FACTORS AFFECTING STOCK PRICE: EVIDENCE FROM COMMERCIAL BANKS IN THE DEVELOPING MARKET

How to cite this paper: Al-Dwiry, M., Al-Eitan, G. N., & Amira, W. (2022) . Factors affecting stock price: Evidence from commercial banks in the developing market [Special issue] . Journal of Governance & Regulation, 11 (4), 339–346. https://doi.org/10.22495/jgrv11i4siart14


INTRODUCTION
The financial markets play a significant role in the economy, as they denote the point of interaction between investors and companies by mobilizing savings and converting them into investments that affect economic development. One of the major methods for investors to accomplish a decent return on their money is to invest in equity shares, which are considered to be the most prevalent and actively traded securities (Arkan, 2016). In addition, because of the increasing level of development in the financial markets, it has been a basic concept that has crystallized in the world. The investment decisions for investors rely on both stock prices and the changes in these prices. Theories and literature mention that there is a connection between changes in share prices and changes in financial fundamental variables (Nisa & Nishat, 2011). Mosley and Singer (2008) established that equities constitute an important factor in the capital markets which may help to enhance the efficiency of corporate spur innovation, and provide a valuable foundation for long-run economic development.
Stock market prices are affected by several factors at the microeconomic level including earnings dividend, book value, return on assets, etc., or external factors based on the macroeconomic level, such as real gross domestic product (GDP), inflation level, interest rate, etc. Recent studies have been conducted on the factors that affect the share price. Fama (1981) suggested that firm size, book-to-market equity (BE/ME) value, cash flow yield, and leverage are considered to be the fundamental variables that determine the stock return. Moreover, Collins (1957) identified that dividends, operating earnings, net profit, and book value are the factors that determine the share prices of US banks, while a company's stock price is determined only by its earnings and value, not by dividend policy from the point of view of Modigliani and Miller (1958). Recently, Almumani (2014) has found that the market price is highly connected with earnings per share, price-earnings percentage, and book value per share, while the firm size is negatively related to the market price. Similarly, Malhotra and Tandon (2013) found that dividend yield is negatively related to the market price.
Previous studies such as Almumani (2014), Malhotra Thuy (2018) investigated the impact of internal and external factors on the market price per share. Therefore, this study adopts the most previous variables in determining the stock prices in Jordanian commercial banks. In view of these factors, there is no study that takes into account the impact of both internal and external factors on stock prices in the Jordanian commercial banking sector. This study may contribute to bridging the gap through a study of the impact of microeconomic (earnings per share (EPS), dividend per share (DPS), price-earnings ratio (PE), book value per share (BV), return on assets (ROA), and size (S) and macroeconomic (GDP, inflation (INF), and MS) factors on the share price of Jordanian commercial banks.
The main objective of the study is to determine both internal and external elements that affect stock market prices and analyse the relationship between these factors for Jordanian commercial banks. Also, it aims to examine the relationship between the market price per share (MPS) as a dependent variable, and the independent variables which are EPS, DPS, PE, BV, ROA, and S. Similarly, GDP, INF, and MS were chosen as independent variables for the macroeconomic level. The contribution of the study is to fill the gap in the theoretical and empirical research concerning the factors that affect stock prices, whether these factors are internal or external.
The structure of the paper is as follows: the literature review is presented in Section 2, and the research methodology is presented in Section 3. Section 4 covers the empirical findings and Section 5 covers the conclusion and outlines the scope of future research and its consequences.

LITERATURE REVIEW
Several studies have been conducted on the factors affecting the share price in commercial banks. Arshad et al. (2015) found that the earnings per share have more effect on share prices and they have a significant positive link with share prices. BE/ME value ratio and interest rate are negatively related to share prices while other factors (GDP, price-earnings percentage, dividend per share, leverage) have no link with price per share. It is contrary to a recent study by Gharaibeh and Jaradat (2021) who showed that earnings per share have a minimum impact on stock prices, whereas ROA has a positive significant impact and delivers the largest effect among all the variables of the research, while the risk factor measured by volatility of ROA has a significant positive impact. In other words, firm size, BE/ME, and dividend yield ratio have a significant inverse impact on the stock prices market. Pradhan and Dahal (2016) investigated the link between bank-specific and macroeconomic factors and MPS for Nepal in the banking sector. The results show that the key drivers of stock price are firmspecific factors such as earnings per share, priceearnings ratio, dividends per share, book value per share, return on assets, and size. Moreover, firm size is the most important variable among the variables that affect the stock price. In a similar study for the same market, Bajracharya and Sawagvudcharee (2019) indicated that the EPS, DPS, and PE had a positive, significant connection with the MPS among the internal variables. However, there was no discernible connection between the internal component ROA and the MPS. Similar to this, the results showed that INF was adversely associated with the MPS of Nepalese commercial banks among the external variables.

