JURNAL AKUNTANSI DAN BISNIS
Jurnal Program Studi Akuntansi
Available online http://ojs.uma.ac.id/index.php/jurnalakundanbisnis
Effectiveness Of Financial Reporting On Share Prices In Mining Public Listed Companies On The Indonesian Stock
Exchange (IDX)
Taskurun1*, & Muhammad Azis2
1Jurusan Magister Akuntansi , Fakultas Ekonomi dan Bisnis, Universitas Airlangga, Indonesia
2Jurusan Pendidikan Akuntansi, Fakultas Ekonomi dan Bisnis, Universitas Negeri Makassar, Indonesia
Submitted: June 2, 2023; Reviewed: October 9, 2023; Accepted: October 25, 2023
*Coresponding Email: [email protected]; [email protected]
Abstract
Financial statement information is one of the important factors in assessing the stock price of a company, many investors before deciding to invest their capital in the company they want to go to first look at financial information, so this study focuses on analyzing the effect of PM, ROA, CR, SR, and PER on the stock price of a coal & lignite mining company on the IDX in 2018- 2022. The focus of this study uses three grand theories, namely value theory, market finance theory, and market efficiency theory, each of which explains the effect of financial statement information on stock price fluctuations. The results of the analysis show that PM has a negative and important effect on stock prices, while ROA and PER have a positive and important effect. CR and SR have no significant influence. The coefficient of determination shows that these variables only explain 30% of the influence of stock prices, the rest are influenced by other factors. The implication of this study is that companies need to improve ROA and PER for better stock performance. Limitations of this study include data quality, external factors, and methodology.
Keywords: Profit Margin; Return On Aset; Current Ratio; Solvency Rasio; Price Earning Ratio;
Stock Price
How to Cite: Taskurun. & Azis, M. (2023). Effectiveness Of Financial Reporting On Share Prices In Mining Public Listed Companies On The Indonesian Stock Exchange (IDX). Jurnal Akuntansi dan Bisnis : Jurnal Program Studi Akuntansi. 9 (2): 93-108
INTRODUCTION
The coal and lignite mining sectors play an important role in the Indonesian economy, and financial information provided by companies in the sector impacts the company's employment process on their share prices. Several previous studies have tested the effect of financial information on a company's stock price.
Financial information presentation includes several reports, namely income statements, balance sheet statements, cash flow statements, and other reports that are important for investment decision making, (Mandika, 2017). Investors rely on financial information to assess the value of a company's stock. In an efficient market, stock prices reflect publicly available financial information which, therefore, evaluating the financial work processes of a company is a very important concern for investors (Arnova, 2016). Positive financial performance, such as stable and high earnings, positive cash flow, and strong financial conditions tend to increase stock prices. Conversely, poor financial performance, such as losses, negative cash flow, and weak financial condition, can lead to a decline in stock prices (Subakti et al., 2021). As a result, it is critical for companies to manage and report financial information accurately and completely to enable investors to make informed investment decisions. Inaccurate or incomplete financial information can lead to errors in valuing a company and result in stock price volatility (Prihadi, 2019). In the coal and lignite mining sector is one of the most urgent sectors, given Indonesia's high economic dependence on this industry. In the era of advanced information and technology, investors and market participants need accurate and transparent information from companies to evaluate and make the right investment decisions. Thus, research investigating the effect of financial information on share prices in coal and lignite mining companies can make a significant contribution to improving financial performance and building investor confidence (Rumondang, A., Sudirman & Sitorus, 2020).
When investors decide to take a company's sham, almost all investors use financial ratios to consider buying shares by looking at the company's financial statements. Ratio analysis helps investors know the advantages and disadvantages of a company. This study uses various ratios, including using ratios such as ROA, PM, CR, SR and EPS. This ratio is included in the category of factors that affect stock prices (Feng, 2021; Oware et al., 2022). Before investing in the capital market, investors generally check in depth the condition of a company and rely on high-quality information or financial statements. However, challenges can arise that affect the value and success of the company. Therefore, understanding the extent to which these factors affect the company is critical to developing strategies to address these issues.
