SOSIOHUMANIORA, 10(1), February 2024, pp. 30-45 2579-4728 (E-ISSN) | 2443-180X (P-ISSN)
Return on assets, return on equity, earnings per share, dividend yield, and book-to-market ratio’s effects on stock return
Annisa Aulia Rahma Atmariani*, Dian Agustia
Universitas Airlangga, Jl. Airlangga No.4 Surabaya 60286, Indonesia Correspondance: [email protected]
Received: 2 September 2023; Reviewed: 17 October 2023; Accepted: 21 November 2023 Abstract: This research intends to investigate the ability of Return on assets (ROA), return on equity (ROE), earnings per share (EPS), dividend yield (DY), and book-to-market ratio (BMR) on stock returns. Stock investment is one strategy for investors to channel their finances while boosting wealth due to the high return on equities earned. In this study, company information is represented by financial ratios, which play a significant role in guiding investors in identifying which companies have the potential to give the highest number of returns. With 164 total observations, this research used 56 companies that were part of the LQ45 index on the Indonesian Stock Exchange (IDX) in the 2019–2022 timeframe as a sample study with the aim to examine the effects of ROA, ROE, EPS, dividend yield, and book-to-market ratio on stock return.
Using STATA 14.0 software, double linear regression analysis is used in the hypothesis test. The results of this research, as proven by the regression analysis, are as follows: (1) the book-to-market ratio negatively affects stock return; and (2) ROA, ROE, EPS, and dividend yield have no bearing on stock return. This study emphasizes the value of diversifying investment strategies and avoiding a narrow range of financial ratios when choosing which stocks to buy. Investors should evaluate general business conditions and take a wider range of issues into account.
Keywords: Return on Assets and Return on Equity, Earnings Per Share, Dividend Yield, Book-to-Market Ratio, Stock Return
© 2024 The Author(s)
https://doi.org/10.30738/sosio.v10i1.15870
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License
INTRODUCTION
Companies must continuously enhance their performance to stay afloat in the face of fiercer competition in the marketplace. The availability of funds became one of the supporting aspects in an attempt to enhance performance. Alternatively, the company may issue debt or stocks on the stock market to fund these needs (Alipudin & Oktaviani, 2016). 21 companies were listed on the Indonesian Stock Exchange (IDX) as new issuers as of May 2022 (BEI, 2022). It indicates that the capital market, which distributes investors' funds to create profitable investment opportunities, is emerging as one of the primary drivers of economic growth (Santosa, 2019).
In addition to channeling funds, the primary goal of stock investors is to maximize their wealth through the return on stocks acquired by the willingness to face market risks (Santosa & Puspitasari, 2019). According to Musallam (2018), stock return is an important
consideration when deciding on the best investment opportunity. In order to select the greatest opportunity with favorable return with minimal risk, investors require both internal and external company information as material for analysis and evaluation of a company's performance and its potential impact on stock return. The financial ratio is one of the most commonly used tools to assist investors in evaluating a company's performance by providing information about the relationship between accounts in financial statements, the company's financial condition, net profit, and debt that can affect stock return (Erzad & Erzad, 2017).
The determinant of stock return has been the subject of extensive empirical research in the fields of academia. As forecasting factors of stock returns, this study focuses on Return on Assets (ROA), Return on Equity (ROE), Earnings per Share (EPS), dividend yield (DY), and Book-to-Market ratio (BMR). As stated by Erzad & Erzad (2017), the most significant profitability ratio for predicting stock returns is ROA. The statement is in line with research by Allozi & Obeidat (2016), Erzad & Erzad (2017), Santosa (2019), Santoso, Owen, & Raissa (2021), and Harlan & Wijaya (2022) that proves that ROA has an influence on stock returns. Instead, research by Oktyawati & Agustia (2014) reveals that ROA has no effect on stock returns because investors look into various aspects other than the profitability ratio, such as the overall picture of the company and personal requirements. In addition to ROA, investors frequently use ROE to gauge the level of profitability of companies because it may estimate the rate of return that investors will receive on investments made (Alipudin & Oktaviani, 2016). Allozi & Obeidat (2016) backs up the statement, proving that ROE is able to forecast a company's stock return. In contrast to prior studies, Santoso et al. (2021) found no influence of ROE on stock return since ROE is primarily driven by the firm's equity composition, so when a company issues additional shares, the ROE rate decreases.
