Earnings Per Share, Returns on Investment and Stock Returns of Quoted Manufacturing Companied in Nigeria

materials for additional research in this area. This report can be used by regulatory agencies such as the Securities and Exchanges Commission , the Central Bank of Nigeria , as well as the Manufacturers Association of Nigeria to enhance the framework for regulating Nigerian manufacturing firms. The study's findings will also help regulators and policymakers enact new rules and guidelines pertaining to working capital administration in manufacturing companies. 1.7 Scope and Limitations of the Study The study is limited to Nine (9) quoted manufacturing industries listed on the Nigeria Exchange Group. They are; Cadbury Nigeria Plc, Dangote Sugar Refinery Plc, Champion Brewery Plc, Guinness Nig. Plc, Nestle Nigeria Plc. GlaxoSmithKline Consumer Nig. Plc., Lafarge Africa Plc, Unilever Nigeria Plc, Berger paint Plc. The research spans eleven (11) years, from 2015 to 2025. 2.0 Review of Related Literature 2.1 Conceptual Review The conceptual issues are discussed in this section of the study. 2.1.1 Overview of Accounting Income Accounting provides a vital service to broad and different users. Investors use financial accounting information for investment decisions; government agencies need it particularly for tax purposes; while regulatory agencies use it to determine whether existing statutory pronouncements are complied with, among others. 2.1.2 Proxies of Accounting Income The commonly used proxies for accounting income are explained in this section 2.1.3 Earnings Per Share This is one important financial indicator that significantly affects the stock price of a company. It is an important measure of profitability since it shows how well a business can produce net income for investors. A key indicator of a business's attractiveness is its earnings per share . According to Nalurita (2016) in Gurung and Subedi (2024), EPS is a primary indicator of a stock's attractiveness and is generally considered the most significant variable in determining stock market prices. Its importance extends to several key financial metrics, including the price-to-earnings (P/E) ratio and the price-to- book (P/B) value, in assessing whether a stock is overvalued or undervalued relative to its earnings and book value, respectively. (Gurung and Subedi 2024; Kinney et al., 2018) have demonstrated the strong correlation between EPS and stock prices, highlighting its importance for investors and analysts in making informed investment decisions. Understanding the influence of EPS on market price per share is essential for assessing a company's financial health and potential for future growth. Research has shown that EPS and the price of shares are strongly correlated (Gurung and Subedi, 2024; Kinney et al., 2018), underscoring the significance of EPS for investors and analysts in making well-informed investment choices. Assessing the financial condition of an organization requires an understanding of how EPS affects the valuation per share status as well as prospects for expansion. Earning per shares is calculated by this formula EPS = (Net income – Preferred Dividends) (Total number of outstanding shares) P-ISSN 2695-186X 2.1.4 Return on Investment One of the most widely used productivity evaluation and assessment indicators in business analysis is returned on investment . ROI analysis is a powerful tool for evaluating existing information system and assisting decision-makers with making informed decisions on manufacturing processes, acquisitions, and other projects when applied correctly. A thorough and measurable examination of financial outcomes and expenses served as the foundation for the definition of ROI, a phrase that was first used in the financial industry decades ago. In both the public and private sectors, ROI is currently generally acknowledged and accepted in the fields of finance and business. However, the widespread use of ROI approach has led to a scenario where ROI is commonly viewed as an unclear, non-rigorous collection of mixed approaches that is vulnerable to biased judgment and inaccuracy (Alexei and Andru, 2022). ROI measures how effectively a business's management is managing its investments. It is the proportion of all assets to post-tax earnings. The sum can be calculated using the ratio of revenues after expenses to total assets. This formula is used to calculate return on investment ROI = (Gain from investment – Cost of investment) (Cost of investment) 2.1.5 Conceptual Overview of Stock Returns Securities known as stock are issued by businesses as limited liability firms (issuers), which indicates that the individual who holds of the shares also owns the business. A piece of paper known as securities documents the investor's (the party holding the paper) right to acquire a portion of the potential wealth of the company issuing the security, as well as the different circumstances that permit investors who are to make use of his rights. Stocks can be defined as a sign of ownership of a business or limited liability company. A tangible stock of paper is a physical stock that indicates that the possessor of the material is also the proprietor of the business that released the securities in question. The amount of money put in the business determines the ownership stake. The high yield and high-risk qualities of stocks are well-known. In other words, stocks are financial instruments that offer both significant risk and profit potential. With stocks, investors can quickly realize significant returns or capital gains. However, because stock prices change, investors may experience significant losses quickly. The formation of stock prices is influenced by the supply and demand for these shares. Stated differently, the supply and demand for shares both affect stock prices. 