







































 
 

 

1 
© 2023 by the authors; licensee Asian Online Journal Publishing Group 
 

Economy 
Vol. 10, No. 1, 1-9, 2023 

ISSN(E) 2313-8181/ ISSN(P) 2518-0118 
DOI: 10.20448/economy.v10i1.4517 

© 2023 by the authors; licensee Asian Online Journal Publishing Group 

 
 

 
 
 
Fundamental factors and stock price volatility of listed banking firms in Nigeria 

 
INIM, Victor Edet1    
MOHAMMED, Abdulrazak2 

Bassey Ime FRANK3   

 
( Corresponding Author)  

 
1,2Department of Accounting, Nile University of Nigeria, Abuja, Nigeria. 
1Email: victor.inim@nileuniversity.edu.ng  
2Email: mabdulrazak@see.gov.ng  
3Department of Insurance, University of Uyo, Uyo, Akwa Ibom, Nigeria. 
3Email: basseyifrank@uniuyo.edu.ng   

 
  Abstract 

The study examined the impact of fundamental factors on the stock prices of Nigeria's listed banking 
sector companies. Using panel data analysis, the effects of five fundamental variables on share prices 
of listed banks in Nigeria, which include return on assets (ROA), return on equity (ROE), earnings 
per share (EPS), dividend per share (DPS), and growth in net interest income (NII), as well as two 
control variables (firm size and firm age), were analyzed. Data were gathered from eleven sampled 
banks' annual reports from 2006 to 2020. Based on the Hausman test, fixed effect model was 
estimated and regression results indicated that the coefficients of ROE, EPS, DPS, NII and SIZE 
were positive but ROE and SIZE were statistically not significant. On the other hand, the 
coefficients of ROA and AGE were negative but statistically significant. The study recommended 
that; regulators should pay attention to earnings management by banks to monitor any attempts to 
smooth dividend; existing shareholders should pay more attention on high dividend paying banks 
for capital gain; and boards of directors of banks should strive to maintain adequate dividend 
payment, specifically by reducing the proportion of yearly retain earnings while minimizing cost. 

 
Keywords: Dividend per share, Earnings per share, Fundamental factors, Net interest income, Return on asset, Return on equity, Volatility. 
JEL Classification D53; E44; G21. 
 

Citation | Edet, I. V., Abdulrazak, M., & FRANK, B. I. (2023). 
Fundamental factors and stock price volatility of listed banking firms 
in Nigeria. Economy, 10(1), 1–9. 10.20448/economy.v10i1.4517 
History:  
Received: 2 September 2022 
Revised: 7 February 2023 
Accepted: 24 February 2023 
Published: 9 March 2023  
Licensed: This work is licensed under a Creative Commons 

Attribution 4.0 License  
Publisher:  Asian Online Journal Publishing Group 
 

Funding: This study received no specific financial support. 
Authors’ Contributions: All authors contributed equally to the conception and 
design of the study. 
Competing Interests: The authors declare that they have no conflict of 
interest. 
Transparency: The authors confirm that the manuscript is an honest, accurate, 
and transparent account of the study; that no vital features of the study have 
been omitted; and that any discrepancies from the study as planned have been 
explained. 
Ethical: This study followed all ethical practices during writing. 

 

 

Contents 
1. Introduction ......................................................................................................................................................................................... 2 
2. Theoretical Framework ..................................................................................................................................................................... 4 
3. Methodology ........................................................................................................................................................................................ 4 
4. Data Analysis and Results ................................................................................................................................................................. 6 
5. Discussion of Findings ....................................................................................................................................................................... 8 
6. Conclusions and Recommendations ................................................................................................................................................ 9 
References ................................................................................................................................................................................................. 9 
 

 
 

 

 

 

 

mailto:victor.inim@nileuniversity.edu.ng
mailto:mabdulrazak@see.gov.ng
mailto:basseyifrank@uniuyo.edu.ng
https://creativecommons.org/licenses/by/4.0/
https://creativecommons.org/licenses/by/4.0/
https://www.doi.org/10.20448/economy.v10i1.4517
https://orcid.org/0000-0001-7895-2114
https://orcid.org/0000-0003-0800-4834


Economy, 2023, 10(1): 1-9 

2 
© 2023 by the authors; licensee Asian Online Journal Publishing Group 

 

 

Contribution of this paper to the literature 
The study contributes to existing literature by investigating the impact of fundamental factors 

on the stock prices of Nigeria's listed banking sector companies. 

 
1. Introduction 

There are many important roles played by financial markets in an economy. It encompasses mobilization of 
financial resources from the surplus units to the deficit units of the economy, also including the provision of the 
medium for; separating ownership and management, risk sharing, efficient allocation of financial resources and 
ascertainment of current and future consumption requirements, among others. As stated by Fouzan, Tahtamouni, 
and Al-Qudah (2016), listed institutions can deploy securities and increase fund through various market securities.  

More specifically, the stock market, which is a critical segment of the financial markets, assist in the process of 
evaluating managerial performance through investors’ sentiments that are contained in market prices of financial 
instruments. Hence, how much the equity of a company is worth arises from the aggregation of diverse opinions of 
market participants. The market, by means of financial or non-financial disclosures, helps management gauge opinion 
on its investment plans and future actions through market positive or negative reactions to stock prices. Stock market 
plays a substantial part in the allocation of resources, both directly as a source of funds and as a determinant of firms' 
value and its borrowing capacity (Tease, 1993).  

Based on the underlying assumption of efficient market hypothesis, a market is said to be efficient where asset 
prices reflect all available information. Since market prices should only react to new information, it is therefore 
important to state that most factors that influence investment decision and the environment which businesses thrives 
ultimately impact share prices. By implication, this indicates that stocks are always trading at their current fair 
market value. Many investors are in dilemma with regard making a choice about profitable investment. One of the 
determining factors in taking decision is the share price of the stock which are constantly changing due to various 
factors in the market. Investors have various methods they may adopt in analyzing the investment, which may include 
bottom-up analysis or a top- down approach. The choice for any of these approaches depends on what motive drives 
the investor’s decision. Some investors may adopt a technical analysis approach, where their focus is on the movement 
of the stock price in the market by relying on the historical prices and the volume of shares that were traded, or they 
conduct a fundamental analysis, where the main aim is to check the financial health of firms and the whole economy 
in order to take informed decision about the available stocks in the market.   