Earnings per share (EPS) is one of the market value ratios that is frequently associated with stock return. A stable business will have consistent EPS growth since EPS shows that the better the company's ability to generate earnings per share for its owners, the higher the return on its stocks (Erzad & Erzad, 2017). In line with the statement, Musallam (2018) and Santosa (2019) proved that the EPS had a positive influence on the signature of stock returns. Din (2017) provides additional evidence that EPS affects stock return, although negatively. Despite a company's high EPS rate, the discrepancy in stock return movements caused by investor response to good and bad news has resulted in decreased stock returns. In contrast to earlier studies, the findings of Erzad & Erzad (2017) and Harlan & Wijaya (2022) indicate that EPS has no effect on stock returns.
Among the financial ratios studied in the research of stock return determinants, dividend yield (DY) and book-to-market ratio (BMR) have been considered as the most important and effective indicators for predicting stock return (Safari, 2011; Arslan &
Zaman, 2014; Hasan, Farooq, & Muddassir, 2015; Sha, 2017). In a bull market, companies
will have better investment opportunities, so they will pay less dividends to fund projects.
The situation will result in a negative relationship between DY and stock returns. Yet, if market conditions are drastically declining (bear market), the relationship between the two will be positive. Companies tend to pay higher dividends to sustain their stock price and demonstrate their company's resilience (Safari, 2011). Wagiri (2013), on the other hand, found no substantial influence of DY on stock return. Another useful measure is BMR, which provides a snapshot of the company's success through the stock market price. When the value of the book-to-market declines, it implies that the company's share value is overvalued, causing the company's worth to grow in the eyes of investors.
Following the growth, the stock market's value and return will steadily rise (Sha, 2017;
Justina, 2018).
The relationship between the five independent variables and the dependent variable in this study may be explained through signaling theory, which highlights the importance of company information for external investment decisions (Bulutoding et al., 2018). Forecasts of the past, present, and future can assist investors when making financial decisions. Using financial ratios, investors can evaluate and analyze a company's financial performance from a range of perspectives. When a company's financial performance is represented in a good financial ratio, investments might profit the most from the acquisition of stock, and vice versa.
Previous research inconsistencies, as well as the importance of financial ratios in predicting stock return, motivated researcher to conduct research by testing the influence of (1) ROA on stock return; (2) ROE on stock return; (3) EPS on stock return; (4) DY on stock returns; and (5) BMR on stock return. This study contributes to the accounting literature by confirming the capacity of financial ratios to predict stock returns.
Theoretical Framework and Hypothesis Development Signaling Theory
Signaling theory highlights the significance of company information as a component in an external party’s investment decision-making (Bulutoding et al., 2018). A company's financial and non-financial information can assist investors in assessing the company's past, current, and future performance. When a company's performance is reflected in the information it provides, investors can simply decide where to route their investment.
Good corporate performance will result in maximum earnings for the company, allowing investors to earn the guaranteed return on profits (Bustani, 2020). Financial ratios such as ROA, ROE, EPS, DY, and BMR can provide investors with information about a company's performance. This will raise investor demand for ownership, thus the company's return on stocks is expected to be higher.