2.1.6 Earnings per Share and Returns Investors' constant pursuit of a reliable and consistent income stream, the selling price for stocks per share is impacted by concentrating on possibilities that yield steady returns over time. However, predicting the price of a business's shares is a difficult way to evaluate its financial performance. The amount of a company's profits that are distributed to each shareholder who holds a share of its underpinning common stock, net of liabilities and preferred stock dividends, is known as dividends per share, or EPS. Comparing the overall quantity of shares exchanged during a reporting period (often quarterly or annually) with the number of dollars of net profits achieved during the exact same period makes the calculation straightforward. P-ISSN 2695-186X Commonly used, EPS is a frequently studied measure of a business's earnings per share of its owners. Consequently, it significantly affects share prices. There are two methods for calculating EPS: basic and completely diluted. A more realistic metric that is frequently used is fully diluted EPS, which accounts for the potentially dilutive impacts of warrants, contracts on stock, similar instruments converted into common shares (Basely and Brigham, 2022). It's crucial to keep in mind that results are frequently manipulated, restated, and subject to accounting adjustments, even if profits per share is sometimes regarded as the most popular indicator of a company's profitability. Because of this, some people believe that the volume of free cash circulating is a more accurate indicator than EPS. 2.2 Theoretical Review The theory upon which this study anchored is explained in this section of the study. 2.2.1 The Signaling Theory Ross (1977) propounded the signaling theory, which explains how a corporation should alert prospective investors. These signals notify the user of the steps taken by management to satisfy the desires of the owner. According to signaling theory, it is crucial to communicate investors' perspectives on the company's future. Investors are supposed to use dividend announcements as a signal in making investment decisions. Managers possess details regarding the company's attributes that the market does not have access to. If the company's planned or existing investments have a favorable impact on its potential cash flows, this information is advantageous. The general public will be pleased and knowledge will be trusted if management can convey a compelling message, and the stock price will reflect this. It is crucial that management activities send signals to the public and investors due to asymmetric information. 2.3 Review of Empirical studies Gurung and Subedi (2024), investigated the relationships between market price per share and its determinants—Earnings Per Share , Dividends Per Share , Book Value Per Share , Price-to-Earnings (P/E) ratio, and Total Assets (TA)—in commercial banks in Nepal. The methodology employed the stepwise regression analysis, the study examined data from 16 out of 19 listed commercial banks on the NEPSE, covering cross- sectional period from 2007 to 2023, with 171 yearly observations. The analysis revealed that EPS is undoubtedly an important variable, in addition to BVPS and the P/E ratio, to explain the MPS of commercial banks. Conversely, DPS and TA were found to have no significant effects on MPS. The study findings have far-reaching implications for Nepal's economic sector, including bank financial health, investor behavior, market efficiency, and overall economic growth. Banks may improve their performance and support to contribute to a stable and prosperous economy by emphasizing on important financial parameters. The sample consists of six manufacturing businesses listed on the Jordanian stock exchange between 2011 and 2021. Using panel data, a model was developed to assess the stock price drivers of manufacturing businesses. To determine if a link exists between the dependent variable and the independent variable, a model utility test is used in regression. P-value hypothesis testing is often employed in model utility testing. R2 coefficient of determination is used in this paper's model utility test approach. A simple linear regression model with significance levels = 0.01, 0.025, and 0.05 is used to assess the usefulness of the model utility test in determining the significance of the regression model. It is shown that findings revealed a negative association between net income and share price, but a positive relationship between P-ISSN 2695-186X Earnings Per Share and stock price. Investors may utilize the study's findings to make investment decisions by paying attention to the company's financial parameters, such as earnings per share and net income. This study recommends that investors should be aware of the factors that influence stock prices prior to making investing decisions if they want to ensure that they will receive a reasonable return. Kata (2022), examined the influence of firms’ profitability and stock returns. The research aims to test whether profitability always has a positive relationship with the company stock