Whether stock prices are impacted by firm fundamentals has become a hot topic in financial economics recently. 
However, there is absolutely no agreement among academics as to the key variables that affect stock values. In light 
of this, the goal of this study was to examine the potential relationships between the stock prices of Nigeria's listed 
banks and their underlying financial metrics, including their return on equity, return on assets, earnings per share, 
dividend per share, and growth in net interest income. It is tempting to encourage research into the factors that cause 
apparent volatility in stock prices as well as the ongoing and sporadic changes in accounting and market ratios. 

The results of this study can undoubtedly affect regulatory policy, motivate businesses to improve performance, 
and help investors make wise stock market investing choices. 
 

1.1. Statement of the Problem 
The onset of 2007/2008 global financial crunch wiped out the growth and investors’ confidence and it became 

worrisome to see that even corporations with proven record of success were not spared from these volatilities, 
especially those companies with sound fundamentals such as dividend pay-out and earnings and its components. 
However, as a result of the negative impact of the 2008-2010 global financial crises and 2015-2017 recession in 
Nigeria, All-Share Index plummeted down to 20,838.90 points in 2009 and remained below 30,000 points 10 years 
after, precisely 26,842.07 points as at 31st December 2019. It becomes expedient to consider the interdependence 
between stock market prices and company fundamentals. 

Even with the potentials to make Nigerian listed companies’ financials comparable with their foreign 
counterparts, it is observed that the stock market is yet to return to its old glory, with share prices of most listed 
companies in Nigeria remaining below pre-2008 financial crisis. Investors are also perplexed as to which investment 
to commit their financial resources in order to have optimum returns. In recent times, studies have been conducted 
to determine the impact of certain fundamental factors on the prices of stocks in Nigeria.  

Thus, examining the impact of fundamental factors on the stock prices of Nigeria's listed banking sector 
companies is the primary goal of this study. Other specific goals include assessing the impact of Return on Asset 
(ROA), Return on Equity (ROE), Net Interest Income (NII), Earnings Per Share (EPS), and Return on Equity (ROE) 
on the stock prices of listed banking companies in Nigeria, as well as looking at the impact of the Threshold Effect 
on Stock Prices of Listed Banking Companies in Nigeria. 

In line with the stated objectives, the hypotheses of the study are stated in null forms thus: 
Ho1: Return on Asset (ROA) has no significant effect on Stock Prices of listed banking companies in Nigeria. 
Ho2: Return on Equity (ROE) has no significant effect on Stock Prices of listed banking companies in Nigeria. 
Ho3: Net Interest Income (NII) has no significant effect on Stock Prices of listed banking companies in Nigeria. 
Ho4: Earnings Per Share (EPS) has no significant effect on Stock Prices of listed banking companies in Nigeria. 
Ho5: Dividend Per Share (DPS) has no significant effect on Stock Prices of listed banking companies in Nigeria. 

 Previous studies, like Karki (2018), Pradhan and Laxmi (2017), Shafiqul, Rubel, and Abdul (2016) and Fouzan et 
al. (2016), were conducted to examine the impact of some fundamental factors on stock prices of some selected firms 
in foreign countries with certain peculiar economic variables, using one fundamental factor in some cases thus leaving 
out other fundamental factors which may have had some influence on the stock prices of those firms. However, since 
findings from empirical studies reviewed were quite mixed for different markets and industries, the unique feature of 
this paper is that, first, it lengthened the study period to 15 years ending 2020 to cover period of capital market boom, 
crash and period of stability. Second, it incorporated growth in Net-interest income not used in any study in Nigeria, 
which is banking industry specific measure of profitability, to determine its influence together with four other 
dominant fundamental factors, on stock price of banking sector stock. Finally, the study lengthens the current 



Economy, 2023, 10(1): 1-9 

3 
© 2023 by the authors; licensee Asian Online Journal Publishing Group 

 

 

discussions on stock prices of firms, thereby adding to the existing literature in the region of fundamental factors as 
they affect share prices. 
 

1.2. Concept of Stock Prices 
Stock price is an indicator, reflecting a security or company's current market value. It is the price agreed by both 

a buyer and a seller at a particular point in time or at an agreed further date. In a market driven economy, share price 
is determined by the forces of demand and supply. Usually, where there are more buyers than sellers, the stock price 
will climb and vice-versa the price may decline. To a large extent, volatility in stock prices could be attributed to 
concern about or the direction of economic indicators such as interest rates, tax changes, inflation rates, and other 
monetary policies. Share prices can also be influenced by industry dynamics, domestic and global events. 
 

1.3. Return on Asset 
The ability of a business to use its assets to generate net profit is measured by return on asset (ROA). In a perfect 

market, a stock with a higher ROA ought to be costlier. Return on assets is the ratio of a company's annual net 
income to its average annual total assets (ROA). It displays how effectively a business uses its resources to produce 
net income. The profitability ratio is as follows (Zutter & Gitman, 2012). A growing ROA demonstrates an 
organization's ability to fully utilize its resources. It also shows that management is skilled at making the most of 
the resources at its disposal to generate higher cash flows with the same or less capital. 
 