Wagle
(2021) attempted to determine the empirical factors that affect the stock market price in Nepal's commercial banks. The findings showed that the stock market price is significantly positively correlated with the market-to-book ratio, price-earnings ratio, and earning yield ratio. The dividend yield ratio, in contrast, has a slight but favorable influence on the price of stocks. Saldanli et al. (2017) studied the macro variables and they concluded that there is no causality link between the real GDP and the share prices of Turkish banking sector, while there is a causality link between the exchange rate and the money supply of some banks on the stock price.
However, Bhattarai (2018) studied the impact of macroeconomic and firm-specific factors on the stock prices of Nepalese banks and insurance enterprises. The study's findings revealed a strong positive association between market price and profits per share, dividends per share, price-toearnings ratio, firm size, GDP, and exchange rate. While money supply, return on assets, and return on equity (ROE) all significantly inversely correlate with the market price. The final results demonstrate that, with the exception of DPS, all individual factors have a considerable impact on the share prices of banks and insurance firms in Nepal. Although, Megaravalli and Sampagnaro (2018) reached a strong negative link between inflation and stock returns. Al Qaisi et al. (2016) found that there is an effect between ROA, debt ratio, company's age, company's size and market stock price in insurance companies listed on Amman Stock Exchange (ASE) but no effect between ROE and market stock price.
In the same manner, Wulandari, Bukit, and Absah (2019) investigated non-performing loans, return on assets, and net interest margin, which are the elements of traditional commercial banks listed in Indonesia, and determined to have a direct beneficial impact on stock prices through capital adequacy level. While the operating expenses on operating income, the loan-to-deposit ratio, and good corporate governance significantly lower stock prices.
On the contrary, Susanto et al. (2021) found that the share price has a significant effect on net income and comprehensive income but does not have a significant effect on profit volatility, proving that net and comprehensive income has relevance to the share price. The results were used to estimate and predict the impact of stock prices on profit volatility, net profit, and comprehensive income on the Indonesia Stock Exchange (IDX).
Hossain and Ismail (2020) demonstrated that the market price of a share is highly influenced by factors such as profits per share, dividends per share, bank size, and the ratio of non-performing loans to total loans. However, the market price of shares of commercial banks listed in Bangladesh is not significantly impacted by asset growth, return on equity, or capital to risk-weighted assets ratio. In the same market, Al Masum (2014) examined the connection between the dividend policy and the stock price of commercial banks registered on the Bangladesh Stock Exchange. In contrast to the retention ratio, which has a negative but statistically insignificant link with stock market prices, this study found a substantial negative relationship between dividend yield and stock price. The study also discovered that profit after tax has a statistically significant negative influence on stock market prices of the commercial banks of Bangladesh, whereas dividend policy, return on equity, and earnings per share had statistically significant positive impacts on the stock price. Kengatharan (2018) studied the effects of firmspecific and macroeconomic factors on the stock price of listed domestic commercial banks in Sri Lanka. The study's findings demonstrated that all bank-specific metrics, including EPS, DPS, and bank size, have a sizable positive impact on the share price. In this study, external factors like interest rate, inflation rate, and currency rate that were taken into account did not show any impact on bank share prices.
Thuy (2018) showed that the market price of non-financial joint stock businesses listed on the Vietnam Stock Exchange is significantly influenced by both internal and external factors, including financial performance, dividend policy, company size, and the percentage of foreign ownership. In a similar vein, a study conducted by Al-Shubiri (2010) found that there is a significant positive relationship between market stock price and net asset value per share as well as a sometimes significant negative relationship between inflation and lending interest rate in Amman Stock Exchange, Jordan.
According to Eldomiaty et al. (2019), the relationship between stock prices and inflation rates is negative, while the relationship between stock prices and interest rates is positive. Bai (2014) asserted that the correlation between the rate of inflation and the returns of shares is positive. Contrariwise, Shula (2017) proved that there is a negative relationship between the interest rate and the stock prices since this relationship has important statistical significance and no statistically significant relationship has been established between the inflation rate and the stock prices.
Al-Malkawi, AlShiab, and Pillai (2018) investigated a few firm-specific variables that affect MPS in the Middle East and North Africa (MENA) area, and they found that although dividend yield and gearing have a negative effect on MPS, return on equity, book value per share, dividend per share, profits per share, and price-earnings ratio had a favourable impact. Finally, while the global financial crisis appears to have no bearing on MPS, the control variable business size suggests a positive and statistically significant link with MPS. According to the findings of Sharif, Purohit, and Pillai (2015), there is a strong and positive correlation between ROE, BV, DPS, PE, S, and MPS. Dividend yield and MPS did, however, show a strong negative association. Leverage also revealed an opposing, if little, association with the market price.
Additionally, Gunarathne, Priyadarshanie, and Samarakoon (2016) used Sri Lanka as a case study to investigate the impact of the firm's dividend policy on the volatility market value of stocks. According to the findings, the dividend payout ratio for both current and prior years has a positive influence on share price volatility whereas the dividend return for the current year has a negative impact. Additionally, the dividend yield has a detrimental effect on the company's market value. Tchereni