Return on Asset (ROA) and Stock Return
Return on Asset (ROA) is one of the profitability measures that reflects a business's ability to use its assets to generate profit after taxation (Erzad & Erzad, 2017). This ratio is critical for companies to evaluate management's efficacy and efficiency in managing the entire company's assets. The higher a company's ROA rate, the more efficient its utilization of assets to generate profits. Given the nature of their long-term investments, Brown & Reilly (2012) and Subramanyam (2014) contend that profitability is one of the key factors taken into account by stock investors. Empirically, Erzad & Erzad (2017), Santosa, (2019), Santoso et al. (2021), and Harlan & Wijaya (2022) have shown that ROA has a significant positive impact on stock returns. The results reveal that the more effective a firm is at utilizing its assets to generate profits, the higher the profits earned and the better the organization's performance. Increased profits will drive up the demand for stocks, resulting in higher stock prices and higher returns for investors. A good ROA value, based on the signaling theory, might be a signal of positive news from the company to the investor when it is about to make an investment. Based on the preceding description, the researcher formulates the following hypothesis:
H1: Return on Asset (ROA) affects stock return positively.
Return on Equity (ROE) and Stock Return
Return on Equity (ROE) is one of the profitability ratios used to evaluate the company's ability for making a profit with its own equity (Aryanti & Mawardi, 2016). The higher a company's ROE rate, the more efficient it is at managing its equity to generate profits. As stated by Alipudin & Oktaviani (2016), ROE can describe potential earnings for investors by linking profits to the amount of equity owned. That statement aligns with the signaling theory, which highlights the value of accounting data in guiding investors in making decisions about their investments. Allozi & Obeidat (2016) have shown that ROE has a significant positive influence on stock returns. The results show that the greater the company's ROE value, the higher the company's share demand. This has resulted in greater pricing as well as larger stock returns. Based on the prior description, the researcher proposes the following hypothesis:
H2: Return on Equity (ROE) affects stock return positively.
Earnings per Share (EPS) and Stock Return
Earnings per share (EPS) information is considered to be the most fundamental and useful information for investors because it may define the company's future possible revenue as well as gauge the company's level of efficiency (Alipudin & Oktaviani, 2016). In short, EPS can be used to evaluate management success in giving advantages to investors as well as investor success in obtaining profits. Because a greater EPS rate indicates a higher return rate, investors are drawn to stocks with a high EPS rate (Horne &
Wachowicz, 2013; Brigham & Houston, 2016). The statement was backed by Allozi &
Obeidat (2016), Musallam (2018), and Santosa (2019), who concluded that higher EPS
values make investors more intrigued in the stock since the amount of profit delivered as shareholder dividends increase, so does the share return. The ability of EPS to represent stock returns to shareholders is in line with signaling theory, where EPS with good value may deliver positive indications to investors (Harlan & Wijaya, 2022). Based on the preceding description, the researcher forms the following hypothesis:
H3: Earnings per share (EPS) affects stock return positively.
Dividend Yield (DY) and Stock Return
Dividend yield is one of the metrics believed to have the most predictive power for stock returns (Alajekwu & Ezeabasili, 2020). As stated by Rahman et al. (2019) and Usman et al. (2021), a high DY indicates that capital markets are undervalued and that investors can acquire and keep firm stocks. When a company's stock price rises in the future, investors are going to gain from the stock. In accordance with the statement, Safari (2011), Arslan & Zaman (2014), and Musallam (2018) provided empirical evidence that DY had a significant positive effect on stock returns. This implies that the larger the dividend that is distributed, the higher the return on stocks for investors due to rising demand and stock prices. Dividend payments remind investors that the company's management has worked in their best interests and compensated shareholders by distributing dividends (Marito & Sjarif, 2020). Based on the preceding description, the researcher formulates the following hypothesis:
H4: Dividend yield (DY) affects stock return positively.
Book-to-Market Ratio (BMR) and Stock Return
A book-to-market ratio (BMR) is a comparison between a company's stock book value and its market value in the capital market (Sha, 2017). According to Nugroho (2020), one of the key benefits of this ratio was the consistency of the measure provided by the book value in comparison to the market price. For investors who are skeptical of discounted cash flow projections, book value can serve as a benchmark. Dempsey (2010) noted that BMR had a significant impact on stock returns. A rise in BMR implies that the company has performed poorly and is prone to monetary strain or unfavorable prospects in the future, resulting in a downturn in the stock's market appreciation (Justina, 2018). As a consequence, investors' chances of receiving a return will decrease with time.