1.4. Return on Equity 
The return on equity (ROE) formula calculates the amount of profit a company generates for each dollar invested 

in shares by shareholders. It is determined by dividing the relevant net income of the firm by the typical equity 
capital. If both ordinary and preference shares have equity rights, the appropriate net income will be the profit after 
tax, which is the amount available to ordinary and preference shareholders for distribution. When preference shares 
are excluded from the definition of equity, the pertinent returns will be net of earnings after tax and dividends on 
preference shares. To calculate average equity, one can use either the simple average or the weighted average 
approaches. In addition to examining the company's profitability, ROE also evaluates its efficacy. An increasing ROE 
shows that a company is getting better at generating profit while requiring less capital. Higher ROE is also 
advantageous for investments. The return on equity demonstrates how well and successfully the shareholders' money 
was managed by the company (Ugwudioha, 2019). Therefore, it is presumed that ROE and stock price have a positive 
relationship. 
 

1.5. Net Interest Income 
It is a metric of profitability unique to the business for banks and other financial institutions that lend out interest-

earning assets. Net interest income is the difference between interest collections and costs (NII). The interest 
payments that banks earn on their interest-bearing assets are known as interest revenues, while the costs related to 
servicing the interest payments that banks make to their depositors are known as interest expenses. Banks receive 
interest through loans, mortgages, and other items that bear interest. On the other hand, in addition to income on 
deposit accounts like savings and CDs, they also deduct interest on any additional debt the bank may have. A 
significant source of income for banking institutions, net interest income is thought to include the cost of financial 
intermediation. The difference between what borrowers pay for their loans and what lenders make from lending is 
consequently what it is. In addition to other measures, banks might use net interest income to assess a company's 
internal profit potential. Investors who are looking at a bank's financial accounts might find this metric fascinating. 
 

1.6. Earnings Per Share 
Profit expressed per outstanding share of stock is known as earnings per share (EPS), and it is a key financial 

metric of a company's performance. The share price of a corporation is determined using it. A high EPS implies that 
the company is more successful and has more profits to distribute to shareholders. This ratio establishes a correlation 
between potential growth prospects and higher investor returns. In light of this, it seems to reason that EPS, which 
illustrates a company's growth, would have a positive effect on share prices. 
 

1.7. Dividends Per Share 
Dividend per share shows how much a corporation pays out in annual dividends in relation to each of its shares. 

Without any capital gains, dividend is the stock's return on investment. According to Ugwudioha (2019) investors 
frequently inquire about a company's dividend per share in order to assess the viability of the business and the value 
of each share. 
 

1.8. Empirical Review 
Karki (2018) used information from Nepalese commercial banks to examine the fundamentals of common stock 

pricing. The focus of the work was to establish the causal relationship between the fundamental factors and the 
changes in the Nepalese commercial banks’ stock prices, using earnings per share, book value per share, cash dividend 
per share, stock dividend per share, price earnings ratio, and firm size as proxies for fundamental factors. Using 
secondary data, a balance panel data from 150 observations were utilized from year 2000 to year 2014. The result 
indicated that earnings per share and stock dividend per share had a greater impact on commercial banks' stock 
values in Nepal than other variables. From the analysis it was observed that the stock dividend was statistically and 
economically the most significant of the six fundamental variables analyzed. 

Pradhan and Laxmi (2017) studied the effect of fundamental determinants on stock prices in the Nepalese 
commercial banks. In the study, market price per share and change in market price per share were the dependent 
variables while return on assets, return on equity, net interest income, earnings per share, and dividend per share 
were the independent variables. Sourcing the needed data from annual reports of the chosen commercial banks as 
well as the Banking and Financial Statistics and Bank Supervision Report released by Nepal Rastra Bank, the research 



Economy, 2023, 10(1): 1-9 

4 
© 2023 by the authors; licensee Asian Online Journal Publishing Group 

 

 

included 104 observations from 13 Nepalese commercial banks between 2007 and 2014. Results from the regression 
analysis showed a favorable relationship between the stock price and dividend per share (DPS), return on assets 
(ROA), and earnings per share (EPS) (market price per share and change in market price per share). This suggested 
that a greater DPS, ROA, and EPS would result in a higher stock price. Net profit margin was, however, inversely 
correlated with stock price. With market price per share at a 5% level of significance, the regression result revealed 
that the beta coefficients for DPS and EPS were positively significant.  

Shafiqul et al. (2016) examined the factors that influence stock prices in listed cement businesses at the Dhaka 
Stock Exchange in Bangladesh, using a panel data set of seven cement industry businesses that were listed on the 
Dhaka Stock Exchange (DSE) between 2006 and 2015. Employing an Ordinary Least Square (OLS) regression with 
fixed effects and random effects models, six fundamental and technical factors, namely: Earnings Per Share (EPS), 
Net Asset Value Per Share (NAVPS), Price Earnings (P/E), Gross Domestic Production (GDP), Consumer Price 
Index (CPI), and Interest Rate Spread (IRS), were identified. Findings from the analysis showed that all the factors 
had significant impact on the share prices of companies in Bangladeshi stock market involved in the cement 
businesses. Fouzan et al. (2016) examined factors influencing stock market pricing in insurance businesses listed on 
the Amman Stock Exchange. The study looked at how certain variables, such as return on asset (ROA), return on 
equity (ROE), debt ratio, age of the company, and size of the company, affect stock market prices. Using simple and 
multiple linear regression, 20 insurance businesses listed on the Amman Stock Exchange between 2011 and 2015 
were analyzed. Results from the analysis showed that there is a relationship between stock market price and ROA, 
Debt Ratio, Age of the Company, and Size of the Company in the firms studied. However, there was no relationship 
between ROE and stock prices of the firms studied.  