RESEARCH METHODOLOGY
The main objective of this study is to investigate the link between MPS of Jordanian commercial banks listed on the Amman Stock Exchange and bank-specific and macroeconomic factors. In particular, it looks at how market price per share is affected by profits per share, dividend per share, price-earnings ratio, book value per share, return on assets, size, GDP, inflation, and money supply. Beginning with the definition of the study population and sample, the study variables, and the measurement techniques, this section presents the approach used in assessing statistical correlations between the variables. The part also discusses the data gathering sources and analysis techniques.
The research's sample is made up of commercial banks from the same list of banks that make up the study population -all banks listed on the ASE. Due to their unique restrictions that differ from those of the regular commercial local banks, all international and Islamic banks are excluded from the sample selection process for the period 2010-2021 in Table 1. 13 banks that are listed in businesses were included in this study because they have the similar business environment and character. The rationale for picking this time period is because of the significant local and worldwide events and developments that affected the economy broadly and the movement and fluctuation of the ASE index in particular. The study examines the relationship between macroeconomic variables and the MPS of commercial banks in Jordan by applying a multiple linear regression model, which is as follows: (1) In the above equations, denotes the market price per share, denotes earnings per share, denotes dividend per share, denotes the price-earnings ratio, denotes book value per share, denotes return on assets and denotes the size of the commercial bank in Jordan, and is used as a control variable. The macroeconomic variables are represented in the second equation: denotes gross domestic products, denotes inflation, denotes money supply, finally, represents error terms. The study has used two statistical analyses and they are: descriptive statistics (means, standard deviations, minimum and maximum) and regression diagnostics (Hausmann test, multicollinearity test) for the variables during the period of the study.
As the first approximation, the model estimated in this study assumes that the market price per share on firm-specific and macroeconomic variables may be seen as under: where, the market price per share is used as a dependent variable and measured in terms of MPS. The independent variables consist of firm-specific and macroeconomic variables as presented below: Explanatory variables used in the study along with their expected sign in the empirical estimate as specified in equations (1), (2) and (3) are summarized in Table 2. The dependent variable is the market price per share (MPS).