Some studies provide data on differences in the impact of financial report information on stock prices that are the object of this study, however, most of these studies conclude that financial information does affect stock prices. For example, Dawam et al., (2021); Erick, (2021) conclude that ROA and DER have no effect while EPS has an effect on stock price. On the contrary, Purwitasari et al., (2021) the research findings concluded that ROA &; DER have a positive and important effect on stock prices which is a research project, while earnings per share (EPS) has no effect However, in another study by Wijayanto (2018), it was found that EPS has an effect on stock prices, while DER has no effect at all. Based on the inconsistencies in the findings in the study, researchers then decided to add other variables that were considered to have an influence on stock prices.
Finally, in order to conclude, financial information has an effect on the share price of coal and lignite mining companies listed on the IDX The performance pattern of a company's finances, including profitability, capital structure, company
size, and leverage, has the potential to affect stock prices. Therefore, it is important for a company to present accurate and transparent financial information so that investors make material to evaluate and make the right decisions. In addition, recent research has begun to explore other possible impacts related to financial information on this sector.
LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT
Value Theory: This theory argues that stock prices reflect a company's intrinsic value. In the coal and lignite mining industry, physical assets such as coal reserves, mining land, and mining facilities have a high value. Therefore, the PM (Price to Book Value) ratio can reflect the extent to which the market appreciates these assets owned by the company (Wijayanto, 2021)
Corporate Finance Theory; Coal and Lignite Mining: This theory studies what increases and decreases stock prices in the coal and lignite mining industry. The variable ROA (Return on Assets) can reflect the utilization of company assets well in generating profits. CR (Current Ratio) can provide an indication of a company's liquidity and ability to service short-term debt, DER can reflect the amount of liabilities a company has fulfilled as well as the associated financial risks. PER (Price Earnings Ratio) can describe investor expectations for company management and opportunities for profit increase in the next period (Sari, 2020) Market Efficiency Theory: This theory states that stock prices describe all the information available in the market. In this context, variables such as ROA, CR, DER, and PER can present information about a company's performance, liquidity, debt levels, and profit growth potential. Studies conducted by (Sabrina &; Lestari P, 2020); (Susanti &; Wirakusuma, 2022) also attribute these variables to market efficiency.
The Effect of Profit Margin on Stock Prices
Company profits, which are a percentage of profits net of expenses generated by the company from the sale of its products or services net of operating expenses, can have an important effect on the share price of the company. The following is an explanation of the effect of profit margin on stock prices Financial Performance Indicators: Profit margin acts as one of the main indicators of financial performance that investors and analysts will assess a company as profitable. A large profit margin indicates efficient operation and the ability to generate greater profits. This indicates the financial well-being of the company and can improve market perception. High profit margins consistently instill confidence in investors, indicating effective management and successful business strategies. This can strengthen future prospects, thereby increasing investor interest in the stock and as a result, causing an increase in the share price.
The Effect of Return on Assets on Stock Prices
ROA is a comparison to see a company is able to make a profit from the use of its assets. ROA provides relevant information for investors when assessing a company's financial progress and influencing share prices. As an indicator of financial performance, ROA is used by investors and analysts to assess how efficiently a company earns profits through the utilization of its assets. (Anachedo et al., 2021) a large ROA figure explains that a company can benefit in greater value with the assets owned by the company, which reflects strong financial performance. (Arkan, 2016) This positive perception of the company's profit- making ability instills confidence in investors. A consistently high ROA reinforces investor confidence in effective management and successful business strategies.
Investors tend to favor companies with solid and sustainable financial performance. (Ibeanu &; Egbunike, 2023) A large ROA reinforces investors'
confidence in the company's long-term prospects, resulting in increased investment or retention of existing investments in the company's stock. Increased investor confidence can encourage high stock sales and further increase stock prices on the stock exchange.