returns. The research conducted quantitatively by using numerical data in investigating the hypothesis. The data and financial numbers are from secondary data source, in the form of financial statements and market statistics on the Indonesia Stock Exchange website. To give the best result and perspective, this research collected the data from 2017-2019 as the peak performance of Consumer Goods Industry in 2017 and the worst at 2019. The population of this research is 52 companies inside the Consumer Goods Industry. Purposive sampling method was used to find the relevant data by certain criteria. These criteria of the samples are: (1) Companies listed in Indonesia Stock Exchange from 2016 until 2020 and never delisted to assume that the companies are stable enough. (2) Companies that have complete Net Income, Return on Equity, Sales Growth, and Stock Price data from 2016 until 2020. Thirty-five companies met the required criteria, and the total data is 105.The research used multiple regression analysis with t-Test, f-Test, and Coefficient Determination to examine the influence direction of independent variables on dependent variables. The result indicates that net income and return on equity have a significant positive effect on the stock returns; otherwise, sales growth has no significant effect on the stock returns. Sulastri et al. (2024) examined the overview of the profitability of stock return in financial technology companies listed on the NASDAQ. The type of research used is descriptive and verification research with explanatory research methods. The sampling technique in this study is purposive sampling technique with a total sample of 6. Financial technology companies listed on the NASDAQ are the objects in this study. The data analysis technique used in this study is a panel data regression analysis technique with data processing applications using the E-views 12 program. This study obtained findings showing that profitability negatively affects stock return. Based on the results of this study, it can be concluded that when profitability increases, stock return do not increase. Tantri et al. (2022) observed the simultaneous and partial effect of Return on Investment , Earnings per Share and Market Value Added on Stock Return. The type of research is explanatory with quantitative approach. The data collection method for this research is using descriptive, inferential statistic and multiple linear regression. The sample used in the research before doing the outliers procedures was 16 companies chosen with purposive sampling. The research uses outliers’ procedures to remove sample data that has extreme value. The result using outlier procedures only find 8 companies that was analyzed in descriptive inferential statistic and multiple regression. The result of T-Test shows that, ROI, ROE, EPS and MVА variable have а significant effect on Stock Return simultaneously. ROI Variable does not have а significant effect on the Stock Return partially. ROE Variable has а positive and significant effect on Stock Return partially. EPS Variable has а negative and significant effect on Stock Return partially, ROI Variable does not has а significant effect on the Stock Return partially. Angguliyah and Roy (2022) examined the effect of Earning per Share on Stock Returns with Exchange Rates as moderating variables. This study uses microeconomic factors, namely ROA and EPS as independent variables. Meanwhile, the macroeconomic factor is the exchange rate as a moderating variable. In carrying out the P-ISSN 2695-186X research, the population taken by the researcher is the manufacturing companies listed in the LQ45 index on the IDX for the 2016-2020 period. Purposive sampling is the method used by researchers in taking samples with a total of 7 companies that meet the criteria. The methods to analyze the data of this research are descriptive analysis, multiple linear regression analysis and Moderating regression analysis using the SPSS application. The results of the analysis show that Earning Per Share has no significant effect on Stock Return. Also, results show that the exchange rate cannot moderate the effect of Earning Per Share on stock returns. Adetula et al. (2022) investigated accounting income and Stock Prices in the Nigerian Stock Market. The researcher was motivated to study the extent to which accounting information summarizes stock prices in Nigerian stock market as an indicator of value relevance. Piece of accounting data is termed value relevant if it is significantly related to the dependent variable, which may be expressed by the stock price. The methods used for gauging information contents of various accounting numbers were Ordinary Least Squared , Random Effects Model , and Fixed Effects Model . The findings show that there is a significant relationship between accounting information and share prices of companies listed on the Nigerian Stock Exchange. Dividends are the most widely used accounting information for investment decisions in Nigeria, followed by earnings and net book value. The study therefore recommends that the firms should improve the quality of earnings as manipulated earnings (of which dividends are sub-sets) have large effects on share prices. Etukudo et al. (2022) focused on accounting estimates and the profitability of listed industrial goods firms in Nigeria. Accounting estimates comprise a large and growing component of financial statements, making the dividing line between fact and conjecture. Since