as moderating variable in this research. Based on the gap from the results of previous studies that have been described above, then to strengthen the results of previous research so that there is a need for a deeper review of the effect of return on assets (ROA), current ratio (CR), earnings per share (EPS) on stock returns with stock trading volume as moderating. Then this research also needs to be done to see the company's financial performance, especially in all manufacturing companies listed on the IDX.
This study is an update of the previous study in which the stock trading volume variable was introduced as a moderating variable. Additionally, all manufacturing companies listed on the Indonesia Stock Exchange were the subject of this study (2017-2021). An independent variable's influence on the dependent variable can be strengthened or weakened by a moderating variable, according to Sugiyono (2018). The use of moderating variables in this study is intended to distinguish it from other research as well as to account for the possibility that other factors may influence the link between return on assets, current ratio, and profits per share on stock returns. Because stock trading volume is directly related to a company’s price increases and stock returns, the researchers opted to use it as a moderating variable.
The purpose of this study is to identify and examine the relationship between stock returns and stock trading volume in manufacturing business and return on assets, current ratio, and earnings per share. It is hoped that this study's findings investors for investment decisions. Therefore, this research serves the interests of the company's future growth.
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LITERATURE REVIEW Signaling Theory
Signaling theory suggests the company's activities in conveying signals in the form of information to users of financial statements. Information from the signals submitted by the company is important to the investment decisions of outsiders. According to Hartono (2017) investors can learn the advantages of the firm with this signaling theory. Based on the signaling theory, a company that deliberately gives a signal to the market means that the company has good quality, so that the market can distinguish which companies are of good and bad quality. Investors can discover the advantages of the corporation with this signaling theory, because the company will provide a signal to investors in the form of significant data demonstrating the company's superiority over competing firms. Based on the signaling theory, a company that intentionally gives a signal to the market means that the company has good quality, so that the market can distinguish which companies are of good quality and which are bad. Companies must publish financial information because there is an information gap between managers (insiders) and creditors and investors (outsiders) which can reduce the companys credibility and reduce investors interest in the companys stock. Furthermore, we need important information related to the company.
According to Frederica Diana (2019) Signaling theory suggests how a company's efforts in providing or giving signals to interested parties regarding the company's financial statements. These signals may include information reporting that the firm is a better corporation than other corporations. So signaling theory is a term that refers to management actions in seeking the best view of investors on the condition of management and the future prospects for the business (Bringham & Houston, 2018). In the theory of company signals it is recommended to provide good signals and information to shareholders, companies need to prioritize the welfare of shareholders, so it is necessary to manage operational activities optimally so that they can meet the expected benefits of shareholders, even for management, employees and other internal parties.
This study uses signal theory due to the use of stock return variables, this is related to the profits or expectations desired by shareholders, expectations for company performance being able to offer a good signal to shareholders for the investment that has been made.
According to Banjarnahor Erliana (2019) a positive signal can encourage investors or potential investors to purchase company shares, the more shares purchased, the greater the number of stock trading transactions, this increase will automatically increase stock prices and will certainly encourage an increase in stock returns. An annual report is one type of information that the corporation may offer. The annual report must include data that people in need of it deem significant and necessary. External parties can use the annual report as a benchmark to judge the potential of the company and success in maximizing shareholder wealth. This shareholder wealth can be realized in the form of stock returns, stock returns are the difference received by investors from each increase in stock prices listed in the annual report
From this signal theory, the corporation is anticipated to be able to share information with interested parties about the actual state of the company, this aims to reduce and minimize doubts or misunderstandings from external parties, also so that external parties can understand and know the real condition of the company. This information is known as the indicator that the company has shared with stakeholders. With this signal theory, it is hoped that there will be no more doubts and misinformation about the company.
119 Stock Return
According to Bringham & Houston (2018) stock return is the difference between the amount received and the amount put into the investment and then divided by the initial amount invested. Meanwhile, according to Tandelilin (2017), one of the things that might inspire people is a stock return before do an investment. A stock return is a profit or return obtained by investors because they have dared to invest and bear it the risk of the investment.