The Effect of Current Ratio on Stock Price
The current ratio is an indicator used in evaluating the extent to which a company can meet obligations within no more than 1 year with available resources. A large current asset ratio reflects the financial strength of a company and can have an effect on the price of shares offered on the stock exchange.
Companies that have high current ratios tend to be rated positively by investors, potentially leading to an increase in stock price (Andoko &; Winson, 2021). The company's financial strength can be seen from the high current ratio, which indicates that the company has assets that are liquid enough to meet obligations in less than one year. This gives investors confidence in the company's financial position and its ability to manage operations effectively. Investors generally give better evaluations to companies with high current ratios, which can have a positive impact on stock prices. (Obulemire, 2019) A stable and healthy Current Ratio increases investor confidence in the company's liquidity management. This can have an effect on the number of shares demanded and the subsequent share price, because investors tend to lean towards companies with an adequate Current Ratio to mitigate the risk of the company's inability to pay debt in the short term.
The Effect of Solvency Ratio on Stock Price
The solvency ratio is a measure of an indicator of a company in paying off debt in less than one year. A high solvency ratio indicates financial stability and can have an impact on stock prices. Generally, investors have a positive view of a company that has a high solvency ratio, which has the potential to cause an increase in stock prices. (Rivaldi &; Priyanto, 2023) The large solvency ratio figure tells us that the company can pay off its debts. By having a healthy and stable solvency ratio, the company can instill confidence in investors regarding the company's financial sustainability and its ability to deal with long-term risks.
Effective management in handling corporate debt and financial risks is also reflected in a high solvency ratio. Increased investor confidence can have an effect on the number of shares demanded on the stock exchange which increases upward stock price movements.
The Effect of Price-to-Earnings Ratio on Stock Price
The price-to-earnings (P/E) ratio compares a company's share price to the earnings of each stock slot, providing insight into stock valuation. The ratio can have an effect on the stock price. A large P/E ratio explains that investors are willing to pay a larger premium for each unit of profit generated by the company, potentially reflecting high expectations for future profit growth. (Hutabarat &;
Flora, 2015) Conversely, a low P/E ratio may indicate an undervalued stock or declining profits for the company. This perception of valuation, whether high or low, can affect the stock price. The P/E ratio is also used to compare a company's stock valuation with its competitors in the same industry. If a company's P/E ratio is lower than that of its competitors, this can be considered an attractive investment opportunity. Investors often view companies with low P/E ratios as undervalued stocks with the potential for impending price increases. All of this will increase the stock price of a company.
Based on the study of the theory above, the development of temporary conjectures in this research can be outlined as follows:
H1: There is an important relationship between Profit Margin (PM) and the share price of coal mining companies.
H2: There is an important relationship between Return on Assets (ROA) and the share price of coal mining companies.
H3: There is an important relationship between current assets (CR) and the share price of coal mining companies.
H4: There is an important relationship between solvency (SR) and the share price of coal mining companies.
H5: There is an important relationship between the price-earnings ratio (PER) and the share price of coal mining companies.
RESEARCH METHODS Types of Research
The study is quantitative research using an explanatory approach. The purpose of the focus of this study is to relate the above variables. This study method uses numerical data and statistical analysis to answer the above allegations proposed.
This study used a panel data design, which involves collecting data samples at specific time intervals. The research sample consists of companies manufacturing mining and coal subdivisions listed on the IDX using the years 2018-2022. The sample in this study used porpusive sampling method Secondary data used as the focus of the study was obtained from annual report information available on the IDX Website
Population and Sample
This study focused on analyzing the financial statements of coal and lignite mining subdivision companies with conditions listed on the IDX for 2018-2022 To select samples, researchers used the purposive sampling method. This method involves selecting companies with objectives and criteria for limiting samples including:
a) Companies must operate in the coal and lignite mining sector and be listed on the IDX for the years 2018-2022
b) Annual financial statements that have gone through an audited process must be available and used in Rupiah from 2018 to 2022. In addition, the company must also have data on the closing price of shares for the same period.