capital market inefficiencies can result if investors are led by estimates-based accounting information to misallocate resources, the SEC mandates that firms provide quantitative AE information when “quantitative information is reasonably available and will provide material information for investors”. Provision for employee benefits and provision for liability were used as proxies for accounting estimate while profit after tax was used as proxy for profitability. To achieve the objectives of the study, ex-post facto research design was adopted. The source of data collection is secondary data. Data were generated from annual reports and accounts of the selected firms. The data collected were analyzed using multiple regression analysis. The finding revealed that while Provision for liabilities has a significant effect on the profitability of listed industrial goods firms in Nigeria, provision for employee benefits has no significant effect on the profitability of listed industrial goods firms in Nigeria. Handito and Wiwiek (2019) examined the influence of Earning Per Share , Price Book Value , effect on Stock Return. In the study, the author used 4 ratios such as Earning Yield (EY), Price Book Value , Return On Asset , and Return On Investment effect on 20 companies stock return that listed for 10 years in LQ45 index from 2014- 2018 with Market Return as control variable. This study found that Earning Yield (EY), Price Book Value , Return on Asset , and Market Return has affecting stock return altogether. Partially all the variables have positive significant effect on stock return. 2.4 Gap in Empirical Literature Preliminary literature review indicates that empirical studies undertaken on the effect of EPS and ROI on stock returns of selected Manufacturing Companies in Nigeria have not been exhaustive. More so, in very recent years, many studies explored the influence of accounting income on the organizational performance without examining the effect on the stock returns. P-ISSN 2695-186X Other studies tend to aggregate the components of accounting income, but failed to examine their distinct effect on the stock returns of Manufacturing Companies in Nigeria. Another potential gap is the scarcity of the study on the effect of EPS and ROI on stock returns of Manufacturing Companies in Nigeria. Given a preliminary review, most studies in this area are mostly undertaken outside Nigeria. Also, there is scarcity of longitudinal studies that track the effect of accounting income on stock returns of Manufacturing Companies in Nigeria. Most studies offer cross-sectional analyses, which provide only a snapshot of the relationship. Longitudinal research could offer more robust insight into how accounting income evolve and their long-term effect on performance. 3.0 Methodology 3.1 Research Design Panel data was used for the study and this was based on ex-post facto research design. The panel data has the characteristics of time series and cross sectional as the data were collected from many companies in many years. The data collected already exist and the study made used of it in its original form. The study employed Ex-post facto, because it used data of past performance of the selected manufacturing organisation. 3.2 Population of the Study The research population comprises of thirty-five (35) manufacturing companies listed on the Nigerian Exchange Group as at December 2025. For the purpose of this study, nine (9) manufacturing companies were selected for the study. Table3.1: List of selected Manufacturing Companies in Nigeria Exchange Group i. ii. Champion Brewery Plc iii. Guinness Nig. Plc iv. Nestle Nigeria Plc. v. GlaxoSmithKline Consumer Nig Plc. vi. Lafarge Africa Plc vii. Livestock Feeds Plc. viii. Cadbury Nigeria Plc ix. Cutix Plc x. Dangote Cement xi. Lafarge Africa Plc xii. Meyer Plc xiii. BUA Brewery xiv. Premier Paint Plc xv. Berger Paints Plc xvi. First Aluminum Nigeria Plc xvii. Unilever Nigeria Plc xviii. Golden Penny xix. PZ Cussons xx. International Brewery Plc xxi. Enamelware Plc xxii. BUA Cement xxiii. May and Baker xxiv. Fidson Plc xxv. Berger Plc xxvi. Dunlop Plc xxvii. Nestle Nigeria Plc xxviii. Betaglass Plc xxix. Dangote Flour Mills Plc xxx. Vitafoam Nigeria Plc xxxi. Breaklines Plc xxxii. Dangote Sugar Plc xxxiii. Honeywell Flour Plc xxxiv. International Brewery Plc xxxv. Ashaka Cement Plc xxxvi. McNichols Plc. Source: Researchers’ Compilation, (2026) P-ISSN 2695-186X 3.3 Sampling Technique The study utilized simple random sampling technique and nine (9) manufacturing companies were selected from the purpose of the study. The goal of random sampling technique is to ensure that the sample is unbiased and representative of the population, allowing researchers to make inferences about the population based on the sample data. 3.4 Source and Nature of Data The study is a secondary research. Secondary data were obtained from audited annual reports published on the Nigerian Exchange Group and from Fact Books of the nine (9) manufacturing companies selected for the purpose of the study. 