According to Fahmi (2017) stock return is the profit obtained by either the company, individual or institution which is the result of the investment policy that has been carried out.
The investment itself is an investment made by investors so that they can enjoy the benefits generated by these investments, but many investors experience failure in their investments due to a lack of caution in investing. Therefore, before making an investment, it is crucial to understand how the firm's financial statements have performed. Based on Hartono (2017), stock return is a type of return that investors receive from their investments. Returns can be realized returns that have already happened or expected returns, that is, returns that have not yet happened. While the overall return is the outcome of all investments made over a specific time period.
Return on asset
The profitability ratio, as defined by Fahmi (2017) can measure overall management efficiency. This is usually represented by the profit generated from sales or investing activities. The ability of business to generate profits increases with the acquisition of this profitability ratio. Return on assets is one of the many variations of this profitability ratio.
Return on assets, which is defined by Bringham & Houston (2018) as the result of dividing a company's net profit by its total assets, is the return provided by all assets. Return on assets (ROA) is the ratio used to determine whether or not an investment can generate the desired return or profit. The investment above consists of establishing corporate property (Fahmi, 2017).
Current ratio
Fahmi (2017), company liquidity is often referred to as short-term liquidity, a definition of its ability to fulfill or pay short-term commitments easily and on schedule.
Sujarweni (2019) stated the liquidity ratio is a metric used to assess a company's ability to meet its short-term financial obligations, especially in the form of short-term loans. This ratio is removed this classified into four types, namely the current ratio, quick ratio, cash ratio, and working capital for the ratio of capital to total assets are the four types of liquidity ratios.
Hantono (2018) stated the current ratio is used to determine the amount of current liabilities whose payments are supported by current assets. However according (Sulindawati et al, 2017), the current ratio compares a company's current assets to its short-term debt. The current ratio is a ratio that can be used to estimate a company's capacity to settle short-term debt using current assets held by the company Sujarweni (2019).
Earnings per share
Based on Hantono (2018) earnings per share measures how much of a company's capability for net income is contained in each outstanding share. According to Sukamulja (2019) EPS is the ratio used to assess how much a company's capacity to generate net income is contained in each outstanding share. Earnings per share (EPS) as defined by Tandelilin (2017) is data from a company that shows the level or quantity or amount of net profit generated by the company and available for distribution to all shareholders. Earnings per share (EPS) according to Hery (2018) is a ratio to measure the success of company management in generating profits for its shareholders. Earnings per share highlights the
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relationship between the amount of net profit and the portion available to investors in each company. Investors can usually use earnings per share figures to help them make an investment decision among the alternatives available for making a decision.
Trading volume activity
According to Sutrisno (2017) stock trading volume can be used to measure stock trading volume in order to observe and understand how the capital market responds to various pieces of information. According to Hartono (2017) the total number of shares exchanged per day is referred to as stock trading volume. So that it can be interpreted that stock trading volume is the quantity of shares sold during a specific time period, and the capital market's stock trading volume fluctuation can be utilized as a signal to assess and study the behavior in the stock exchange of investors. Stock trading volume is a tool used to be able to describe the reaction of the capital market to various information carried out through the parameters of the movement of stock trading volume that occurs in the market. This stock trading volume is usually referred to as a variation of the event study in terms of its function. Where stock trading activity may be used as a tool to test the efficient market hypothesis, and also serves as an indicator to determine whether a capital market is weak or strong. This stock trading volume can be said as the total number of shares, bonds, or futures contracts traded in a certain period or period (Sutrisno 2017).
Hypothesis Development
The effect of return on asset on stock return
ROA (Return On Assets) is a ratio that can affect the rate of return on shares obtained by investors on their investments. Because the greater this ratio, the larger the firm's profit may generate from managing its assets, which will increase investor confidence and trust in the company which will affect rising stock prices and stock returns (Aryaningsih et al, 2018).
