**3. Data and variables**

Gjerde and Saettem [12] studied the relationship between stock returns and macroeconomic variables like inflation, real economic activity and oil prices in Norway. The empirical study revealed that inflation is not a significant variable for changes in stock prices. However, there

Irfan et al. [13] attempted to explain the impact of six company variables dividend yield, dividend payout ratio, leverage, size of the firm, earnings volatility and asset growth rate on stock prices of Pakistani companies during the period 1981–2000. A regression model was

> dividend payout ratio (insignificant), dividend yield (−), earnings per share (+), price earnings ratio (+), logarithm of

> closing price of the stock at time t-1 (+), book-to-market equity (+), leverage ratio (−), firm size (+), dividend paid (−),

earnings per share (insignificant), net cash from operating activities per share (+), book value per share (+), long-term debt to total assets (+), dividends per

Earnings per share (+), dividends per share (+), book value per share (+)

Beta (+), market capitalization (+), current ratio (insignificant), earnings per share (+), D/E ratio (insignificant), return on capital employed

earnings ratio (+), EPS (+), size-sales (insignificant), book value per share

Inflation rate (−), economic activity

Oil prices (−), real economic activity and

Equity (−), dividend yield (insignificant), return on assets (insignificant), asset growth

total assets (insignificant)

**Place**

Banking sector of Nepal

Istanbul Stock Exchange

Mobile companies from Europe, Asia, the Middle East

Abu Dhabi Securities Market

Banking sector of Pakistan

Indian Stock Market

Indian Manufacturing

Brazil stock market

Greece stock market

New York Stock Exchange

Companies

and America

was a positive relationship between oil price and stock price.

**Study Methodology Results of the study (+/− significant or** 

Bhattarai [15] Multiple Regression Model

24 Firm Value - Theory and Empirical Evidence

Dynamic Panel Data

Panel least squares regression model

Multiple Regression

Fixed effect regression

Fixed effect regression

co-integration model

auto regression (VAR)

Srinivasan [20] Random effects model Dividend per share (−), price

Analysis

Model

model

model

Adrangi et al. [21] Johansen and Juselius

Papapetrou [22] Multivariate vector-

**Table 1.** Summary of other identified studies.

approach

Şebnem and Vuran

Gregoriou et al.

Ibrahim Obeidat

Mohammad Khan Ghauri [18]

Raithatha and Bapat [19]

Fama and Schwert

[23]

[16]

[17]

[6]

**insignificant)**

oil price (−)

share (+)

(insignificant)

(insignificant)

(insignificant)

(GDP) (+)

employment

Regression Model Expected inflation (−) and unexpected inflation (−)

By available literature and data, the author has identified dividend payout ratio, debt ratio, earnings per share (EPS), logarithm of total assets (a proxy for company size) and price earnings ratio as the regressors of the stock price in this study. This study is based on 26 nonfinancial companies listed in Muscat securities market during 2011–2016. The sample companies selected for the study are based on the availability and fullness of the data. The selected companies are Al Saffa Foods, Salalah Mills, Oman Cement, Raysut Cement, Galfar Engineering and contracting, Anwar Ceramic Tiles, Jazeera Steel Products, National Aluminum Products, Gulf International Chemicals, Oman Chlorine, Oman Cables Industry, Voltamp Energy, Omantel telecommunications, Port Services Corporation, Almaha petroleum products, National Gas, Oman oil marketing, Shell Oman Marketing, ACWA Power Barka, SMN Power Holding, Sohar Power, United Power, Al Jazeira Services, Oman Investment and Finance, Renaissance Services and Ooredoo.

Roll and Ross [2] in his arbitrage pricing theory (APT) has proved the relevance of macroeconomic variables in stock pricing. Based on the literature, economic variables like growth rate in GDP, consumer price index and crude oil prices have also been considered as the external variables affecting stock prices. Fama and Schwert [23] the well-known study was also based on the relationship between stock prices and inflation. Oman being the net exporter and mainly depending on oil and gas export is facing the heat of low oil prices. Economy of Oman like other GCC countries is driven by oil and gas, so consideration of oil price as an independent variable makes sense.