 
2. Theoretical Framework 
2.1. Efficient Markets Theory 

The efficient markets theory by Wallace and Thomas (1975) has been discovered to be the most appropriate 
theoretical framework for this investigation (1975). According to this hypothesis, investors purchase stocks they 
anticipate will have higher-than-average returns and sell those they anticipate will have lower returns. They have a 
tendency to raise the prices of stocks with higher-than-average return expectations and drop the prices of stocks 
with lower-than-average return expectations. As soon as the predicted returns, taking into account risk, are equal 
for all stocks, the stock prices start to change. Equalization of expected returns implies that expectations or 
projections of investors are included into or reflected in stock prices. It actually means that stock prices adjust in 
such a way that, after taking into account information like dividends, bonuses, the time value of money, and other 
risks, they equal the best estimate of the future price made by the market. Therefore, only unpredictable, random 
elements that are impossible to predict in advance can affect stock price. According to the Efficient Market 
Hypothesis, a change in the company's fundamentals has the most immediate impact on a stock's price. Because of 
this, a rise in the share price is anticipated whenever revenues and earnings increase. On the other hand, if profit is 
dropping with no sign of change, investors start to give up on stocks, which thus causes the stock price to fall. This 
hypothesis’ claim is that changes in the underlying business typically have impacts on share prices. Therefore, 
investors with keen, quick and imaginative thinking would have predicted a shift even before prices of the stocks 
were affected and thus would have taken an informed decision before the changes occur. 

 

3. Methodology 
The 22 Nigerian commercial banks that have been granted licenses make up the study's population. As of 2020, 

thirteen (13) banks and corporations with subsidiaries that held commercial banking licenses and were listed on the 
Nigerian Stock Exchange (NSE) made up 59% of the 22 banks that fell under the commercial banking license 
category. Due to the availability of quoted stock prices for the banks, convenient sampling was used to concentrate 
the analysis on listed institutions. 

 A few filtration processes have been used to remove some of the banks that were deemed unsuitable for the study 
due to the requirements of the empirical models used in this investigation. First, only surviving firms' data is used 
for the study's empirical portion. Second, institutions with either missing value for the relevant variable were 
disqualified. Ecobank Transnational Incorporated (ETI) and Sterling Bank Plc are two of the excluded banks. 
Following the above-mentioned screening methods, the study's final sample, which is given in Table 1, consists of 
11 banks listed on the Nigerian Stock Exchange, eight of which were among the top 10 banks in Nigeria according 
to Answer Africa's ranking (List of Largest Commercial Banks in Nigeria in 2020). Following is a list of the sampled 
banks along with the date of their incorporation: 

The study used secondary data extracted from the individual financial statements of eleven (11) sampled banks 
over a period of 15 years.  Hence, the analytical framework used is panel data regression, in view of the cross-sectional 
and time series dimensions of the sampled observations. The use of panel data analysis reduces the phenomenon of 
multicollinearity of the variables. 

 

3.1. Model Specification 
In order to examine the influences of ROA, ROE, NII, EPS, and DPS on the stock prices of listed banks in 

Nigeria, this study uses an econometric approach of data analysis. In order to analyze the association between one 
dependent variable, five explanatory factors, and a control variable, the study specifically uses the panel ordinary 
least square (OLS) approach.  

To offer details on individual bank behavior over a range of individual characteristics and over time, a balanced 
panel OLS model is used (2006 - 2020). Consequently, the three popular models used in panel regression-pooled OLS, 
fixed effect, and random effects-are as follows: 

 
 
 
 



Economy, 2023, 10(1): 1-9 

5 
© 2023 by the authors; licensee Asian Online Journal Publishing Group 

 

 

Table 1. List of sampled banks. 

S/N Symbol Security name Date listed  Date of incorporation 

1 Access Access bank of Nigeria PLC November 18th 1998 February 8th 1989 
2 FBNH FBN holdings PLC November 26th 2012 August 13th 2012 but originating 

company existed since 1894 
3 FIDELITYBK FIDELITY bank PLC May 17th 2005 November 19th 1987 
4 FCMB FCMB group PLC June 21st 2013 November 20th 2012 but originating 

company existed since 
20 April, 1982 

5 Guaranty Guaranty trust September 9th 1996 July 20th 1990  
6 STANBIC Stanbic IBTC holdings PLC November 23rd 2012 March 14th 2012 but originating 

company existed since 
2 February 1989 

7 UBA United bank for Africa PLC March 31st 1970 February 23rd 1961 
8 UBN Union bank of Nigeria PLC Since 1971 Since 1917 
9 UNITYBNK Unity bank PLC December 22nd 2005 April 27th 1987 
10 WEMABANK Wema bank PLC February 13th 1991 May 2nd 1945 
11 ZENITHBANK Zenith international bank PLC October 21st 2004 May 30th 1990 

Source: NSE fact books (2020). 

 
The pooled model specification, assuming constant coefficients is represented in Equation 1:  

𝑆𝑃𝑖,  =  𝛼 + 𝛽𝛸𝑖,  +  𝜑𝑌𝑡  +  𝑢𝑖,𝑡                (1) 

𝑖 ~ 1, 2, . . . , 11 and 𝑡 ~ 1, 2, . . . , 15 

𝑆P𝑖, represents stock price for bank i at time t;  

𝚾𝑖, is a vector of bank specific variables (ROA, ROE, NII, EPS DPS, AGE and SIZE), which varies across banks 
and time. 

𝐘t is a vector of time, varying banking sector specific variables. 

𝑢𝑖, are the disturbances across individual banks and time, and it is assumed to be independently identically 
distributed; and 

𝛼, and 𝜑 are constant coefficients for all banks.  
The heterogeneity that occurs among banks is denied by pooled OLS because this model does not change among 

individual banks. It is impossible to presume homogeneity in this study because organizational goals and culture 
vary between organizations. As a result, the fixed effect and random effect models were used in the study rather than 
the pooled OLS. 