According to Anggraini & Wijayanto (2021), the return on assets significantly and positively impacts stock return. From this explanation, the hypothesis developed is as follows.
H1: Return on assets has a significant and positive effect on stock returns
The effect of current ratio on stock return
According to Febrioni (2018) the current ratio measures how well a corporation can use its current assets to pay for its current liabilities. If the current ratio is low, it tends to be believed that there is a problem with the company's liquidity. But if the current ratio is excessive, then it is also considered bad because it means that there are unused funds which in the end can disrupt the corporation's income or profits, so investors need to understand this current ratio in order to be able to select the appropriate corporation that can provide a satisfactory return. From this explanation, the hypothesis developed is as follows.
H2: Current ratio has a significant and positive effect on stock returns
The effect of earning per share on stock return
Earning per share is net income per share that investors will receive. The higher the EPS received by investors, the greater the dividends that investors will receive. Dividends are an important factor that investors look for in investing, now dividends are what causes investors to want to have many shares of a company so that earning per share becomes one of the crucial elements that may have an impact on stock returns distributed by companies (Hakim & Abbas, 2017) . According to research by Sinaga et al (2020) the findings indicate that the earning per share positively influences stock returns. According to Anggraini &
121 Wijayanto (2021) in his research, it shows that the return on stocks is significantly influenced by earnings per share. From this explanation, the hypothesis developed is as follows.
H3: Earnings per share have a significant and positive effect on stock returns
Trading volume activity moderate the effect of return on asset on stock return
According to Mayuni & Suarjaya, (2018) return on assets is a ratio that can affect the rate of return on shares obtained by investors on their investments. the larger the firm's profit may generate from managing its assets, which will increase investor confidence and trust in the company which will affect rising stock prices and stock returns
The quantity of shares traded on the stock market is referred to as the stock trading volume (Hartono, 2017). The announcement of information regarding positive ROA will entice investors to purchase shares, increasing the amount of stock trading, with many requests or an increase in the volume of buying shares, it will simultaneously have an impact on rising stock prices so that an increase in stock return will accompany it. But, if there is a negative return on asset it will reduce investor excited for investments, this will decrease stock prices and also reduce stock returns. Research’s findings by Effendi & Hermanto (2017) shows that stock trading volume positively affects stock returns. From this explanation, the hypothesis developed is as follows.
H4: Stock trading volume moderates the effect of return on assets on stock returns
Trading volume activity moderate the effect of current ratio on stock return
According to Astutik & Anggraeny (2019) According to Febrioni (2018) the current ratio measures how well a corporation can use its current assets to pay for its current liabilities. If the current ratio is low, it tends to be believed that there is a problem with the company's liquidity. According by Hartono (2017) the quantity of shares traded on the stock market is referred to as the stock trading volume. The announcement of information regarding positive current ratio will entice investors to purchase shares, increasing the amount of stock trading, it will simultaneously have an impact on rising stock prices so that an increase in stock return will accompany it. Vice versa, if there is a negative current ratio, it will reduce investor’s excited for investments and also decrease stock prices and reduce stock returns. Research’s findings by Effendi & Hermanto (2017) shows that stock trading volume positively affects stock returns. From this explanation, the hypothesis developed is as follows.
H5: Stock trading volume moderates the effect of the current ratio on stock returns
Trading volume activity moderate the effect of earning per share on stock return
According to Roesminiyati et al (2018) earnings per share is company’s net profit from company’s each outstanding shars. Earnings per share can influence investors to invest, because if the company has a large profit per share, investors will be interested to purchase the company's shares.
According to Hartono (2017) the quantity of shares traded on the stock market is referred to as the stock trading volume. The announcement of company’s earning per share is large, this will entice investors to purchase shares, increasing the amount of stock trading, then it will rising stock prices and increase stock return. But, if the company’s earning per share is low, this will reduce investor excited for investments, it will decrease stock prices and reduce stock returns. Research’s findings by Effendi & Hermanto (2017) shows that stock trading volume positively affects stock returns. From this explanation, the hypothesis developed is as follows.