Conversely, a declining BMR of a company represents a solid performance and raises stock returns (Sha, 2017; Justina, 2018). Based on the prior description, the researcher forms the following hypothesis:
H5: The book-to-market ratio (BMR) affects stock return negatively.
METHOD
According to Abdullah (2015), the population is the overall target of the research to which the results are subsequently applied. The population in this study is a non-financial company that is included in the LQ45 index on the Indonesian Stock Exchange (IDX) from 2019 to 2022. The LQ45 index was chosen by the researcher because the stocks of the companies included in it belong to the blue-chip category in the Indonesian capital market. Blue-chip stocks are those that have a high level of liquidity, a stellar track record, and are known for their dividend stability and consistency (Santoso et al., 2021).
Research samples are subsets of the target population (Abdullah, 2015). Purposive sampling approaches are used by researchers to choose research samples, because not all samples meet the criteria that are given. The following criteria were applied in the sample selection for this study: (1) are non-financial firms included in the LQ45 index on the Indonesian Stock Exchange (IDX) from 2019-2022; (2) published financial statements in 2019-2022 and are on OSIRIS database; and (3) have the data required in this study. 56 companies with 164 total observations make up the study's final sample based on these criteria.
This study contains five independent variables and one dependent variable. ROA, ROE, EPS, DY, and BMR are the independent variables analyzed by researcher to examine their impact on the dependent variable, stock return. Table 1 presents a summary of each variable's measurement and definition.
Empirical Methodology Winsorizing
Winsorizing is a process that mitigates the impact of outlier data on averages and variances, resulting in a more robust estimator (Blaine, 2018). This technique has become a crucial tool for social science researchers because the mean-based significance test and variance are frequently used procedures in calculating significance in social scientific studies. Winsorizing is carried out by converting the outlier data value with the greatest value to the 99% level and the lowest to the 1% level (Leone et al., 2019). The advantage of this method is that it doesn't erase data, but only modifies data behavior, thus the amount of research data does not change.
Statistic Descriptive Analysis
Descriptive statistics are used to examine data by describing the obtained data without attempting to draw generalizable conclusions. In this study, descriptive statistics provide the maximum and minimum value, mean, median, and standard deviation for each variable measured.
Table 1. Variable Definition and Measurement
Variables Definition Measurement Previous
Studies
Data Source Dependent Variable
RTS Stock
Return
Pt− Pt−1
Pt−1
where Pt is the stock price at time t, and Pt-1 is the stock price at time t-1.
The return on the stock is calculated using the closing price in the year in question.
Erzad & Erzad (2017)
OSIRIS
Independent Variables
ROA Return on
Asset
Earning after Tax Total Assets
Erzad & Erzad (2017)
OSIRIS
ROE Return on
Equity Earning after Tax
Total Equity
Alipudin &
Oktaviani (2016)
OSIRIS
EPS Earning per
Share Earning after Tax
Outstanding Stocks
Alipudin &
Oktaviani (2016)
OSIRIS
DY Dividend
Yield
Dividend per Share Market price per Share
Marito & Sjarif (2020)
OSIRIS
BMR Book-to-
Market Ratio
Book value of Equity Market value of Equity
Nugroho (2020) OSIRIS
Pearson Correlation
The Pearson correlation coefficient estimates the strength and direction of a direct relationship between variables. Pearson's value ranges from -1 to +1. A value of -1 indicates an exact negative relationship, a value of 0 indicates an absence of any relationship between variables, and a value of 1 points to a pure positive relationship.
Perfect correlations ranging from -1 to +1 show that all data points are on a straight line (Schober & Schwarte, 2018). This coefficient is solely used to test the linear influence on each variable.