This heterogeneity of the banks was captured with 𝛼𝑖. A fixed effect model is established if 𝛼𝑖 are correlated with 
the explanatory variables, otherwise random effect is established. Equation 2 specified the fixed effect model; 

𝑆𝑃𝑖,  =  𝛼𝑖  +  𝛽𝛸𝑖,  + 𝜑𝑌𝑡   + 𝑢𝑖,𝑡                                     (2) 

The variables in Equation 2 are as defined in Equation 1 above and 𝛼𝑖 measures the individual bank’s effect on 
stock price. A fixed effect model allows the individual banks to have different intercept term but the same slope 
parameters.  
In the same vein, the random effect model is specified as 

𝑆𝑃𝑖,  =  𝛽𝛸𝑖,  + 𝜑𝑌𝑡  + (𝛼𝑖  + 𝑢𝑖,𝑡)                                  (3) 
The impacts of that bank are taken into account in the random effect model via the intercept parameter I although 

each bank is chosen at random. 
The Hausman test is used to evaluate the significance of the difference between Fixed and Random estimates in 

order to choose the best panel model. Only factors that are strictly cross sectional and particular to a given bank are 
used in the test, though. Yt in Equations 1, 2, and 3 above would be disregarded as a result. The Hausman test is 
based on a test of the null hypothesis that there is no association between the random effect and explanatory variables, 
and the outcome is distributed according to a chi-square formula. The fixed effect model is regarded as having the 
best fit in cases where the null hypothesis is rejected. This study is based on partial logarithm form of Equations 1, 

2, and 3, hence restating the 𝚾 vector (i.e. 𝛽1, 𝛽2, 𝛽3, 𝛽4, 𝛽5, 𝛽6 and 𝛽7 representing the coefficients of ROA, ROE, NII, 
EPS, DPS, AGE and SIZE as follows and ignoring Yt, the modified model specifications are as follows; 

𝐿𝑜𝑔(𝑆𝑃𝑖,𝑡)  =  𝛼𝑖  +  𝛽1 ∗ 𝑅𝑂𝐴 + 𝛽2 ∗ 𝑅𝑂𝐸 + 𝛽3 ∗ 𝑁𝐼𝐼 +  𝛽4 ∗ 𝐸𝑃𝑆 +  𝛽5 ∗ 𝐷𝑃𝑆 +  𝛽6 ∗ 𝐴𝐺𝐸 + 𝛽7 ∗
𝐿𝑜𝑔(𝑆𝐼𝑍𝐸) +  𝑢𝑖,𝑡           (4) 

Equation 4 above represents the modified model specification of the variables, excluding the banking sector 
specific variable, Yt. 
Modified Fixed Effect model 

𝐿𝑜𝑔(𝑆𝑃𝑖,𝑡)  =  𝛽1 ∗ 𝑅𝑂𝐴 + 𝛽2 ∗ 𝑅𝑂𝐸 + 𝛽3 ∗ 𝑁𝐼𝐼 +  𝛽4 ∗ 𝐸𝑃𝑆 +  𝛽5 ∗ 𝐷𝑃𝑆 +  𝛽6 ∗ 𝐴𝐺𝐸 + 𝛽7 ∗ 𝐿𝑜𝑔(𝑆𝐼𝑍𝐸)  +
 (𝛼𝑖  +  𝑢𝑖,𝑡)           (5) 

The modified fixed effect model of the variables is represented by Equation 5, which would be used to decide on 
the hypotheses.   
Modified Random Effect model 

The study expects the coefficient of 𝛽1, 𝛽2, 𝛽3, 𝛽4, 𝛽5, 𝛽6 and 𝛽7 to be positive (non-negative). That is the a priori 

expectation of the constant term and 𝛽1, 𝛽2, 𝛽3, 𝛽4, 𝛽5, 𝛽6 and 𝛽7> 0. 
 

3.2. Justification of Variables 
To study gt the effect of fundamental factors on firms, variables like Return on Asset (ROA), Return on Equity 

(ROE), Net Interest Income (NII), Earnings Per Share (EPS) and Dividend Per Share (DPS) may be employed. 
Previous works (Fouzan et al., 2016; Karki, 2018; Pradhan & Laxmi, 2017; Shafiqul et al., 2016) employed the 
variables in their studies at different times to examine the impact of fundamental factors on stock prices of firms in 
various industries. The variables help in determining the performances of the firms based on what objective the 
investor wish to achieve. Employing these variables in this study will help in achieving the objectives of this study. 



Economy, 2023, 10(1): 1-9 

6 
© 2023 by the authors; licensee Asian Online Journal Publishing Group 

 

 

Table 2. Estimation procedure. 

S/N Variable Estimation Variable interaction  

1 Dependent Stock 
prices 
(SP) 

End-of-period closing 
share prices measured in 
Naira 

Share prices is determined by the forces of demand and supply. They 
are significantly affected by company’s fundamental, industry 
changes, national and global events. Therefore, share price 
movement results from investor’s perception of the available 
information specific or general about the entity or market. 

2  
 
 
 
Explanatory 

Return on 
assets 
(ROA) 

Profit after interest and 
tax divide by average total 
assets measured in 
percentage 

ROA indicates the capability of a company to utilize its assets to 
generate net profit. In an ideal market, a stock with higher ROA 
should have a higher price. Therefore, ROA should have positive 
and significant relationship with stock price. 

3 Return on 
equity 
(ROE) 

Profit after interest and 
tax divide by average total 
equity measured in 
percentage 

Return on equity (ROE) calculates how many Nairas of profit a 
company generates with each Naira of shareholders' equity. Hence, 
represents a measure of company’s efficiency. A rising ROE 
suggests that a company is increasing its ability to generate profit 
without requiring much capital. In other words, higher ROE is 
better for investment. Therefore, ROE is presumed to have positive 
relation with stock price. 

4 Net 
interest 
income 
(NII) 

Measured as the annual 
growth in percentage of 
the difference between 
interest income and 
interest expenses. 

NII is the primary source of income and cost of financial 
intermediation, which provide the measure of the ability of banks to 
earn profits. The consistency to sustain growth in NII in excess of 
operating cost and impairment on loan assets increases the ability 
of a bank to reward investors and consequently impact share price. 

5 Earnings 
per share 
(EPS) 

Profit after interest and 
tax divide by total number 
of shares measured in 
Naira 

From the perspective of an investor, higher the EPS the better it is, 
as it indicates the future prospects of the company's business, 
potential growth opportunities and higher returns for the investors. 
Hence, earnings per share has a positive relationship with market 
price, that is, higher the earning per share, higher would be the 
market price per share. 