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H6: Stock trading volume moderates the effect of earnings per share on stock returns
METHODS
The population of this study use 191 manufacturing business listed on the Indonesia Stock Exchange (IDX) 2017 through 2021. This study is quantitative and includes a total of 191 manufacturing business listed on the Indonesia Stock Exchange for 2017 through 2021.
Purposive sampling was used in this study's sampling process. We get total sample of 56 manufacturing enterprises listed on the IDX and 280 pieces of data. The financial reports used for the research can be found on the IDX's official website as secondary data (www.idx.co.id) then the researchers presented the data in a data tabulation. Using EViews 9, panel data regression was used to evaluate this investigation. This research start from 2017 to 2021 aims to keep the research and references up to date and the study’s result can describe the situation of five years last. The researcher choose the manufacturing sector as the research‘s object, because this sector is a large scale company and has an important role in economic growth.
Definition and Measurement of Variabel Dependent Variable
The dependent variable used is stock returns. Stock return is the level of profit obtained by investors for their investments in a company (Hartono, 2017). Stock returns can be formulated as follows:
Independent Variables
The dependent variable experiences changes as a result of the independent variable, which likewise influences the dependent variable (Sugiyono, 2018). Therefore, the study’s three independent variables were return on assets, current ratio, and earnings per share.
Return on assets (ROA), according to Anwar (2019), is a statistic that shows a company's ability to produce profits or net income from its assets. To measure this variable can be used the formula:
A measure of a company's capacity to meet its short-term obligations with its current assets is called the current ratio (CR) (Anwar, 2019). To measure this variable can be used the formula:
Earnings per share (EPS) is the amount of profit that will be given to shareholders for each share they own (Fahmi, 2017). The formula used to calculate EPS is:
Stock return = (Pt – Pt-1) / Pt-1
ROA = (earning after tax/ total asset) x 100%
CR = (current asset / current liabilities) x 100%
EPS = (earning after tax / listed share) x 100%
123 Moderating Variable
The moderating variable in this study is trading volume activity (TVA). According to Hartono (2017) The total number of shares exchanged over a specific time period is known as stock trading volume. Indicators can be used to measure changes in the amount of stock trade on the stock market to assess and study the behavior of investors in the capital market. The formula for measuring stock trading volume activity is as follows:
Data Analysis Techniques
Descriptive Statistical Analysis
Descriptive test analysis utilized to provide information about the characteristics or characteristics of the main research variables. Descriptive statistical analysis aims to describe or describe research data which includes the maximum (highest), minimum (lowest), average (mean) and standard deviation values (Sugiyono, 2018).
Normality test
According to Ghozali & Ratmono (2017) the normality test aims to determine whether the research data to be analyzed has been distributed normally or not. In order to avoid data bias, The study's data must follow a normal distribution. The Jarque Bera test is the procedure used for the normalcy test.
Multicollinearity Test
According to Ghozali & Ratmono (2017) This test looks to see if there is a multicollinearity issue, specifically whether the independent variables in the regression model are correlated.
Heteroscedasticity Test
According to Ghozali & Ratmono (2017)The test looks to see if the residuals from one observation to the next differ or have different variances.
Autocorrelation Test
This is a test carried out in order to find out whether the research regression model has a connection between the residuals from period t and those from period prior. Sequential observations made throughout time that are connected to one another cause the autocorrelation problem (Ghozali & Ratmono, 2017).
Panel Data Regression Analysis
The form of regression analysis utilized in research to identify the nature and magnitude of the effects of two or more independent variables (independent) on the dependent variable is known as multiple linear regression analysis. EViews 9 software was used to analyze the multiple linear regression analysis used in this study. Panel data regression was used in this study and was required to see and decide which approach was the most appropriate for estimating panel data.