H07: There is no significant effect of crude oil price on share price.

H09: There is no significant effect of growth in GDP on share price.

+ β1 CPjt−1 + β2 Dividendjt

+ β<sup>7</sup> Sizejt

+ β<sup>7</sup> Sizejt

where, CPjt = annual closing price of firm's stock in year t; β0 = common y-intercept; β1

the coefficients of concerned explanatory variables; ɛjt = stochastic error term for firm j at time

Based on the literature on share price determinants, the following company-specific variables dividend payout ratio, leverage, earning per share, size of the company, price earnings ratio and three economy based variables growth rate in GDP, inflation rate and crude oil prices were selected as the predictor variables in the regression analysis. Apart from these variables, first lag of yearly closing price of shares was also considered as a predictor

This section presents the results of panel data analysis which are reported in **Table 2**. Both the fixed effect and random effect model was used to measure the impact of the selected independent variables on the stock prices of sample companies. Then the Hausman specification test was used to select a better model between fixed effects and random effects model. The null hypothesis in Hausman test is that the preferred model is random effects and the alternate

+ β6 Inflationjt

CPjt = β0 + β1 CPjt−1 + β2 Dividendjt

+ β6 Inflationjt

t; β0j = firm j's y-intercept; μjt = error term for firm j at time t.

hypothesis is that the preferred model is fixed effects.

Panel data analysis has been used to analyze the impact of firm-specific and macroeconomic determinants on the share price of the nonfinancial listed companies in Oman. Panel data always has advantages over time-series and cross-sectional data. Panel data analysis weakens the interaction between the variables that result in more reliable parameters, Hsiao [24]. Employment of this technique is considered more efficient as it reduces the co-linearity of the predictor variables and also it offers gain regarding the degree of freedom. The research study uses both the panel data methods, that is, fixed effect method and the random effect method. The better method is then selected applying the Hausman test. Both the models fixed effects and the random effects have been represented by the following Eqs. (1) and (2),

+ β<sup>3</sup> EPSjt

+ β<sup>3</sup> EPSjt

+ β<sup>8</sup> Oiljt

+ β<sup>8</sup> Oiljt

+ β<sup>4</sup> Leveragejt

+ β<sup>4</sup> Leveragejt

+ β9 PEjt

Stock Price Determinants: Empirical Evidence from Muscat Securities Market, Oman

+ β9 PEjt

+ β5 GDPjt

http://dx.doi.org/10.5772/intechopen.77343

27

+ β5 GDPjt

+ μjt (1)

+ μjt (2)

–β9 are

H08: There is no significant effect of inflation on share price.

**3.2. Panel data analysis**

respectively:

variable.

**4. Data analysis**

CPjt = β0j

Dividend payout ratio is the ratio of the amount of dividend paid per unit of total earnings, also represents the percentage of earnings distributed in the form of dividends to shareholders. The payout ratio is considered to be one of the important variables affecting stock price as current stock value is the discounted value of future cash flows from that stock. The second variable 'debt ratio' is defined as the ratio of total debt to total assets, expressed as a decimal or percentage. It can be interpreted as the proportion of a company's assets that are financed by debt. It is a measure of financial risk on the assets of a company, and higher financial risk will affect the returns and consequently price of a stock. The third variable considered in the study is EPS, which measures the income generated on one share. It is a ratio of net income to the number of shares outstanding. In most of the studies, EPS has emerged as a significant variable having a positive impact on share prices. In literature, many studies have tried to measure the impact of the size of the company on the stock prices. Some of them have used the logarithm of sales as the proxy for company size and in some cases logarithm of total assets. Both sales and total assets are an indicator of business size. Many investors take their investment decision by company size as bigger companies are more stable regarding profit and are also less prone to the business cycle. Price-earnings ratio commonly known as PE ratio is one of the prime indicators used in the stock selection by the investors. PE ratio is the ratio of the market price of a stock to its EPS. It is a measure of investor's confidence on stock and is a reflection of investor's anticipation of higher growth in the future. Gordon growth model confirms the role of the growth rate of the company on the intrinsic value of the stock.