6 Dividend 
per share 
(DPS) 

Total amount of dividend 
divides by total number of 
shares measured in Naira 

Dividends generally influence the share price in a positive direction. 
Dividend per share shows how much a company pays out in 
dividends each year relative to each of its share. In the absence of 
any capital gains, dividend is the return on investment for a stock. 
Therefore, DPS and stock price is supposed to have a positive 
relationship. 

7  
Control 

Age of the 
bank 
(AGE) 

The age of the bank from 
the date of incorporation 

Companies with longer existence and with history of consistence 
performance tend to enjoy investors’ patronage and thus may 
impact it share price. 

 
The above (Table 2) represents a tabular presentation of explanation of the variables and other factors used in the 

analysis of the study. It highlights the relevance of the variables and how they are situated in this study to help in 
achieving the study’s objectives. 
 

 
Table 3. Sample descriptive statistics of the variables. 

Variables* 
Dependent Explanatory Control 

SP DPS EPS ROA ROE NII AGE SIZE 

 Mean 11.356 0.610 1.260 1.340 11.006 28.746 47.727 1.80E+09 
 Median 7.600 0.250 0.890 1.760 12.710 15.050 31.000 1.17E+09 
 Maximum 49.500 3.600 8.300 9.930 346.680 250.390 126.000 8.68E+09 
 Minimum 0.500 0.000 -20.810 -29.3200 -252.920 -235.730 17.0000 1.07E+08 
 Std. dev. 11.474 0.792 2.866 4.090 45.065 56.293 32.591 1.80E+09 
 Skewness 1.479 1.715 -3.045 -4.380 1.301 0.754 1.1355 1.691810 
 Kurtosis 4.701 5.429 26.481 29.874 31.618 8.599 2.880 5.667539 
 Jarque-Bera 80.095 121.533 4045.609 5493.060 5677.462 231.202 35.559 127.6320 
 Probability 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 
 Sum 1873.820 100.6600 208.0406 221.2100 1816.150 4743.100 7875.000 2.98E+11 
 Sum Sq. dev. 21591.21 103.0487 1347.225 2743.834 333067.6 519713.7 174202.7 5.32E+20 
 Observations 165 165 165 165 165 165 165 165 

Note: *SP = Share price (Naira), ROA = Return on assets (%), ROE= Return on equity (%), NII = Net-interest income (%), Earnings per share (Naira), 
DPS= Dividend per share (Naira), Age= Age of the bank (years) since establishment Size = Logarithm of annual total assets. 

 
Table 3 above represents the description of the statistics employed in the study. It shows the value position of 

each of the variables in relation to the mean, median, standard deviation, Jargue-Bera and the probability of the 
variables. 
 

4. Data Analysis and Results 
4.1. Correlation Matrix 

Table 4 below shows the correlation matrix, showing the relationship between the dependent variable and 
explanatory variables, on the other hand, the matrix indicates the direction of the relationship which assist 
establishing the extent of multicollinearity among all the variables considered. The table indicates that there is a 
positive relationship between the dependent variable and all the other variables, except one of the control variable, 
Age.  

This revelation suggests a likelihood that all explanatory variables affect the share price of sampled listed banks 
in Nigeria. In a similar vein, the degree of relationship between these variables are not too high which is an indication 
of absence of multicollinearity among all the explanatory variables considered in this study. In relation to the 
dependent variable, the result showed a strong positive correlation between SP and DPS compared to the other 
variables. 

 
 



Economy, 2023, 10(1): 1-9 

7 
© 2023 by the authors; licensee Asian Online Journal Publishing Group 

 

 

Table 4. Correlation matrix for the sample observations, which are the variables. 

Variables SP DPS EPS ROA ROE NII AGE SIZE 

SP 1.000000        
a -----        
b -----        

DPS 0.7500 1.000000       

a 14.477 -----       

b 0.0000* -----       

EPS 0.460 0.642 1.000000      

a 6.620 10.711 -----      

b 0.0000* 0.0000* -----      

ROA 0.267 0.357 0.730 1.000000     

a 3.551 4.893 13.652 -----     

b 0.0005* 0.0000* 0.0000* -----     

ROE 0.192 0.178 -0.105 -0.320 1.000000    

a 2.507 2.321 -1.350 -4.322 -----    

b 0.0131** 0.0215** 0.1788 0.0000* -----    

NII 0.0750 -0.038 -0.049 0.239 0.030 1.000000   

a 0.961 -0.497 -0.638 3.147 0.387 -----   

b 0.337 0.619 0.524 0.0020* 0.6990 -----   

AGE -0.073 -0.190 -0.180 -0.195 -0.049 -0.221 1.000000  

a -0.947 -2.473 -2.338 -2.546 -0.633 -2.897 -----  

b 0.3449 0.0144** 0.0206** 0.0118** 0.5271 0.0043* -----  

SIZE 0.176 0.488 0.408 0.168 0.095 -0.204 0.220 1.000000 

a 2.288 7.148 5.713 2.180 1.224 -2.664 2.886 ----- 

b 0.023** 0.0000* 0.0000* 0.0307** 0.2226 0.0085* 0.0044* ----- 

Note: ** Correlation is significant at the 5% level. *Correlation is significant at the 1% level, a:t-statistics and b-p-value. 
 

4.2. Estimated Regression Result 
The results of the estimated models (pooled, fixed and random effect) and Hausman Test are presented in Table 

5 and 6 respectively. 
The amounts in brackets represent the standard errors of the estimations and the corresponding probabilities. 

The fixed effect model has a superior fit, according to a summary of the models' statistics in terms of R-squared, 
standard error of the regression, and Durbin-Watson Statistic, whereas the value of cross-section random error is 
very minor in comparison to the idiosyncratic random. 