TVA = (number of shares traded / listed share) x 100%
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The following multiple linear regression equation is formulated as follows:
Equation 1:
Equation 2:
Description:
Y = Stock return X1 = Return on asset X2 = Current ratio X3 = Earning per share
Z = Trading Volume Activity e = error
This study uses moderating variables, according to Ghozali & Ratmono (2017) moderating regression analysis or known as moderated regression analysis (MRA) is a special regression used for multiple linear regression which has a regression equation in the form of interaction elements, namely new variables that arise as a result of multiplication.
between two or more independent variables. The use of MRA in this study is because this study uses a moderator variable, so that the panel data regression equation for the moderator variable is to use the moderated regression analysis (MRA) equation.
Hypothesis Test Partial Test (t)
According to (Sugiyono, 2018) the partial test determine whether the independent variable has real or no effect on the dependent variable. The hypothesis is not accepted if the significance’s value > 0.05. In contrast, if the significance value < 0.05, the hypothesis is accepted.
Determination Test (R2)
Determination test is a test meant to see how well the research model can explain the dependent variable. The value used is the value of R square because it is believed to be able to evaluate the research regression model (Sugiyono, 2018).
RESULTS
Descriptive Statistical Analysis
In table 2 explains the descriptive statistical analysis as follows.
Table 2.
Descriptive Statistical Analysis
Mean Maximum Minimum Std. Deviasi N
Y 0,0185 0,6833 -0,4941 0,2280 275
X1 8,0240 24,3000 0,0500 6,0385 275
X2 261,9885 726,0000 61,4000 165,8742 275
X3 161,8187 581,9000 0,2000 162,7376 275
Z 0,2357 0,5258 0,0028 0,1497 275
X1*Z 2,0059 12,7789 0,0001 2,2414 275
X2*Z 61,1231 316,552 0,2021 55,9075 275
Y = α + β1X1 + β2X2 +β3X3 + β4Z + β5X1*Z + β6X2*Z + β7X3*Z + e Y = α + β1X1 + β2X2 +β3X3
+ e
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Mean Maximum Minimum Std. Deviasi N
X3*Z 46,9807 306,0100 0,0006 68,0749 275
Source: Data processed with EViews 9 (2022) Description:
Y = Stock return X1 = Return on asset X2 = Current ratio X3 = Earning per share
Z = Trading Volume Activity e = error
Classic Assumption Test
EViews 9 was used to conduct the normalcy test. The Jarque Bera follow probability value (JB), which is based on the normality test following the outlier test, was 0.769424 >
0.05, indicating that the data utilized are normally distributed. It can be inferred that the independent variable is free of the multicollinearity issue if VIF is less than 10. Harvey’s test was used in this study's heteroscedasticity test. Harvey test results show that the probability value is 0.1683 > 0.05. This indicates that there are no issues with heteroscedasticity in the research data. The panel data regression table's autocorrelation test findings show that Durbin Watson's value is 1.956188. Given that this number lies between -2 and +2, it may be said that the regression model is devoid of autocorrelation issues.
Panel Data Regression Test
The following table displays the results of multiple linear regression based on tests that were run using the Fixed Effect Model (FEM):
Table 3.
Estimation Results of Panel Data Regression Fixed Effect Model Equation I Variable Coefficient Std. Error t-Statistic Prob.
C -0,3373 0,0374 -9,0160 0,0000
X1_ROA 0,0269 0,0030 8,7535 0,0000
X2_CR 0,0002 0,0001 2,2718 0,0241
X3_EPS 0,0004 0,0001 3,1149 0,0021
Effects Specification Cross-section fixed (dummy variables)
R-squared 0.6118 Mean dependent var 0.0185 Adjusted R-squared 0.5098 S.D. dependent var 0.2280 S.E. of regression 0.1596 Akaike info criterion -0.6468 Sum squared
residual 5.5300 Schwarz criterion 0.1159 Log likelihood 146.9454
Hannan-Quinn
criterion -0.3407
F-statistic 6.0005 Durbin-Watson stat 1.9561 Prob(F-statistic) 0.0000
Source: Processed by EViews 9 (2022)
The following is the regression equation I in this study:
Y = -0.3373 + 0.0269 (X1) + 0.0002 (X2) + 0.0004 (X3)
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Description:
Y = Stock return X1 = Return on asset X2 = Current ratio X3 = Earning per share
Z = Trading Volume Activity e = error
Table 4.