#### **3.1. Hypothesis**

The following hypothesis statements were formulated on the basis of available literature and theory which provides the scope and depth to the study.

Hypotheses H01 to H06 are framed to test the reflection of publicly available information on the stock prices based on semi-strong form of EMH.

H01: There is no significant effect of size of the company on its share price.

H02: There is no significant effect of dividend payout ratio on share price.

H03: There is no significant effect of EPS on share price.

H04: There is no significant effect of leverage on share price.

H05: There is no significant effect of price-earnings ratio on share price.

H06: There is no significant effect of first lag of share price on current share price.

The following hypothesis are framed to confirm the impact of economic variables on the stock returns based on arbitrage pricing theory (APT),


#### **3.2. Panel data analysis**

variables affecting stock prices. Fama and Schwert [23] the well-known study was also based on the relationship between stock prices and inflation. Oman being the net exporter and mainly depending on oil and gas export is facing the heat of low oil prices. Economy of Oman like other GCC countries is driven by oil and gas, so consideration of oil price as an independent

Dividend payout ratio is the ratio of the amount of dividend paid per unit of total earnings, also represents the percentage of earnings distributed in the form of dividends to shareholders. The payout ratio is considered to be one of the important variables affecting stock price as current stock value is the discounted value of future cash flows from that stock. The second variable 'debt ratio' is defined as the ratio of total debt to total assets, expressed as a decimal or percentage. It can be interpreted as the proportion of a company's assets that are financed by debt. It is a measure of financial risk on the assets of a company, and higher financial risk will affect the returns and consequently price of a stock. The third variable considered in the study is EPS, which measures the income generated on one share. It is a ratio of net income to the number of shares outstanding. In most of the studies, EPS has emerged as a significant variable having a positive impact on share prices. In literature, many studies have tried to measure the impact of the size of the company on the stock prices. Some of them have used the logarithm of sales as the proxy for company size and in some cases logarithm of total assets. Both sales and total assets are an indicator of business size. Many investors take their investment decision by company size as bigger companies are more stable regarding profit and are also less prone to the business cycle. Price-earnings ratio commonly known as PE ratio is one of the prime indicators used in the stock selection by the investors. PE ratio is the ratio of the market price of a stock to its EPS. It is a measure of investor's confidence on stock and is a reflection of investor's anticipation of higher growth in the future. Gordon growth model confirms the role of the growth rate of the company on

The following hypothesis statements were formulated on the basis of available literature and

Hypotheses H01 to H06 are framed to test the reflection of publicly available information on the

The following hypothesis are framed to confirm the impact of economic variables on the stock

variable makes sense.

26 Firm Value - Theory and Empirical Evidence

the intrinsic value of the stock.

theory which provides the scope and depth to the study.

H03: There is no significant effect of EPS on share price. H04: There is no significant effect of leverage on share price.

H01: There is no significant effect of size of the company on its share price. H02: There is no significant effect of dividend payout ratio on share price.

H05: There is no significant effect of price-earnings ratio on share price.