Multiple Linear Regression Analysis
As there are multiple independent variables in this study, multiple linear regression is applied to test the hypothesis. Cluster model regression is utilized as a robust method to minimize the presence of heteroscedasticity and autocorrelations (Petersen, 2009). To estimate regression with the cluster model, companies are grouped by company classification in IDX (IDX-IC) and year. The benefits of such models lie in the handling of outliers and abnormal error values. In addition, the year-fixed effect was used in this
analysis to eliminate the bias of time and industry disparities. The regression equation used in this research is as follows:
RTS = + 1ROA + 2ROE + 3EPS + 4DY + 5BMR + ε (1)
The confidence levels applied to test the hypotheses are 90%, 95%, and 99%, respectively, hence the margin of error are () = 1%, 5%, and 10%. If the p-value is less than
, the hypotheses are accepted. Meanwhile, if the p-value exceeds , the hypotheses are rejected.
RESULT AND DISCUSSION An Overview of the Research Sample
Table 2 states the distribution of samples by year. The results demonstrate that samples are generally uniform, ranging from 40 to 42 annual observations. The smallest sample size was 40 observations in 2022, while the largest sample size was 42 observations in 2020.
Table 2. Samples Distribution by Year
Year Freq. Percent Cum.
2019 41 25.00 25.00
2020 42 25.61 50.61
2021 41 25.00 75.61
2022 40 24.39 100.00
Total 164 100.00
Source: STATA, 2023
Descriptive Statistic Analysis
Descriptive statistical analysis provides details regarding the variables selected for this study, namely Return on Assets (ROA), Return on Equity (ROE), Earnings per Share (EPS), Dividend Yield (DY), Book-to-Market Ratio (BMR), and Stock Returns (RTS). The results are presented in Table 3 below along with each variable's mean, median, maximum, minimum, and standard deviation.
Table 3. Descriptive Statistical Analysis
Obs Mean Std. Dev. Min Max
ROA 164 7.486 7.695 -7.3 35.8
ROE 164 14.379 23.896 -64.39 139.97
EPS 164 303.163 811.614 -332.495 5654.991
DY 164 .503 1.695 0 11.224
BMR 164 .764 .523 .018 2.438
RTS 164 -.009 .363 -.59 1.362
Source: STATA, 2023
Table 3 discloses that ROA has the lowest value of -7.3 and the highest value of 35.8.
The studied companies' average ROA is 7,486 with a standard deviation of 7,695. The ROE variable has the lowest and highest values of -64.39 and 139.97, respectively, and an average and standard deviation of 14,379 and 23,896. EPS ranges from -332,495 to 5654,991. The average EPS is 303,163 with a standard deviation of 811,614. The DY variable has a minimum and maximum value of 0 and 11.224, respectively, as well as a mean and standard deviation of 0.503 and 1.695. BMR, the study's fifth independent variable, had the lowest value of 0.018 and the highest value of 2.438. With a standard deviation of 0.523, the average BMR is 0.764. Finally, RTS, as the dependent variable in this study, has the lowest and highest values of -0.59 and 1.362, respectively. The RTS average is -0.009 and the standard deviation is 0.363.
Pearson Correlation
The Pearson correlation test was performed in this study to determine the strength of the linear relationship between the two variables. Table 4 reveals that there is no association between ROA (coef = 0.037), ROE (coef = 0.047), EPS (coef = -0.061), and DY (coef = -0.080) with stock returns. This implies that the company's high or low levels of ROA, ROE, EPS, and DY have nothing to do with the rate of return on stocks, which increases or decreases year upon year. Meanwhile, the BMR has been found to have a substantial inverse association (coef = -0.243***) with stock returns. These findings suggest that an increase in the ratio of book value to market value is strongly related to a drop in the rate of return on a company's stock, and vice versa.
Table 4. Pearson Correlation Analysis
ROA ROE EPS DY BMR RTS
ROA 1.000
ROE 0.838*** 1.000 (0.000)
EPS 0.191** 0.083 1.000 (0.014) (0.289)
DY 0.134* 0.062 0.181** 1.000 (0.088) (0.433) (0.020)
BMR -0.368*** -0.296*** 0.001 0.002 1.000 (0.000) (0.000) (0.987) (0.977)
RTS 0.037 0.047 -0.061 -0.080 -0.243*** 1.000 (0.636) (0.548) (0.440) (0.306) (0.002)
Source: STATA, 2023
Multiple Linear Regression Analysis
In this research, multiple linear regression modeling is implemented to analyze the effect of the independent variables, namely ROA, ROE, EPS, DY, and BMR, on the dependent variable, which is stock returns. This test was carried out utilizing the STATA 14.0 software.