Estimation Results of Panel Data Regression Fixed Effect Model Equation II Variable Coefficient Std. Error t-Statistic Prob.
C -0.4699 0.0561 -8.3672 0.0000
X1 0.0136 0.0049 2.7353 0.0068
X2 0.0004 0.0001 2.4952 0.0133
X3 0.0003 0.0002 2.2052 0.0285
Z 0.9688 0.2231 4.3407 0.0000
X1Z 0.0287 0.0164 1.7497 0.0816
X2Z -0.0010 0.0006 -1.6356 0.1034
X3Z -0.0007 0.0006 -1.2764 0.2032
Effects Specification Cross-section fixed (dummy variables)
R-squared 0.6684 Mean dependent var 0.0185 Adjusted R-squared 0.5734 S.D. dependent var 0.2280 S.E. of regression 0.1489 Akaike info criterion -0.7753 Sum squared resid 4.7240 Schwarz criterion 0.0400 Log likelihood 168.6077 Hannan-Quinn criter. -0.4480 F-statistic 7.0386 Durbin-Watson stat 1.9833 Prob(F-statistic) 0.0000
Source: Processed by EViews 9 (2022)
The following is the regression equation I in this study:
Y = -0,4699 + 0,0136 (X1) + 0,0004 (X2) + 0,0003 (X3) + 0,9968 (Z) + 0,0287 (X1Z) – 0,0010 (X2Z) – 0,0007 (X3Z)
Description:
Y = Stock return X1 = Return on asset X2 = Current ratio X3 = Earning per share
Z = Trading Volume Activity e = error
127 Hypothesis testing
The summary results of hypothesis result in the table below:
Table 5.
Hypothesis Test Results
Variables Coefficient Probability Prediction
C -0.3373 0.0000 +
X1 0.0269 0.0000* +
X2 0.0002 0.0241* +
X3 0.0004 0.0021* +
Z 0.9688 0.0000* +
X1*Z 0.0136 0.0068 +
X2*Z 0.0004 0.0133* +
X3*Z 0.0003 0.0285 +
Source: Data processed with EViews 9 (2022)
*significant level 5%
X1: Return on asset, X2: Current ratio, X3: Earning per share, Z: Trading volume activity
Based on table 5, it can be seen that the probability is 0.0000 and the value of the coefficient constant is -0.337376. Additionally, the value of the X1 ROA variable is 0.0000 0.05, indicating that return on assets (X1) significantly and positively influences stock returns (Y). Furthermore, the current ratio (X2) significantly and positively influences stock returns, as indicated by the probability of 0.0241 0.05 for the X2 CR variable (Y). Additionally, the probability of the X3 EPS variable is 0.0021 0.05, indicating that earnings per share (X3) significantly and positively influences stock returns (Y). According to equation I, table 8 adjusted R2 coefficient of determination has a value of 61.18%. This means that the independent variable in explaining the stock return variable (Y) is only 61.18%, while other factors outside this study’s scope contribution to the remaining 38.82%.
Table 5 shows that the probability is 0.0000 and the coefficient constant value is - 0.3971. Furthermore, the stock trading volume (Z) does not moderate the impact of return on assets (X1) on stock returns because the X1 ROA variable has a probability of 0.0068 >
0.000. (Y). However, the current ratio's (X2) effect on stock returns (Y) can be moderated by the stock trading volume (Z), according to the coefficient of 0.0004 and probability of 0.0133
< 0.0241 for the X2 CR variable. Furthermore, the X3 EPS variable has a coefficient of 0.0003 and a probability of 0.0285 > 0.0021, indicating that the effect of earnings per share (X3) on stock returns is not moderated by the volume of stock trading (Y). Equation II from table 9's coefficient of determination (Adjusted R2) displays a value of 57.34%. Accordingly, 66,84% of the stock return variable (Y) can be explained by the independent variable, and the remaining 33,16% can be explained by variables not included in this study.