3.5 Measurement and Description of variables The variables in the regression model is expected as follows: Table 3.1 Measurement and Description of variables The following summarizes the variables and their formulae for calculations. Variables Formula Description Apriori Expectation Stock Returns (SR) P1 −PO P0 Pı = Closing Price of the stock P0 = Opening price of the stock Measures gains/losses of investors in a particular period of time Earnings per Share (Net Income−Preferred Dividen total number of outstanding shar Measure market efficiency in terms of profitability Positive Return on Investment : Gain from Investment−Cost of i Cost of Investment Measures the profitability of an investment by comparing the gain or lost to it cost. Positive 3.6 Model Specification The model used was premised on the main objectives and anchored on the sub-objective. The following mathematical model were developed to analyse the effect of EPA and ROI on stock returns of Manufacturing Companies in Nigeria. The study adapted Easton and Harris (1991) valuation model. This give the background to the work. It establishes that there is relationship between accounting income and stock returns. This prompted the researcher to adapt the model because it suit the researcher’s research variables. The Easton and Harris (1991) Valuation Model Easton and Harris’s (1991) valuation model expresses stock returns as a function of earnings levels and earnings changes, with both variables deflated by the stock price at the end of the previous year. P-ISSN 2695-186X ΔNI i,t Pri i,t-1 NI i,t Pri i,t-1 ΔNI i,t Pri i,t-1 NI i,t Pri i,t-1 In statistical notation, the model is as follows: Ret i, t = αo + α1 + α2 + Ɛ i,t Model 3.1 where Ret i,t is the stock return of firm i at time t, measured three months after the fiscal year end (Easton and Harris, 1991), the net income (NI) of firm i at time t, before taxes and extraordinary items (NIi,t) divided by the number of common shares outstanding and deflated by the market price at the end of the previous year (Pri t-1) and the change in the net income of firm i at time t, before taxes and extraordinary items (∆NI i,t) divided by the number of common shares outstanding and deflated by the market price at the end of the previous year (Pri,t-1). Last, ε i,t is an error term that follows a normal distribution with mean zero and standard deviation σε . The Easton and Harris model measures the information content of earnings levels and changes for stock returns and thus can be described as providing evidence on the differential relationship between earnings and prices. The model can be used to assess annual differences in the information content of the accounting variables between the pre- and post-IFRS periods. However, Easton (1999) provides some additional insights on the interpretation of the slope coefficients α1 and α2. Specifically, assuming that the clean surplus relation holds, he argues that slope coefficient α1 is a proxy for the statistical association between the stock price and the book values of equity per share. In addition, slope coefficient α2 measures the statistical association between stock prices and earnings per share. Econometrically the basic model is stated as; SRit = β0 + β1EPSit + β2ROIit + e Equation 3.1 This equation can be rewritten as putting the variables SR = f (EPS, ROI, ) Model 3.2 Whereas: β0 = Intercept SR = Stock Return EPS = Earnings per Share ROI = Return on Investment e = Error term t = Time dimension i = individual firm 3.7 Method of Data Analysis The secondary data collected was analyzed using descriptive statistics, correlation analysis, regression and interaction analysis. Multiple regression analysis was used to evaluate the effect of the independent variables with the aid STATA. The result is to reveal the degree of influence and the level of significance. The collected research data were checked for any errors and omissions, coded, defined and then entered into STATA. This study used both descriptive and inferential statistics. A panel data was used to evaluate the hypotheses. First Order Econometric Tests The statistical criteria that was used to test the first-order hypotheses include: P-ISSN 2695-186X The economic apriori expectation evaluated the parameter in terms of their meeting the standard economic theory expectations. Statistical tests are done to evaluate reliability of the estimated parameter in accordance with statistical theory and expectation. The statistical test that were carried out included: 1 The t-test: this is used to test the significance of the individual parameters of the regression model. The decision to accept null hypothesis is based on the value of the test statistics from the data at hand. A high t – statistic indicates that the independent variable is significance in explaining the variation in the dependent variable. In this study, we will use a significance level of 0.05. 2 The f-test: this measure the overall significance of the model. The null hypothesis for the F-test is that all the regression coefficient is equal to zero, implying that the independent variables do not have any significance influence on the dependent variable. This was carried out to ascertain whether, an individual regression co-efficient is statistically significant. If the calculated F-statistic is greater than the critical value of the F-distribution, the null hypothesis is rejected, and it conclude that at least one independent variable has a significant influence on dependent variable. Conversely, if the calculated F-statistic is less than the critical value of the F-distribution, the null hypothesis is accepted, and it conclude that none of independent variable has a significant influence on dependent variable. 