The Hausman test result showed a chi-square statistic value of 320.63 and a p-value of 0.000 with 7 degrees of 
freedom, suggesting that the null hypothesis that there is no connection between the explanatory factors and the 
random effect has been rejected at a 1% significant level. This suggests that fixed effect is a better model for predicting 
share price in Nigeria throughout the data period. 

 
Table 5. Determination of appropriate model: Dependent variable: LOG(SP) and other independent variables 

Variable Pooled model Fixed effect model Random effect model 

DPS 1.0379  
(0.1329)  
(0000)* 

0.5637 
(0.0968)  
(0000)* 

1.0251  
(0.0767)  
(0000)* 

EPS -0.0351 
(0.0463)  
(0.4498) 

0.088 
(0.0285)  
(0.0024)* 

-0.0308 
(0.0265)  
(0.2472) 

ROA 0.0241 
(0.0301)  
(0.4247) 

-0.0552 
(0.0186)  
(0.0036)* 

0.0206  
(0.0172)  
(0.234) 

ROE 0.0034 
(0.0017)  

(0.0524)*** 

0.0009 
(0.00103)  
(0.3427) 

0.0033 
(0.001002)  
(0.0012)* 

NII 0.00462  
(0.001)  

(0.0015)* 

0.001705  
(0.0008)  

(0.0523)*** 

0.004563  
(0.0008)  
(0000)* 

AGE 0.0055 
(0.0024)  

(0.0224)** 

-0.0989  
(0.0198)  
(0000)* 

0.0054 
(0.0014)  

(0.0002)* 
LOG(SIZE) 0.0942  

(0.0871)  
(0.281) 

0.1141  
(0.1204)  
(0.3451) 

0.0807 
(0.0504)  
(0.1117) 

C -1.19408 
(1.7425)  
(0.4942) 

3.7310 
(1.7832)  

(0.0381)** 

-0.8963 
(1.01006)  
(0.3762) 

R-squared 0.5220 0.8548 0.5080 

Adjusted R-squared 0.5007 0.8380 0.4861 

F-statistic 24.5008 50.921 23.1638 

Prob(F-statistic) 0.000000 0.000000 
 

0.000000 

Durbin-Watson stat 0.7161 1.7637 0.7222 

Cross-section random 
  

0.0373 
(0.0055) 

Idiosyncratic random 
  

0.5009 
(0.994) 

 Note: * Significance at 1%, ** significant at 5% and *** significant at 10% level. 

 
 



Economy, 2023, 10(1): 1-9 

8 
© 2023 by the authors; licensee Asian Online Journal Publishing Group 

 

 

The study proposed that the explanatory variables would positively affect share price. According to Table 5, the 
value of the R-squared coefficient of determination is 85.48%, and the corrected R-squared value is 83.80%. This 
coefficient expresses how much of the entire fluctuation in bank share prices can be accounted for by the explanatory 
factors used. This coefficient showed that the model explained 83.8% of the variation in the overall price of banks' 
shares.  

By extension, the independent variable used in this study cannot account for 16.2% of the overall fluctuation in 
the share price of banks. The F-statistics is significant at 1% and has a value of 50.92 with a p-value of 0.000. This 
finding shows that the econometric model used in the study is suitable for explaining the relationship between the 
share price of banks and the five key factors taken into account (DPS, EPS, ROA, ROE and NII). Therefore, the 
following is the estimated fixed effect panel regression model:  
Log(SP) = 3.73 - 0.055*(ROA) + 0.001*(ROE) + 0.002*NII + 0.088*(EPS) + 0.564*(DPS) – 0.099*AGE + 
0.114*Log(SIZE) 
 

Table 6. Correlated random effects - Hausman test of chi-sq 
Test summary Chi-sq. statistic Chi-sq. d.f. Prob. 

Cross-section random 320.636 7 0.0000 

 

4.3. Test of Hypotheses 
Ho1: Return on assets (ROA) do not significantly affect the stock prices of listed banks in Nigeria. 

Coefficient (ROA) Std. error T-statistics P-value 

-0.055 0.0186 -2.9595 (0.0036) 

 
Decision: The study accept Ho1 and conclude that ROA do not significantly affect stock prices of banks since the 

coefficient return is negative coefficient rather than the expected positive value. However, the negative coefficient 
was significant at 1% 

Ho2:Return on equity (ROE) do not significantly affect the stock prices of listed banks in Nigeria. 

Coefficient (ROE) Std. error T-statistics P-value 

0.000987 0.0010 0.9519 0.3427 

 
Decision: The study accept Ho2 and conclude that ROE do not significantly affect the stock prices of listed banks 

in Nigeria. The coefficient showed positive impact of ROE as expected but is not statistically significant. 
Ho3:Growth in Net Interest Income (NII) do not significantly affect the stock prices of listed banks in Nigeria. 

Coefficient (NII) Std. error T-statistics P-value 

0.001705 0.0008 1.9568 0.0523 

 
Decision: The study reject Ho3 and conclude that growth in Net Interest Income (NII) significantly affect the 

stock prices of listed banks in Nigeria. The coefficient is positive as expected and significant at 10%. 
Ho4: Earnings per share (EPS) do not significantly affect the stock prices of listed banks in Nigeria. 

Coefficient (EPS) Std. error T-statistics P-value 

0.08814 0.0285 3.0860 0.0024 

 
Decision: The study reject Ho4 and conclude that EPS significantly affect the stock prices of listed banks in 

Nigeria. The coefficient is positive as expected and significant at 1%. 
Ho5: Dividends per share (DPS) do not significantly affect the stock prices of listed banks in Nigeria. 

Coefficient (EPS) Std. error T-statistics P-value 

0.5637 0.0968 2.0922 0.0000 

 
Decision: The study reject Ho5 and conclude that DPS significantly affect the stock prices of listed banks in 

Nigeria. The coefficient is positive as expected and significant at 1%. 
The above findings provide evidences for the rejection of three null hypotheses (Ho3, Ho4 and Ho5), implying that 

that, NII, EPS and DPS positively impact share price of banks. Thus, when banks want to boost their market value, 
they must strive to continuously leverage acquired assets to generate quality earnings, maintain optimum expense 
level to remain profitable as well as declare dividends. 