DISCUSSION
The effect of return on asset on stock return
Return on asset (X1) has a coefficient value of 0,0269 and a probability of 0.0000 <
0.05, which indicates that it significantly and positively influences stock returns, according to the findings of partial hypothesis testing (Y). Earlier studies validate the findings of this study by Laulita & Yanni (2022), Rahmawati & Putra (2022). The ROA (Return on Assets) ratio
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can have an influence on the rate of return that investors see on their shares. Due to the fact that the higher this ratio, the more profit the firm will get from managing its assets, there will be an increase in investor confidence and trust in the company, which will result in higher stock prices and stock returns (Aryaningsih et al (2018). The better a firm can create net income from utilizing all of its assets, the greater the return on assets (ROA) it generates.
This will draw investors' attention and encourage them to invest, increasing the company's stock price and boosting its stock return.
The effect of current ratio on stock return
The current ratio (X2) is determined to have a significant and positive impact on stock returns with a coefficient value of 0,0002 and a probability of 0.0241 < 0.05. (Y). Prior studies validate the findings of this study by Rahmawati & Putra (2022) and Yuliarti &
Diyani (2018). According to Febrioni (2018), the current ratio measures a company's capacity to use its current assets to pay its current liabilities. If the current ratio is low, it is frequently assumed that the company's liquidity is an issue. However, if the current ratio is too high, then it is also considered bad so it means that there are unused funds which in the end can disrupt the company's financial performance or profits, so investors must know this current ratio in order to be able to choose the right corporation that can provide a favorable return.
The current ratio indicates how the corporation can use its current assets to pay off short-term debt. The test results above show a positive relationship between information about a company's current ratio and the rate at which its stock returns are calculated; the results also show that the better a please company's current ratio, the more investors it will draw in and raise stock prices, which will in turn increase stock returns.
The effect of earning per share on stock return
Earnings per share (X3) has a probability of 0.0021 < 0.05 and a coefficient value of 0,0004. According to the findings of the partial hypothesis, earning per share (X3) has a significant and positive influence on stock returns (Y). Earlier studies verify this study’s findings by Laulita & Yanni (2022) and Almira &Wiagustini (2020). Net profit per share is the value that investors will be received. The amount of dividends investors will receive will increase when EPS for investors rises. Dividends are a crucial feature that investors look for when investing, and because it make investors want to own a large number of shares of a company, EPS becomes one of the factors that may affect stock returns reported by companies Hakim & Abbas (2017). The business's performance health is represented by its earnings per share; the higher the earnings per share, the better the company's ability to produce net income for each share it issues. The company's net profit per share will undoubtedly be in the spotlight as investors consider their options; if the EPS is high, a lot of investors will be interested in making investments, which will have an impact on rising stock prices and further boost the company's stock returns.
Trading volume activity moderates the effect of return on asset on stock return
According to the X1*Z variable's coefficient value of 0,0136 and probability of 0.0068 > 0.0000, the influence of return on assets (X1) on stock returns (Y) in manufacturing business listed on the IDX for the 2017–2021 period is not moderated by stock trading volume (Z). Earlier studies verify the findings of this research by Putri et al (2021) and Sustrianah (2020). This indicates that when the return on assets (ROA) is high, stock trading volume (TVA) cannot improve stock returns, and when the ROA is low, TVA cannot decrease stock returns. According to signal theory, investors typically use the information supplied by the company to make choices, However, in this research, investors no longer pay attention to the company's stock trading volume (TVA) variable if there is information about the return on assets (ROA) generated by the company, whether it is good news or bad news,
129 so the stock trading volume cannot affect the company's stock transactions. The relationship between return on assets (ROA) and stock returns in this study therefore cannot be impacted by the volume of stock trading.