Tabel 1. Sampel
No Information Total
1. Number of companies During the period 2018-2022, there were a number of coal and lignite mining manufacturing companies
listed on the IDX 140
2. Companies with the condition that they always publish their annual reports with complete, accurate and measurable data. (65)
Number of companies studied in 2018-2022 75
Research Design H1
H2
H3
H4
H5
Pict 1 Conceptual Framework Operational Definition and Variable Measurement
Table 2. Definition of Operations and Measurement of Variables
No Variabel Defenisi Pengukuran Sumber
1. Profit Margin (X1)
PM is the
company's ability to cover revenue by using its net
income.
Sa'adah, L.
(2020).
2. Return On Aset (X2)
ROA is a measure of the company's efficiency in utilizing its assets
to generate profits. Arum, R. Et.al
(2022).
3. Current Rasio (X3)
CR (Current Ratio) is a ratio used as a
measure of
performance in paying off debt less than a year using current assets owned by the company
Zaenal, M. H.
(2020).
4. Solvency Rasio (X4)
SR is to measure the company's performance to meet debts in a long period or a long time
Astuti, S. Et,.al (2021).
Return On Assets
Current Asset
Solvency Ratio
Price Earnings Ratio
Price Stock Profit Margin (PM)
5. Price Earnings Rasio (X5)
Ratio used as a measure of the amount of profit distributed to the stock price per stock slot is on the stock exchange
Darmawan, M.
(2020).
6. Share price (Y)
Share price is the value of the stock after the final closing on the stock exchange
Nilai Price Market End Year
(Agung et al., 2022) &
Purba, R., Nugroho, L., Et.al (2023) Data Collection Techniques
This study technique uses a method of data collection called documentation. This method involves collecting information from official company documents, such as annual financial statements, quarterly financial statements, and records related to financial statements, as explained by Kusumastuti, A., Khoiron, A.M., & Achmadi, T.A. (2020). The type of data source used in the focus of the study is secondary data, also known as indirect data, not primary data. Secondary data is based on data collection from databases provided by stock exchanges, as explained by Unaradjan, D. D. (2019). This technique is used to access secondary archival data. The focus data of this study was obtained from the Indonesia Stock Exchange (IDX) and Osiris. The form of secondary data is in the form of panel data, which is a type of data that combines time series data or data from several times and cross-sectional data, as mentioned earlier.
Data Analysis Techniques
The focus of this study uses several ways of data analysis, including descriptive analysis of data that explains a variable, in addition to using classical assumption prerequisite tests to examine assumptions that must be done before regression in regression analysis, and finally using a hypothesis test involving multiple linear regression analysis, then partial tests, then simultaneous tests (F- tests), and finally using determination coefficient tests.
RESULTS AND DISCUSSION
This is an illustration of the answer to the hypothesis that has been formulated by analyzing 75 samples of coal mining sub-sector manufacturing companies, the data used in the analysis of this study was obtained from the official website of the Indonesia Stock Exchange (www.idx.com
<http://www.idx.com>) and Osiris are using the company's annual report and financial statements for 2018-2022.