 
5. Discussion of Findings 

Regarding the explanatory variables, the model showed that the coefficient of DPS, EPS, NII and ROE contribute 
positively to share price of the sampled banks while ROA impact share price negatively. Precisely, the coefficients of 
the model suggest that increase in the proportion units of DPS, EPS, NII and ROE may result in 0.564, 0.088, 0.002 
and 0.001 percentage point increase in share price. On the other hand, proportionate unit increase in ROA could lead 
to 0.055 percentage point decrease in share price respectively. While the coefficient of NII was statistically significant 
at 10%, the coefficients of DPS, EPS and ROA are significant at 1% level. The coefficient of ROE was not statistically 
significant and hence suggest that the study accept the second hypothesis (H02) and conclude that ROE does not 
significantly affect the stock prices of listed banks in Nigeria. This finding is consistent with Fouzan et al. (2016), 
whose work found that there is no effect between ROE and stock market price of 20 insurance companies listed in 
Amman stock exchange during the period 2011 to 2015.  

The possible conjecture of non-significance of the ROE could relate to the fact that the equity positions of a few 
banks, as a result of post consolidation expansion drives, expanded dramatically from merger of medium sized banks, 
emerging in to larger banks, which has not translated in earnings capacity that could drive share prices of those 
banks to the height attained by leading banks on the Nigerian stock market. The study found that it is not the leading 
banks in terms of assets, equity and/or earnings that are price leaders. The negative ROA also differ from the a priori 



Economy, 2023, 10(1): 1-9 

9 
© 2023 by the authors; licensee Asian Online Journal Publishing Group 

 

 

expectation. This is likely as a result of the fact that the study covered both the period of capital market boom, when 
stock prices reached unprecedented high points, and the period of crash, precisely during the 2008 global financial 
crisis, when the market witnessed significant decline in stock prices. The later event eroded investors’ confidence and 
the stock market have not been able to surpass the height reached over a decade ago. The study found that as at close 
of 2020, only two out of the sampled eleven banks were able to reach or surpass the price levels they attained in 2007. 
Coincidentally, the two banks were that best in terms of average ROA and ROE for the 15-year study period.    

In relation to the control variables (age and size), the coefficient on age is negative but statistically significant at 
1% but was found to have insignificant inverse relationship with share price. The coefficient of size is positive but 
not significant. This result indicate that the share price of a Nigerian bank with a larger size of assets is likely to be 
lower keeping every other variable constant. The study found that the share price of one of the leading banks in 2020 
(in terms of assets) was less than 9 naira per share and the bank had assets 3 times a medium sized bank trading 
above 44 naira per share. 
 

6. Conclusions and Recommendations 
In conclusion, the study has provided both empirical as well as statistical evidence on the utility of the 

explanatory variables (ROA, ROE, NII, EPS and DPS) and control variables (firm size and age) in explaining and 
predicting the share price of banks. On the bases of the findings of the research, the study concludes that there is a 
positive relationship between share price and some firm fundamental factors. Also, dividend per share, earnings per 
share, growth in net interest income engender share price positively. While bank age negatively affects share price. 
With this, the study recommends that dividend is relevant fundamental factor in determining share price of bank 
quoted on the Nigerian Stock Exchange. Based on this revelation, boards of directors of firms should strive to 
maintain adequate dividend payments.  Some of the numerous ways of maintaining adequate dividend payment is by: 
(a) reducing the proportion of yearly retain earnings, (b) optimization of operational cost, (c) aggressive loan recovery 
to minimize loan assets impairments, and (d) credit risk management and strategic loan and advances to the real 
sector. Also, the extent that dividend per share enhance share prices, it is recommended that existing shareholders 
pay more attention on high dividend paying companies for capital gain. Finally, Due to the enhancing role of dividend 
on share price, managers may want to window dress their earnings figure through dividend smoothing. Therefore, 
regulators should pay extra attention on earnings management techniques employed by managers in the attempt to 
smooth dividend payments. 
 

References  
Fouzan, A. Q., Tahtamouni, A., & Al-Qudah, M. (2016). Factors affecting the market stock price-the case of the insurance companies listed in 

Amman Stock exchange. International Journal of Business and Social Science, 7(10), 81-90.  
Karki, D. (2018). Fundamentals of common stock pricing: Evidence from commercial banks of Nepal. SAARJ Journal on Banking & Insurance 

Research, 7(1), 4-32. https://doi.org/10.5958/2319-1422.2018.00001.2 
Pradhan, R. S., & Laxmi, P. (2017). Impact of fundamental factors on stock price: A case of Nepalese Commercial Banks. Nepalese Journal of 

Engineering, 4(2), 1-13.  
Shafiqul, A., Rubel, M., & Abdul, K. (2016). Analysis of factors that affect stock prices: A study of listed cement companies at Dhaka Stock 

exchange. Research Journal of Finance and Accounting, 7(18), 93 -113.  
Tease, W. (1993). The stock market and investment. OECD Economic Studies, 20(Spring), 41-63.  
Ugwudioha, M. O. (2019). Financial management; Theory and practice. Ile-Ife, Nigeria: Obafemi Awolowo University Press. 
Wallace, N., & Thomas, J. S. (1975). Rational expectations, the optimal monetary instrument, and the optimal money Supply Rule. Journal of 

Political Economy, the University of Chicago Press, 83(2), 241-254.  
Zutter, C. J., & Gitman, L. J. (2012). Principles of managerial finance 13th Edited by Donna Battista. Boston: Pearson Prentice Hall. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Asian Online Journal Publishing Group is not responsible or answerable for any loss, damage or liability, etc. caused in relation to/arising out of the use of the content. 
Any queries should be directed to the corresponding author of the article. 

 

https://doi.org/10.5958/2319-1422.2018.00001.2