H06: There is no significant effect of first lag of share price on current share price.

stock prices based on semi-strong form of EMH.

returns based on arbitrage pricing theory (APT),

**3.1. Hypothesis**

Panel data analysis has been used to analyze the impact of firm-specific and macroeconomic determinants on the share price of the nonfinancial listed companies in Oman. Panel data always has advantages over time-series and cross-sectional data. Panel data analysis weakens the interaction between the variables that result in more reliable parameters, Hsiao [24]. Employment of this technique is considered more efficient as it reduces the co-linearity of the predictor variables and also it offers gain regarding the degree of freedom. The research study uses both the panel data methods, that is, fixed effect method and the random effect method. The better method is then selected applying the Hausman test. Both the models fixed effects and the random effects have been represented by the following Eqs. (1) and (2), respectively:

$$\begin{array}{l} \mathbf{CP}\_{\mathbb{H}} = \beta\_{\mathbb{q}} + \beta\_{1} \mathbf{CP}\_{\mathbb{p}-1} + \beta\_{2} \mathbf{Dividend\_{\mathbb{p}} + \beta\_{3} \mathbf{EPS}\_{\mathbb{p}} + \beta\_{4} \mathbf{Leverage}\_{\mathbb{p}} + \beta\_{5} \mathbf{GDP}\_{\mathbb{p}} \\ \quad + \beta\_{\mathbb{s}} \mathbf{Inflation}\_{\mathbb{p}} + \beta\_{7} \mathbf{Size}\_{\mathbb{p}} + \beta\_{8} \mathbf{Oil}\_{\mathbb{p}} + \beta\_{9} \mathbf{PE}\_{\mathbb{p}} + \mu\_{\mathbb{p}} \end{array} \tag{1}$$

$$\begin{aligned} \text{CP}\_{\text{\tiny\text{\tiny\text{\tiny}}}} &= \beta\_0 + \beta\_1 \text{CP}\_{\text{\tiny\text{\tiny}}-1} + \beta\_2 \text{Dividendend}\_{\text{\tiny\text{\tiny}}} + \beta\_3 \text{EPS}\_{\text{\tiny\text{\tiny}}} + \beta\_4 \text{ Leverage}\_{\text{\tiny\text{\tiny}}} + \beta\_5 \text{ GDP}\_{\text{\tiny\text{\tiny}}} \\ &+ \beta\_\delta \text{ Inflation}\_{\text{\tiny\text{\tiny}}} + \beta\_\gamma \text{ Size}\_{\text{\tiny\text{\tiny}}} + \beta\_s \text{ Oil}\_{\text{\tiny\text{\tiny}}} + \beta\_\rho \text{ PE}\_{\text{\tiny\text{\tiny}}} + \mu\_{\text{\text{\tiny}}} \end{aligned} \tag{2}$$

where, CPjt = annual closing price of firm's stock in year t; β0 = common y-intercept; β1 –β9 are the coefficients of concerned explanatory variables; ɛjt = stochastic error term for firm j at time t; β0j = firm j's y-intercept; μjt = error term for firm j at time t.

Based on the literature on share price determinants, the following company-specific variables dividend payout ratio, leverage, earning per share, size of the company, price earnings ratio and three economy based variables growth rate in GDP, inflation rate and crude oil prices were selected as the predictor variables in the regression analysis. Apart from these variables, first lag of yearly closing price of shares was also considered as a predictor variable.

### **4. Data analysis**

This section presents the results of panel data analysis which are reported in **Table 2**. Both the fixed effect and random effect model was used to measure the impact of the selected independent variables on the stock prices of sample companies. Then the Hausman specification test was used to select a better model between fixed effects and random effects model. The null hypothesis in Hausman test is that the preferred model is random effects and the alternate hypothesis is that the preferred model is fixed effects.


**4.1. Testing of research hypotheses**

**Table 3.** Result of Hausman Test.

**5. Conclusion**

concept of 'trading on equity.'

to bigger and established firms.

study.