Trading volume activity moderates the effect of current ratio on stock return
According to the X2*Z variable's coefficient value of 0,0004 and probability of 0.0133 < 0.0241, the influence of current ratio (X2) on stock returns (Y) in manufacturing business listed on the IDX for the 2017–2021 period is moderated by stock trading volume (Z). Prior studies confirm this study’s findings by Damaris & Poerwati (2022) and Murtaza
& Aryan (2021). According to signal theory, investors generally use all information supplied by the company to make decisions, This study, information on the company's current ratio to the number of shares traded by the company is announced, with either positive or negative implications. will affect how investors behave while purchasing and selling shares. The acquisition of the company's shares will increase if the information is positive, which will raise the stock price and stock returns at the same time. In this research, the volume of stock trading can reduce the impact of the current ratio on stock returns. This demonstrates that when the current ratio is high, stock trading volume (TVA) can boost stock returns. On the other hand, when the current ratio is low, stock trading volume (TVA) might lower stock returns.
Trading volume activity moderates the effect of earning per share on stock return According to the X3*Z variable's coefficient value of 0,0136 and probability of 0.0068 > 0.0000, the influence of earnings per share (X3) on stock returns (Y) in manufacturing business listed on the IDX for the 2017–2021 period is not moderated by stock trading volume (Z). Earlier studies verify the findings of this research by Putri et al (2021), Sustrianah (2020). As a result, stock trading volume (TVA) cannot improve stock returns when earnings per share (EPS) are high, and stock trading volume (TVA) is not able to reduce stock returns when earnings per share (EPS) are low. In signal theory, the information released by the company will usually be used by investors to make decisions, but in this study, when there is information about earnings per share (EPS) generated by the company, whether it is good news or bad news, investors no longer pay attention variable stock trading volume (TVA). Therefore, in this study, stock trading volume cannot influence the impact of earnings per share (EPS) on stock returns.
CONCLUSION
The researcher can draw the following conclusions from the analysis and justification provided in the prior chapters. Earnings per share (EPS) partially has a significant and positive impact on stock returns with a probability of 0.0021 < 0.05, return on assets (ROA) has a significant and positive impact on stock returns with a probability of 0.0000 < 0.05, current ratio (CR) individually has a significant and positive impact on stock returns with a probability of 0.0241 < 0.05, W]with a probability value of 0.0068 > 0.0000, the volume of stock trading does not moderate the impact of return on assets (ROA) on stock returns. With a probability level of 0.0133 to 0.0241, stock trading volume moderates the impact of the current ratio (CR) on stock returns, but with a probability level of 0.0285 > 0.0021, stock trading volume does not moderate the impact of the earnings per share (EPS) on stock returns.
From the conclusions that the researchers describe above, the following suggestion for companies to submit good financial reports and demonstrate the company’ ability and good performance convey relevant information so that the company can gain the trust of potential
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investors. Then for investors, before making an investment, it is advisable to observe the company's capacity to produce profits and fulfill its obligations, which can be in the financial report of firm, so that investors can decide which company is more profitable to invest in.
Last, for the next researcher who want to examine topics related to stock returns, they can examine other independent variables that are thought to be able to influence stock returns.
Then, it is also recommended to expand the research sample by increasing the population, not only in the manufacturing sector but also in other sectors so that the research results are more general and it is also recommended to increase the research period so that more samples are studied in order to obtain results. research that tends to be more general in nature. This research is limited to companies in the manufacturing sector on the Indonesia Stock Exchange for the 2017-2021 period, so for further research a wider sample scope and a longer period are needed in order to obtain better and more general research results.
The contribution of this research is to provide information on the condition of return on assets, current ratio, earnings per share, trading volume of the company's shares, and stock returns that can be used as consideration for future company growth. This study uses moderating variables which are rarely used in previous studies.
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