Table 5. Multiple Linear Regression (1) RTS
ROA -0.007
(-1.21)
ROE 0.002
(1.20)
EPS 0.000
(0.11)
DY -0.026
(-1.32)
BMR -0.233***
(-3.13)
IDXIC Included
YEAR Included
_cons 0.442***
(2.78)
r2 0.176
r2_a 0.087
N 164
t statistics in parentheses
* p < 0.1, ** p < 0.05, *** p < 0.01
Table 5 discloses that ROA has no effect on stock returns, with a coefficient value of -0.007 and a significance of 0.237 (p-value more than 10%). As a result, it may be concluded that the first hypothesis in this research was rejected. The second and third independent variables in this analysis, namely ROE and EPS, also had no effect on stock returns, with significant values of 0.239 and 0.915 (p-value more than 10%), respectively.
As a result, the second and third hypotheses proposed in this study were rejected. The same results were found when assessing the effect of DY on RTS, which stated a significant value of 0.198 (p-value more than 10%), implying that the fourth hypothesis in this study was likewise rejected. In contrast to the preceding four independent variables, the BMR variable has been shown to have a negative effect on stock returns. This is reflected in a coefficient value of -0.233 and a significance of 0.004 (p-value less than 1%), indicating that H5 in this study is accepted.
DISCUSSION
The Effect of Return on Asset (ROA) on Stock Return
Based on the regression results, ROA had no effect on stock returns, with a coefficient value of -0.007 and a significance of 0.237 (p-value greater than 10%), hence the first hypothesis (H1) in this study was rejected.
ROA, as one of the profitability ratios, plays an important role in signaling to external parties the company's efficiency and effectiveness in managing all of its assets to generate profits (Erzad & Erzad, 2017). Because of the long-term nature of the investment, the profitability ratio is another crucial assessment tool to examine. The lack of influence suggests that ROA is not the sole factor investors examine when investing in a company.
According to Oktyawati & Agustia (2014), investors also analyze other accounting information, company image, major events in the current year, suggestions from specialists or financial consultants, corporate social interactions, and individual financial needs. When the ROA value increases, the company's stock price remains unchanged, thus ensuring that the returns on stocks do not change. This study's findings contradict those of Erzad & Erzad (2017), Santosa, (2019), Santoso et al. (2021), and Harlan & Wijaya (2022), who discovered empirical evidence that ROA has a positive impact on stock returns.
The Effect of Return on Equity (ROE) on Stock Return
With a significance value of more than 10% (0.239), ROE has been statistically proven to have no effect on stock returns. The statistical test results contradict the hypothesis proposed in this study, hence H2 is rejected.
The ability of an enterprise to generate profits with its own equity can be quantified using ROE as a profitability ratio (Aryanti & Mawardi, 2016). Since it compares profit to the amount of equity owned, ROE has been considered to show income potential for investors (Alipudin & Oktaviani, 2016). However, the findings of this study reveal that ROE has no predictive value on stock returns. The findings of this study are consistent with Santoso et al. (2021), who showed that stock returns are unaffected by the company's ROE. Because ROE is more easily influenced when companies issue shares, it is unable to provide a signal to investors regarding the level of return on shares. This result also runs counter to the signaling theory, which points out the vital role of all business information while making investment decisions (Bulutoding et al., 2018). Tumonggor, Murni, & Van Rate (2017) argue that since companies cannot guarantee their equity with profits, ROE has no bearing on stock returns.
The Effect of Earning per Share (EPS) on Stock Return
The findings of multiple linear regression demonstrate that, statistically, EPS has no effect on the company's stock return rate, with a significance value of 0.915 or a p-value of more than 10%. As a result, H3 as proposed in this study was rejected.