3 Co-efficient of Determination (R2): The goodness of fit test was carried out using the square of the correlation co-efficient. It shows or explains the percentage in total variation of the endogenous variable being explained by the change in the explanatory variables. It measures the extent to which the explanatory variables are responsive for judging the explanatory power of the regression. 3.7.2 Second Order Econometric Tests The test was performed on the regression result in order to evaluate it according to the classical assumptions of Ordinal Least Square . These tests are discussed briefly below: 1. Test for multi-collinearity: This was used to test the linear collinearity among the explanatory variables and correlation matrix would be employed in this test. Multi-collinearity was used to test the linear collinearity among the explanatory variables, whether the independent variables are actually independent or they are linked to each. 2. Unit Root Test: the purpose of the test is to check the stationarity of the time series data in order to avoid having a spurious regression result. To check for stationarity, the Augmented Dickey-Fuller test was utilized. 3. Auto-correlation test: This was used to test if the errors corresponding to different observation is uncorrelated, testing for the randomness of error term. The Durbin-Watson (DW) method would be employed for this test, since according to Koutsoyannis (1997) D.W, provides estimates which have properties and are more efficient for all sample of all sizes. 4. Heteroscedasticity test: This was used to know whether error term of the explanatory variables of the estimated model have equal variance. P-ISSN 2695-186X 5. Normality test: This was used to know whether the error term of the estimated model is normally distributed. 6. Heteroscedasticity Test: Breusch-Pagan-Godfrey: Heteroscedasticity refers to situation where the variance of the residuals is unequal over a range of measured values. This is used to know whether error term of the explanatory variables of the estimated model have equal variance. 4.0 Results and Findings This section presents all the results of the empirical analysis with their interpretations. Data used for this analysis are time series that cover the period 2015-2025. The empirical results were generated using E-views 13 econometric software. 4.1 Data Analysis The descriptive test summarizes the descriptive statistics of the model variable testing the appropriateness and normality of the variables as modeled. Summary result of the descriptive test is presented on Table 4.1 Table 4.1: Descriptive Statistics Source: Researchers’ Computation using E-views 13.0 (2026) Table 4.1 shows that SR, EPS, and ROI, had mean values of 1.038699, 200.2321, and 15.93378, respectively. This indicates the central or average values for these variables used in the study. In terms of the level of variability and dispersion in the distribution of these variables, the standard deviations obtained for the variables were 0.468159, 299.9707 and 26.49376, respectively. This indicates varying levels of variability in the distribution. Similarly, from the skewness values obtained, SR, EPS, and ROI, showed positive skewness values meaning they were all skewed to the right. This indicates that the mean values of these SR EPS ROI Mean 1.038699 200.2321 15.93378 Median 1.016129 93.91743 11.02991 Maximum 3.273322 1390.117 152.1094 Minimum 0.195779 -585.8453 -82.52039 Std. Dev. 0.468159 299.9707 26.49376 Skewness 1.864935 1.588158 1.159385 Kurtosis 8.837431 6.442526 10.94205 Jarque-Bera 197.9486 90.50239 282.3681 Probability 0.000000 0.000000 0.000000 Sum 102.8312 19822.97 1577.444 Sum Sq. Dev. 21.47893 8818278. 68788.08 Observation s 99 99 99 P-ISSN 2695-186X variables were greater than their median and mode. The Kurtosis values obtained for the variables were showed in the table respectively. Since the values of the kurtosis are greater than three (3), it indicates a mesokurtic distribution, hence the presence of outliers in the data for the variables. Finally, based on the Jarque-Bera probability values obtained, all variables (SR, EPS, and ROI, indicated normality in their distribution, given that their Jarque-Bera probability was greater than 0.05. 4.2 Multicollinearity Test In evaluating multicollinearity, the study examines the correlation coefficients using correlation matrix and the variance inflation factor . For correlation matrix, multicollinearity occurs when the magnitude of the correlation coefficient exceeds .80 (Kim, 2019; Benjamin, et al., 2023). Table 4.2: Correlation Matrix SR EPS ROI SR 1.000000 0.217046 0.110126 EPS 0.217046 1.000000 -0.045890 ROI 0.110126 -0.045890 1.000000 Source: Researcher’s Computation using Eviews 13.0 (2026) From the correlation matrix result on Table 4.2, there is no problem of multicollinearity, given that the magnitude of the correlation coefficient does not exceed 0.80. Table 4.3: Variance Inflation Factor Variance Inflation Factors Date: 06/17/26 Time: 03:32 Sample: 1 99 Included observations: 99 Coefficient Uncentered Centered Variable Variance VIF VIF EPS 2.67E-08 1.618213 1.115924 ROI 8.53E-06 3.798317 2.781850 C 0.007078 3.320662 NA Source: Researchers’ Computation using E-views 13.0 (2026) For Variance Inflation Factor , multicollinearity occurs when the VIF exceed 10. (Marcoulides and Raykov, 2019). The test conducted in Table 4.2 indicate the absence of violations of the assumption of multicollinearity on all the variables used in the study (given that Centred VIF values is less than 10). P-ISSN 2695-186X Heteroscedasticity Test: Breusch-Pagan-Godfrey Heteroscedasticity refers to situation where the variance of the residuals is unequal over a range of measured values. This is used to know whether error term of the explanatory variables of the estimated model have equal variance. The result revealed there is no heteroscedasticity, given that the Prob (F-Statistic) and Prob (Chi-Square) are both 0. Table 4.4: Heteroskedasticity Test: Breusch-Pagan-Godfrey F-statistic 1.312286 Prob. F(6,92) 0.2596 Obs*R-squared 7.804835 Prob. Chi-Square(6) 0.2528 Scaled explained SS 24.95107 Prob. Chi-Square(6) 0.0003 SSource: Researchers’ Computation using E-views 13.0 (2026) Given that the probability value associated with the Chi-Squares is significantly greater than 0.05 levels, we accept the null hypothesis that there is no heteroscedasticity in the model. 