RESULT
A. Descriptive Statistical Analysis
Table 3. Descriptive Statistical Results
Variable Obs Mean Std. Dev. Min Max
Harga Saham 75 .635 .874 -.67 3.1
PM 75 2.691 1.068 -.49 4.14
ROA 75 2.696 1.122 -.71 4.38
CR 75 .633 .68 -1.31 2.31
SR 75 53.548 25.905 -41.58 91.2
PER 75 29.156 85.709 1.85 567.64
Based on the table above, we present information that there are as many as 75 tests as samples during the 2018-2022 period. The Share Price has an average value of 0.635 and a standard deviation value of 0.874. There is significant variation in the observed values for each variable. For the variable Profit Margin (PM), the lowest price is -0.67 and the highest value is 3.1. The average PM is 2.691 with a standard deviation of 1.068. For variable ROA, the lowest price is - 0.49 and the highest number is 4.14. The average ROA is 2.696 with a standard deviation of 1.122 For the variable Current Ratio (CR), the lowest price is -0.71 and the highest value is 4.38. The mean CR is 0.633 and the standard deviation is 0.68. For the variable Solvability Ratio (SR), the lowest price is -41.58 and the highest value is 91.2. The average SR is 53.548 with a standard deviation of 25.905. the variable Price-Earnings Ratio (PER), the lowest price is 1.85 and the highest value is 567.64. The average PER is 29.156 and the standard deviation is 85.709. All these numbers give an idea of the variation and distribution of data observed in the analysis.
Classic Assumption Test 1. Normality Test
Tabel 4. Normality Test Results
Harga saham 75 0.943 3.686 2,848 0.002
PM 75 0.954 2.967 2.374 0.009
ROA 75 0.757 15.853 6.033 0.000
CR 75 0.923 5.032 3.527 0.000
SR 75 0.840 10.429 5.119 0.000
PER 75 0.906 6.105 3.950 0.000
Based on the results of the Shapiro table, the Wilk W test for normal data researchers take conclusions based on the table, it can be found that the number of probability numbers for each variable is below or <0.05, which means that the focus of the study tested all meet normal standards. With the normality test, it can be assumed that the focus of the object in the reserch is spread on a reasonable line, so that testing other classical assumption stages can be tested.
1. Heteroscedasticity Test
Based on the results of the Breusch "Pagan/ Cook" Weisberg test for heteroskedasticity we conclude that decision making after looking at the results, it can be found that the probability number of all variables observed dependent and
Variable Obs W V z Prob>z
independent below or >0.05 this means that the variable does not experience the phenomenon of heteroskedasticities. By conducting this heteroscedasticity test, it can be explained that the data are all accurate, free of indications of hetero symptoms among variables, and tests contained in other classical assumption tests can be carried out.
2. Multicolonicity Test
Tabel 6. Hasil Uji Multikolonieritas
VIF 1/VIF
HS 4.580 0.218
PM 4.340 0.231
ROA 2.930 0.341
CR 2.410 0.416
SR 1.490 0.671
PER 3.150
The residual value of VIF for the HS variable is 4.580 and 0.218, the resistance value and VIF for PM 4.340 and 0.231, the resilience value and VIF for the ROA variable, individually 2.930 and 0.341 and the residual value of VIF for the CR variable is 2.410 and 0.416, the residual value of the VIF of the SR variable is 1.490 and 0.671, the residual value of the VIF of the variable PER is 3.15. Among the variables explain the residual value of one variable with another variable and the VIF number below 10, which means that in testing this variable no assumption of multicollinearity was found to be tested this time.
3. Autocorrelation Test
Tabel 7. Autocorrelation Test Results Durbin Watson d-statistic (6, 75) = 1.532205
From the Autocorrelation test obtained the output of the "Durbin-Watson Model Summary" above, it can be seen the value of the Durbin-Watson table (d) worth 1.432. This figure will be seen if it is greater with the value of the Durbin- Watson table at the significance level of 5% using (k'; N). It can be interpreted that the Durbin-Watson number (d) on regression is somewhere between the values of dL and dU, or dL < d < dU (1.486 < 1.432 < 1.769). With reference to the Durbin- Watson test above, if the value of d (Durbin-Watson) is in the range of dL and dU values, or is present in the middle (4-dU) and (4-dL), so it can be ascertained that there is no indication of autocorrelation in the model, in accordance with the requirements that have been met by all classical assumption tests.