EPS is frequently used as a benchmark for investors in gauging their effectiveness in obtaining the intended profit because it contains the most basic information about the company's earnings prospects (Alipudin & Oktaviani, 2016). However, the findings of this study suggest that EPS does not have the ability to predict stock returns. According to Harlan & Wijaya (2022), the ineffectiveness of EPS in influencing stock returns is due to companies frequently failing to pay dividends to shareholders, despite the fact that one of the primary goals of investing shareholders is to receive dividends. If investors expect a high EPS rate but do not receive the required return, they are unlikely to take advantage of EPS to predict stock returns (Erzad & Erzad, 2017). The inadequacy of EPS to forecast stock returns also defies signaling theory, which states that high or low levels of EPS created by companies are unable to provide signals to investors to help them make a decision.
The Effect of Dividend Yield (DY) on Stock Return
This study provides empirical evidence that DY has no effect on stock returns. These findings are reflected in the coefficient value of -0.026 and the significance level of 0.198 (p-value more than 10%). As an outcome, H4 in this study was rejected.
According to Alajekwu & Ezeabasili (2020), DY is a form of ratio that plays a crucial part in estimating stock returns since fluctuations in yield ratios tend to enhance price variations and stock returns. However, the study's findings suggest that DY has no impact on stock returns. The high or low value of DY has no bearing on the investor's choice to purchase company stock. This is due to various factors utilized as a reference by investors, such as corporate image, expert advice, corporate social interactions, and individual financial demands (Oktyawati & Agustia, 2014). Furthermore, the lack of effect may be due to the fact that many of the companies being studied fail to distribute dividends.
According to this research data, only 25% of corporations pay dividends to investors. The findings of this study support the findings of Wagiri (2013), who found that DY has no impact on stock returns.
The Effect of Book-to-Market Ratio (BMR) on Stock Return
Based on the regression results, BMR has a negative influence on stock returns with a coefficient value of -0.233 and a significance of 0.004 (p-value less than 1%). As a result, the fifth hypothesis (H5) formulated in this study is accepted.
As stated by Dempsey (2010), the ratio of book value to market value has a major effect on predicting stock returns. This is due to the ratio's relationship with leverage, which also plays a role in projecting stock returns. The inverse relationship between BMR and stock returns suggests that the higher (lower) the level of ratio generated by the company, the lower (higher) the rate of return on the company's shares (Sha, 2017;
Justina, 2018). The conclusions of this study are in line with the findings of Justina (2018), which found that BMR has a negative impact on stock returns. Companies with high BMR values are likely to experience monetary problems, prompting stock returns to fall and
investors to be wary of investing in companies experiencing significant financial troubles.
The above finding is aligned with signaling theory, which states that outstanding or poor firm performance can be portrayed in financial information, which can help investors make investment decisions (Bulutoding et al., 2018).
CONCLUSION
This research intends to investigate the ability of ROA, ROE, EPS, DY, and BMR on stock returns using 56 companies from the LQ45 index on the Indonesia Stock Exchange (IDX) in the 2019-2022 period with a total of 164 observations. Stock investment is one strategy for investors to channel their finances while boosting wealth due to the high return on equities earned. In this study, company information is represented by financial ratios, which play a significant role in guiding investors in identifying which companies have the potential to give the highest number of returns. The findings revealed that BMR has a negative effect on stock returns. Meanwhile, ROA, ROE, EPS, and DY have no effect on stock returns and are in contrast with signaling theory, which argues that all information owned and publicized by business organizations plays a significant role in assisting investors in making investment decisions.
This study contributes to the accounting literature on financial ratios as a predictor of a company's stock return. The results of this study also provide insights and implications for investors not to be fixated on one or several financial ratios in making a decision, but also to consider the overall business conditions. Because this study only uses non-financial enterprises in the LQ45 index from 2019 to 2022 as the study population, it is advised that future researchers broaden the population scope and research period. Furthermore, this study only examines the effect of five financial ratios on stock returns. Therefore, future research can conduct tests of different financial ratios to broaden knowledge and enrich accounting research.
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