4.2. Testing of Hypotheses Hypothesis One: HO1: There is no significant influence of Earnings per Share on stock returns of selected Manufacturing Companies in Nigeria. Table 4.5: OLS Analysis showing the influence of Earnings per Share on stock returns of selected Manufacturing Companies in Nigeria Dependent Variable: SR Method: Least Squares Date: 06/17/26 Time: 05:17 Sample: 1 99 Included observations: 99 Variable Coefficient Std. Error t-Statistic Prob. C 0.970873 0.055594 17.46375 0.0000 EPS 0.000339 0.000155 2.189862 0.0309 R-squared 0.047109 Mean dependent var 1.038699 Adjusted R-squared 0.037286 S.D. dependent var 0.468159 S.E. of regression 0.459348 Akaike info criterion 1.301979 Sum squared resid 20.46707 Schwarz criterion 1.354405 Log likelihood -62.44794 Hannan-Quinn criter. 1.323191 F-statistic 4.795497 Durbin-Watson stat 2.081896 Prob(F-statistic) 0.030932 Source: Researchers’ Computation using E-views 13.0 (2026) The regression line can be written as follows: SR = 0.970873 + 0.000339 EPS + e P-ISSN 2695-186X The equation implies that if the independent variable were held constant, SR will grow on an average rate of 0.970873. Furthermore, the results indicated that EPS exhibited positive relationship with the SR with a coefficient of 0.000339. This means that if other factors remain unchanged, a one-unit increase in EPS will lead to a one-unit increase in SR by 0.000339. The statistical significance of the above relationships was given by the p-value associated with each of the variables. Since this study t-test is based on the 95% level of confidence, a variable is said to have significant effect if its p-value is less than or equal to 0.05. Therefore, with the p-value of 0.0309, EPS is said to have a significant effect on SR. The R-squared value of 0.047109 indicates that about 0.047109 variation in SR is accounted for by the independent variable of this study. In order to test the hypothesis, the researcher relied on the p-value of the F-statistic. The result shows the p-value of 0.0309 which implies that the independent variable has a significant effect on the dependent variable. Therefore, the null hypothesis which states that there is no significant influence of Earnings per Share on stock returns of selected Manufacturing Companies in Nigeria, is rejected. Hypothesis Two: HO2: Return on Investment has no significance effects on stock returns of selected Manufacturing Companies in Nigeria. Table 4.6: Table OLS Analysis showing the influence of Return on Investment on stock returns of selected Manufacturing Companies in Nigeria. Dependent Variable: SR Method: Least Squares Date: 06/17/26 Time: 05:29 Sample: 1 99 Included observations: 99 Variable Coefficient Std. Error t-Statistic Prob. C 1.007693 0.054927 18.34620 0.0000 ROI 0.001946 0.001783 1.091250 0.2779 R-squared 0.012128 Mean dependent var 1.038699 Adjusted R-squared 0.001943 S.D. dependent var 0.468159 S.E. of regression 0.467704 Akaike info criterion 1.338032 Sum squared resid 21.21844 Schwarz criterion 1.390458 Log likelihood -64.23257 Hannan-Quinn criter. 1.359244 F-statistic 1.190826 Durbin-Watson stat 2.039908 Prob(F-statistic) 0.277866 Source: Researchers’ Computation using E-views 13.0 (2026) The regression line can be written as follows: SR = 1.007693+ 0.001946 ROI + e The equation implies that if the independent variable were held constant, SR will grow on an average rate of 1.007693. Furthermore, the results indicated that ROI exhibited positive relationship with the SR with a coefficient of 0.001946. This means that if other factors remain unchanged, a one-unit increase in ROI will lead to a one-unit increase in SR by 0.001946. P-ISSN 2695-186X The statistical significance of the above relationships was given by the p-value associated with each of the variables. Since this study t-test is based on the 95% level of confidence, a variable is said to have significant effect if its p-value is less than or equal to 0.05. Therefore, with the p-value of 0.2779, ROI is said to have an insignificant effect on SR, given that the p- values is greater 0.05. The R-squared value of 0.012128 indicates that about 0.012128 variation in SR is accounted for by the independent variable of this study. In order to test the hypothesis, the researcher relied on the p-value of the F-statistic. The result shows the p-value of 0.277866 which implies that the independent variable has an insignificant effect on the dependent variable. Therefore, the null hypothesis which states that there is no significant influence of Return on Investment on stock returns of selected Manufacturing Companies in Nigeria, is accept. Discussion of Findings The result of the first hypothesis indicates that about 