A. Hypothesis Test
1. Multiple Regression Analysis
Based on the multiple regression test table, the researcher notated the multiple regression equation with the following formula.
Y = 0.044 – 0.598 PM + 0,883 ROA – 0.184 CR -0.003 SR + 0.003PM+e
The interpretation of the above notation results is explained in the explanation below:
a) The value of the constant coefficient (0.044) is explained that when the independent variable variables (PM, ROA, CR, SR, and PER) are zero, while the stock price is 0.044. A positive constant coefficient value signifies a positive effect between these variables and the stock price.
b) The value of the PM constant coefficient (-0.598) indicates to us if the value of the PM variable increases by 1% with other variables (ROA, CR, SR, and PER) considered fixed or constant, while the stock price will decrease by 0.598.
c) The value of the constant coefficient of ROA (0.883) indicates to us if the value for the ROA variable increases by 1% by keeping the other variables (PM, CR, SR, and PER) considered fixed or constant, while the stock price rises by 0.883.
d) The value of the constant coefficient CR (-0.184) indicates to us that the value of the variable CR increases by 1% by keeping the other variables (PM, ROA, SR, and PER) considered fixed or constant, while the stock price falls by 0.184.
e) The value of the constant coefficient SR (-0.003) indicates to us that the value of the variable SR increased by 1% by keeping the other variables (PM, ROA, CR, and PER) considered fixed or constant, while the stock price fell by 0.003.
f) The constant coefficient of PER (0.003) shows us the value of the variable PER rising by 1% by keeping the other variables (PM, ROA, CR, and SR) considered fixed or constant, while the stock price rises by 0.003.
2. Partial Test (T Test)
The test results above can be interpreted regarding the effects of PM, ROA, CR, SR, and on stock prices in the explanation below:
a. Impact of PM on Stock Price: From the results of the analysis conducted using Stata version 17, the t value for PM is -3.51 with an estimated P number of 0.001. Comparing it to a critical T number of 1.665 taking into account the significant level of 0.05, the results explain that PM has an important negative relationship based on statistical testing of stock prices.
b. Impact of ROA on Stock Price: Analysis using Stata version 17 shows a t value of 5.59 for ROA with an estimated P value of 0.000. Comparing it to a critical T number of 1.665 taking into account the significant level of 0.05, the results
explain that ROA has a positive effect and is important statistically on stock prices.
c. Impact of CR on Stock Price: Based on analysis using Stata version 17, the t value for CR is -0.95 with an estimated P value of 0.347. Comparing it to a critical T number of 1.665 taking into account the significance level of 0.05, the results show that CR has an insignificant negative impact on statistical testing of stock prices.
d. Impact of SR on Stock Price: Analysis using Stata version 17 shows a t-value of - 0.50 for SR and an estimated p-value of 0.621. Comparing it to a critical t value of 1.665 and considering a significance level of 0.05, the results explain that SR has an unimportant negative effect on statistical testing of stock prices.
e. Impact of P/E on Stock Price: According to the analysis using Stata version 17, the t-value for P/E is 2.44 with an estimated P/E value of 0.017. Comparing it to a critical T number of 1.665 taking into account the significant level of 0.05, the results show that the P/E has a positive and important effect on statistical testing of stock prices.
3. Simultaneous Test (F Test)
Based on the results of investigations using stata version 17, it has been found that when the independent variable simultaneously has an important effect on the dependent variable, this test is supported by the F value of the count of 7.29 and the F value of the table with the number 2.34 because the F number is small above the F number of the table (7.29 > 2.34) so that the significance value shows a value of 0.05 or 5%, which is 0.00. so it is concluded that the focus of these research variables PM, ROA, CR, SR, and PER can be used as indicators to identify increases and decreases in stock prices and all of them simultaneously have an important impact on Stock Prices.