RESULTS AND DISCUSSION
Results from the descriptive statistics are presented in Table 3. They show that the mean value of MPS is 3.49 over the study period. This variable has a minimum value of 0.79 and a maximum one of 63.30 during the study period. However, in terms of standard deviation, it is 5.30 during the study period. The mean for EPS, DPS, ROA and S are 1.97, 0.04, 0.01 and 9.19 respectively, whereas the mean for macroeconomic factors are 0.060, 3.942 and 0.028 respectively. According to the descriptive analysis, the standard deviation for GDP, INF, and MS is 0.020, 3.891 and 0.021 respectively during the period of the study in Jordan. When it comes to the maximum values for microeconomic variables including EPS, DPS, BV, ROA and S, they are 6.86, 0.14, 187.1, 77.01, 0.08 and 10.41 respectively over the period 2010-2021. The bivariate Pearson's correlation coefficients between share market value and variables affecting share market price are shown in Table 4  The determination factor ( ) was used for all independent variables except for the dependent variable in the variance inflation factor (VIF) test through the following formula: If > 5 then this indicates the existence of a multiple correlation problem between the independent variables. Table 5 shows the values of the VIF test for all the study variables, as it is clear that there is no problem in the multiple linear correlation between the study variables in the study standard models.  Table 6 shows the impact of the specific variables of Jordanian commercial banks, the macroeconomic variables and the internal and external variables together on the share price of Jordanian commercial banks. Results are based on 11-year panel data (2010-2021). Hausman test was used to compare the fixed effects model (FEM) and the random effects model (REM), where a REM is used if the probability of the test value is greater than 5%, a FEM is used if the probability of the test value is less than 5%.
The results in Table 6 showed that the random effect model is the most appropriate for estimating the MPS Model 2 because the probability is greater than 5%. The fixed effect model is also more appropriate to estimate the MPS Model 1 and MPS Model 3 because the probability is greater than 5. The adjusted R-squared is effectively the ratio of the total variance that the model represents, which adds to this finding. The coefficient of determination of the variable for three models (0.496, 0.597 and 0.473) are typically referred to as adjusted R-squared. The models can explain around 51%, 41% and 53% of the variance in bank stock prices, according to R-squared, which is also a measure of the model's overall fit. This accounts for around 51%, 41% and 53% of the variation models. Other parameters not included in the model are used to determine the price of sample banks on the market.
Similarly, the F-statistics, which is evidence of the estimated model's correctness, as shown in Table 6, indicate that F-tests of models are around 13.324, 18.514 and 12.662 and a p-value equal to 0.000 respectively, which always clearly indicates that the explanatory variables are highly correlated with the dependent variable at the same time. That is, they have a significant impact on the behavior of stock market values. Furthermore, the Durbin-Watson results of models have values of 1.89, 1.75 and 2.03 respectively, indicating that the error term is autocorrelation-free and independent.
The regression of the company's own variables on the market price of the stock has been investigated in terms of MPS. Table 6 shows the results of company-specific factors that impact MPS in both Models 1 and 3. The coefficient of EPS is positive in the table, implying that the greater the EPS, the higher the MPS. The coefficient of EPS, on the other hand, is significant at the 1% level of significance. The coefficient of DPS is positive, implying that the greater the DPS, the higher the MPS. The beta coefficient of DPS, on the other hand, is significant at the 1% level of significance.
Another empirical conclusion from the regression study is that ROA and S ratios have a beneficial influence on MPS. For both Models 1 and 2, the coefficients of ROA ratio are 0.873 and 0.940, respectively, implying that for every unit increase in ROA, the MPS rises by 0.873 and 0.940 in both Models 1 and 2, respectively.
The impact of macroeconomic factors on the stock market price was investigated using MPS. The findings of macroeconomic factors impacting MPS are reported in Table 6. According to the table, the coefficient of GDP and monetary aggregate M2 have a positive impact on MPS, implying that the larger the GDP, the higher the MPS. According to the empirical findings, there is no problem in the multiple linear correlation between the study variables in the study standard models. Whereas the panel data of the MPS models regression illustrate that the random effect model is most appropriate in estimating the MPS Model 2 while the fixed effect model is more appropriate to estimate the MPS Model 1 and MPS Model 3. Furthermore, the adjusted R-squared explains around 51%, 41% and 53% of the variance in bank stock price and the F-tests of models are around 13.324, 18.514 and 12.662 and a p-value equal to 0.000 respectively, which indicates that the explanatory variables are highly correlated to the market price per share.

CONCLUSION
Based on the regression results, the coefficient of EPS is positive at the 1% level of significance, implying that the greater the EPS, the higher the MPS. This result is consistent with Almumani In other words, company-specific factors such as EPS, DPS, ROA, and S are major predictors of stock prices in the context of banking in Jordan. Volume was discovered to be the most important determining variable impacting stock price among the factors. The study concludes that the major variables that affect the stock price on the macroeconomic level are GDP, and MS, and that was in the same study by Saldanli et al. (2017) Bhattarai (2018. Furthermore, the variables such as the price-earnings ratio, book value per share, and inflation have a minor impact on the market price per share. This result is consistent with Arshad et al. (2015).
The implications of this study show that before making an investment decision, a rational investor should evaluate earnings per share, dividend per share, firm size, and money supply, as well as signaling and asymmetric information in the setting of the Amman Stock Exchange.
Additionally, this research has some limitations. Firstly, only 13 listed banks have been applied in the study, therefore, the sample is small. Secondly, some data that have been used in this study were obtained from the data stream, hence not all data were available for the analysis. However, future studies could concentrate on additional hazards including interest rate, market, and foreign exchange risk. Future research can also take into account risks in other nations including Qatar, Egypt, Tunisia, and Morocco to produce more reliable findings on the relationship between risks and bank performance in developing nations.