0.047109 variation in SR is accounted for by the independent variable of this study. In order to test the hypothesis, the researcher relied on the p-value of the F-statistic. The result shows the p-value of 0.0309 which implies that the independent variable has a significant effect on the dependent variable. Therefore, the null hypothesis which states that there is no significant influence of Earnings per Share on stock returns of selected Manufacturing Companies in Nigeria, is rejected. The result is consistent with previous studies where accounting information had a positive and significant effect on share prices (Adetula et al., 2021; Gharaibeh et al., 2022). The result of the second hypothesis indicates that about 0.012128 variation in SR is accounted for by the independent variable of this study. In order to test the hypothesis, the researcher relied on the p-value of the F-statistic. The result shows the p-value of 0.277866 which implies that the independent variable has an insignificant effect on the dependent variable. Therefore, the null hypothesis which states that there is no significant influence of Return on Investment on stock returns of selected Manufacturing Companies in Nigeria, is accept. The findings are in contrast with some prior studies (Tantri et al., 2022). 5.0 Summary and Conclusion The followings are the summary of the findings: 5.1 Summary and Major findings i. Earnings per share has a positive and significance influence on stock returns of selected Manufacturing Companies in Nigeria. ii. Return on Investment has a positive and insignificant effect on stock r e t u r n s of selected Manufacturing Companies in Nigeria 5.2 Conclusion The main objective of the study was to examine the effect of accounting income on stock of selected manufacturing companies in Nigeria. Ex-post-facto research design was adopted for the study. The data for the study were obtained from secondary source (that is from the published financial statement of Consumer goods manufacturing companies) for the period of eleven years (2013 to 2023). Ordinary least square regression, with the aid of E-views 13, was used in analysing the data and testing the stated hypotheses. 5.3 Business Implications of the Findings In line with the findings of the study, the following business implications were made: P-ISSN 2695-186X i. The significant effect of EPS and ROI on stock returns suggests that investors in the Nigerian manufacturing sector may prioritize other factors, such as market trends and macroeconomic conditions, over financial statements. This implies that businesses must complement their financial disclosures with other value-driven strategies to attract investors. ii. Companies should focus on improving financial reporting quality and transparency to enhance investor confidence. The findings indicate that financial statements alone may not be enough to drive stock prices, possibly due to concerns about earnings management or information asymmetry. Strengthening corporate governance and adopting high-quality financial reporting standards can improve the credibility of accounting information. 5.4 Recommendations i in the light of the finding that EPS has a positive and significant influence on SR, Manufacturing companies in Nigeria should continue to focus on increasing net income and reducing shares outstanding to boost EPS. This can be achieved by improving operational efficiency, engaging in share repurchase or buyback, reducing cost and increasing revenue by expanding product lines, and enhancing sales strategies. ii Based on the finding that ROI has a positive and insignificant influence on SR, Manufacturing companies should look beyond ROI when evaluating investment opportunities. Emphasis should be placed on optimizing investment strategies, reducing costs, and increasing revenue. This can be achieved by investing in project with high returns, improving operational efficiency, and enhancing productivity. 5.5 Suggestion for further studies Further studies should analyze how macroeconomic variables (e.g., inflation, exchange rates, interest rates, and GDP growth) and industry-specific factors (e.g., competition, government policies, and production costs) affect the stock returns of manufacturing firms. 5.6 Contribution to Knowledge This study contributes to the body of knowledge in accounting and finance by providing empirical evidence on the relationship between accounting income and stock returns in the Nigerian manufacturing sector. Unlike many prior studies that establish a strong link between financial performance and stock market behavior, this research reveals a statistically insignificant effect, suggesting that investors may rely more on non-accounting factors when making investment decisions. Additionally, the study sheds light on the potential inefficiencies in the Nigerian stock market, where accounting information may not be fully reflected in stock prices. This finding contributes to the discourse on market efficiency in developing economies and calls for further investigation into alternative determinants of stock returns. P-ISSN 2695-186X References Adetula, M. Alsksi, K. and Ryaka, Y. (2022). Accounting income numbers and Stock Prices in the Nigerian Stock Market. Contemporary Accounting Research, 11 661–688. Alexei, M., and Andru, T., (2022). Stock market reactions to the release of annual financial statements case of the banking industry in Sri Lanka. 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