Results of random effect model indicate the rejection of the null hypothesis H03, H04 and H06 at 5% level of significance. Other null hypothesis like H01, H02 and H05 are not rejected at 5%. Hypothesis H01 to H06 were framed to test the existence of semi-strong form of EMH in capital market of Oman, which is partially met. Similarly, two null hypotheses (H07 and H08) are rejected

**Test Summary Chi-Square Statistic Probability** Cross-section random 0.000000 1.0000

Stock Price Determinants: Empirical Evidence from Muscat Securities Market, Oman

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29

The study aimed at investigating the effect of dividend payout, EPS, a log of total assets, debt ratio, PE ratio and previous year stock price on the current stock price of 26 listed nonfinancial companies in Oman. Three economic variables—growth rate in GDP, crude oil prices and consumer price index—are also considered as an independent variable in this

The empirical analysis is based on random effect model regression analysis with the stock price as the dependent variable. Based on the data analysis, the study finds that EPS has a significant positive effect on the price of common stock. Relatively, the value of the coefficient (12.16) for EPS is the highest among all the independent variables. In the majority of the existing studies, EPS had shown the same relationship with stock price [5, 6, 15, 19, 20]. EPS is a direct measure of shareholders earning on one share, and stocks with high EPS are commonly selected by equity analysts. Debt ratio (leverage) is also a significant variable having a positive relationship with stock price. Conceptually higher debt capital is an indication of financial risk, and hence an investor avoids these stocks. The reason for a positive relation between leverage and stock price could be a low percentage of debt capital in sample companies, as up to a certain level debt capital is favorable for stockholders which has been explained by the

First lag of stock price is also significant and has a positive effect on current stock price consistent with Şebnem and Vuran [16]. This finding supports 'Behavioral Finance Theory' which explains the inconsistent behavior of investors toward theories and concepts. Dividend payout is insignificant determinant for stock prices, and results are consistent with the previous studies [9, 15, 18]. However, intrinsic value of a stock depends on future dividends; this may be because of anomalies or investors giving weightage to capital gains. The firm size is not significant; this result shows that investors are not giving any preference

at 10% level of significance and supports APT theory for stock prices.

**Table 2.** Determinants of share price according to fixed and random effect model.

According to the results of fixed effects model earnings per share, a log of total assets (a proxy for company size) and crude oil prices are found to be significant determinants of the changes in stock prices. All the three variables have a positive relationship with share prices. The macroeconomic variables growth rate in GDP and consumer price index are found to be insignificant in explaining the changes in share prices.

Results of the Hausman test are reported in **Table 3**, and according to that, null hypothesis is accepted. Therefore, random effects model is supposed to be a better model for analyzing this panel data. Value of R square is also quite high with 93.23% of variations in stock price explained by the regression model. In Random effects model, among the company-specific variables used in this study, lag of share prices, earnings per share and leverage are the statistically significant variables. The two variables earnings per share and first lag of share prices are even significant at 1% level of significance. The lag of the share prices has positive coefficient which means the previous hike in share prices are responsible for the increase in share price of the next year. Investors invest by stock price movement; this result supports the behavioral theory of finance. Earnings per share (EPS) is one of the most dominant determinants of share prices with the highest positive regression coefficient of 12.16 and significant at 1%. Debt to the total asset (leverage) is also significant and is positively related to sharing prices of the sample companies. The dividend has proved to be an insignificant determinant of the share prices, and this supports the irrelevance of dividend policy on the firm value. The logarithm of total assets (size of the company) and PE ratio are also not significant determinants at 5%.

From the three external variables, inflation rate and crude oil price are significant at 10% level of significance. The result of inflation rate is consistent with the previous studies and has a negative impact on share prices [21, 23]. Oman being an exporter of crude oil, the oil prices are significant determinants and have a positive impact on them. The growth rate in GDP is not seen as important and significant variables for share prices in Oman.


**Table 3.** Result of Hausman Test.

#### **4.1. Testing of research hypotheses**

Results of random effect model indicate the rejection of the null hypothesis H03, H04 and H06 at 5% level of significance. Other null hypothesis like H01, H02 and H05 are not rejected at 5%. Hypothesis H01 to H06 were framed to test the existence of semi-strong form of EMH in capital market of Oman, which is partially met. Similarly, two null hypotheses (H07 and H08) are rejected at 10% level of significance and supports APT theory for stock prices.