4. Coefficient Determination (R² Test)
Table 11. Determination Coefficient Test Results (R² Test)
Based on the results of investigations using stata version 17, it has been found that the Adj R-Squared value is 0.298 this finding means that 30% of various financial statement information can explain 5 kinds of free variations of PM, ROA, CR, SR, and PM. While others (100% - 30% = 70%) are explained by other indicators outside the focus of this research study.
Discussion
In the focus of this study, the scope is clarified more deeply with empirical evidence on the analysis of temporary grief that has been formulated at the beginning. The results of indications to answer the hypothesis can be described below.
a) PM's Relationship to Stock Prices
Based on statistical output, the PM coefficient number is obtained with a value of -0.598, and a significance number of 0.001. This proves that PM has a negative and important effect on stock prices. PM is obtained from the division between net income and revenue. This result can be explained, if the greater the PM number of a company, inversely proportional to the company's stock price, this is corroborated by empirical evidence from the latest research conducted by (Azhar, 2022) (Boru Situmorang, 2022), and (Hutapea et al., 2017) which found the conclusion of profit margin research to have a negative and important effect on stock prices. So the conclusion is drawn in this study that H1 is accepted.
Because Esteem meets the standard criteria.
b) ROA Relationship to Stock Price
Based on the statistical output, the ROA coefficient figure is 0.883 over a significance figure of 0.000. This indicates ROA has an important effect on stock prices. ROA (Return On Assets), is a comparison of current debt with current assets. The results of this study can be interpreted, if the ROA value is higher than a company, in line with the value of company shares, This result is supported by findings by several researchers, (Zaman et al., 2021), (Kadek et al., 2022), (Suryasari &; Artini, 2020), (Wardani &; Wati, 2018), (Dwi &; Astuti, 2018), (Edsel Yermia Egam et al., 2017), (Rusli &; Dasar, 2014), (Almira &;
Wiagustini, 2020), (Anita Wijayanti, 2017), which found that ROA has a positive and important effect on stock prices so that it is concluded that the findings of the focus of this study H2 are accepted because esteem meets the standard criteria.
c) CR's Relationship to Stock Price
Based on the statistical output, the CR coefficient figure is -0.184 while the significance figure of 0.347 tells us that CR has no impact on the stock price. CR (Current Ratio) is comparing current assets with current debt. The results of this study are interpreted, if the CR number of a company is high. Not in line with the company's stock price figures, this finding is supported by findings by several researchers, (Nur Huda, 2012), (Suryasari &; Artini, 2020), (Nurhandayani &;
Nurismalatri, 2021), (Sari, 2020), (Sukayasih et al., 2019), (Januardi Manullang et al., 2021), (Yuniarti, 2022) and (Mahendra et al., 2022) which concluded that CR had a negative and unimportant effect on stock prices so that the conclusion of H3 was not accepted because esteem did not meet the standard criteria.
d) SR Relationship to Stock Price
Based on the statistical output, the SR coefficient is -0.003 on the significance of 0.621, this explains to us that the SR variable has no effect on stock prices. SR (Solvency Ratio), is comparing total assets with current debt. The results of this study can be interpreted, the higher the SR of a company, not in line with the company's stock price, this finding is corroborated by findings by several
researchers, (Devi Anggreini, 2019), (Husna &; Sunandar, 2022), and (Damayanti &; Valianti, 2017) who found SR measured using DER has a negative and unimportant effect on stock prices so that it can be concluded that H4 was rejected because esteem did not meet standard criteria.
e) P/E Relationship to Stock Price
Based on the statistical output, the PER coefficient is 0.003 and the significance figure of 0.17 of these findings tell us that the PER variable has a positive and important effect on stock prices. PER (Price Earning Ratio) is a comparison of share prices per share to earnings per share. The results of this study can be interpreted, the higher the PER of a company, in line with the company's stock price, this finding is in line with the conclusions by several researchers, (Ariani, 2021), (Lestari &; Suryantini, 2019), (Suryasari &; Artini, 2020), (Sugiyono, 2021), (Badillah, 2017), (Rinaldi, 2016), (Ratih et al., 2013), and (Novasari, 2013) with the conclusion that PER has a positive and important effect on stock prices and H5 conclusions are accepted because esteem meets standard criteria.
CONCLUSIONS, LIMITATIONS AND ADVICE Conclusion
a. Profit Margin (PM) has an important effect on stock prices. Previous findings and analyses in this study suggest that PM is negatively associated and has an important impact on stock prices. This is in line with value theory which argues that stock prices reflect a firm's intrinsic value.
b. Return On Assets (ROA) has an important effect on stock prices. This ratio has been widely used in previous studies with other considerations, and in this study, ROA was found to be positively related and have an important impact on stock prices. This is supported by corporate financial theory which says that financial information is one of the factors that affect stock prices.
c. Current Ratio (CR) has no significant effect on stock prices. This ratio has been widely used in previous studies with other considerations, and in this study, CR was found to be negatively related and not have an important impact on stock prices.
d. Solvency Ratio (SR) has no significant effect on stock price. This ratio has been widely used in previous studies with other considerations, and in this study, SR was found to be negatively related and had no significant effect on stock prices.
e. Price Earning Ratio (PER) also has no important effect on stock price. This ratio is often used in the review of previous research with other considerations, and the focus of this study is that P/E was found to be positively related and have an important impact on stock prices. This finding is corroborated by market efficiency theory explaining that stock prices describe all available information in the market. PER is one of several measuring tools to describe the performance and growth potential of the company that will have an impact on increasing the value of the company in the market.
Limitations
a. Data Limitations: The availability and quality of data, including financial data and historical stock prices, may be incomplete, inaccurate, or difficult to obtain, which may affect the accuracy and reliability of results.
b. Time Limit: This study is limited to a specific time period (2018-2022), which may not capture long-term trends or short-term fluctuations that may affect stock prices. Changes in market conditions or regulations beyond this period may affect the generalizability of findings.
c. External Factors: External factors, such as changes in commodity prices or
market conditions, are not taken into account in the focus of this study. This indicator can have a significant increase and decrease in coal and lignite mining stock prices and may have an impact on the results.
d. Unstudied variables: Other variables within the scope of the study focus such as management performance, industry risk, or macroeconomic conditions, have the potential to affect stock prices and should be considered in future studies.
e. Causal Effect: Studies only establish correlations between variables and stock prices, without determining causality. More research is needed to establish a causal relationship between variables and stock prices.
f. Methodological limitations: methodologies used in the focus of this study, such as linear regression or panel analysis, may have limitations and assumptions.
Consideration of alternative analytical methods and stress checks can increase the validity of findings. In addition, the study did not explore potential interactions between variables, which could provide further insight.
Advice for the Next Researcher
a. Extended Time Period: Extending the research period beyond 2018-2022 will provide a more comprehensive understanding of long-term trends and mitigate the impact of short-term fluctuations.
b. Expanded Sample: Including more diverse companies other than coal and lignite listed on the IDX will increase the generalizability of findings and account for variations in industries.
c. Additional Control Variables: Incorporating additional control variables, such as company size, stock liquidity, industry growth rate, and interest rates, will allow a more comprehensive analysis of the factors affecting stock prices.
d. Advanced Methodology: Utilizing advanced econometric models or more sophisticated analytical techniques, such as panel regression or multivariate analysis, can provide a more nuanced understanding of the relationships between variables.
e. Specific Financial Indicators: Considering industry-specific financial indicators that are more relevant to coal and lignite mining companies, such as gross profit margins or solvency ratios, can provide more precise insight into the relationship to stock prices.
f. Moderation and Mediation Variables: Exploring the influence of moderation or mediation variables that can interact with the factors studied can enlighten future research.
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