Final Project GBU

Analysis of Factors Impacting Stock Price Change of

Companies Listed on Casablanca’s Stock Market

Ayoub Fikri

Al Akhawayn University

Charaf El Gharbi Al Akhawayn University

Fatima Zahra Chakir Al Akhawayn University

Dr. Khondker Aktaruzzaman

Assistant Professor, Al Akhawayn University

Fall 2014

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Abstract

Making profit is the common goal for the most of investors. In order to make a decision

concerning investing in stock exchange, investors should deeply understand the factors that

determine the stock price. According to scholars, the stock price of a company tend to be

unstable, which lead investors to look for the elements that are influencing it in order to predict

its movement, consequently make a profitable investment decision. The factors that influence the

stock price can be either internal or external, and direct or indirect. The internal factors include

dividend, which is the cash payment that the stockholders receive, the market capital that is the

company’s value, the net income that is the total earning of the company, the earning per share,

the liquidity of the firm, the book value and the return on equity. The external factors could be

any change in the government policies, political issues, rules and regulations, the international

situation, the exchange rate and the media. In this study, we selected three internal factors that

could affect the stock price, which are the earning per share, the book value, and the return on

equity. After running different tests using the multiple regression analysis including T-test, F-test,

and Durbin Watson test, we found significant results as P-value < α, which would be interpreted

by the existence of a linear relationship between the independent variables (earning per share,

book value, and return on equity), and the dependent variable (stock price).

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Table of Contents

Introduction .................................................................................................................................................. 3

Data & Descriptive statistics ....................................................................................................................... 4

Data ............................................................................................................................................................ 4

Descriptive statistics ................................................................................................................................... 4

Assumptions ............................................................................................................................................... 6

Methodology & Findings ............................................................................................................................. 7

Methodology .............................................................................................................................................. 7

Findings ...................................................................................................................................................... 7

R² and R² adjusted ................................................................................................................................. 8

F-Test ..................................................................................................................................................... 9

T-Test ..................................................................................................................................................... 9

Confidence Interval Estimation ............................................................................................................ 10

Durbin Watson Analysis ...................................................................................................................... 11

Conclusion ................................................................................................................................................... 12

Literature Cited .......................................................................................................................................... 13

Appendix A: Data Set ............................................................................................................................... 14

Appendix B: Excel Data Output ............................................................................................................... 15

Appendix C: SPSS Data Output ............................................................................................................... 19

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1. Introduction:

Many factors can cause the price of a stock to rise or fall; it could be from specific news

about a company’s earnings or a change in how investors feel about the stock market in general.

In our research, using the statistical tools learned in class we decided to demonstrate how the

stock price is influenced by other factors, particularly in Moroccan’s companies. In order to

choose our independent variables and before collecting data, our team has done some extensive

research to find out what are the appropriate factors that we can use for the research. We based

the search on other countries in order to see afterwards if the same factors could be applied to the

Moroccan context.

According to a study that was conducted in Malaysia, earning per share significantly affects

stock prices. The aim of the study was to determine the impact of the earning per share (EPS) on

stock prices of Public Banks located in Malaysia, and to measure the degree of stock prices’

response to changes in earning per share. The study indicated that EPS has a significant impact

on the movement of stock prices of the bank, and contributes significantly to the explanation of

long-term stock price variation. Hence, it is considered as one of the strongest factors to evaluate

the actual performance and the progress of a company since it reflects its financial situation.

In 1984, a researcher called Balakrishnan studied the impact of dividend per share, earning

per share, and book value and yield on share price of firms in India and his studies showed up

that the book value and dividend per share turned out to be the most valuable determinants of

market price in all firms studied. However, in our project dividend per share was not found in

many Moroccan companies while collecting data so we could not consider it as one of the

independent variables and only chose the book value. Moreover, in another study that AL

Khalaileh conducted in 2001; 40 Jordanian public firms were chosen as a sample for his study. Al

Khalaileh examined the link between accounting performance indicators and market ones. The

outcome showed an important optimistic relationship between the market price per share and the

ratios of return on assets and return on equity.

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2. Data and Descriptive statistics:

Data:

To collect data in order to conduct our project, we have been searching in the Casablanca

Stock Exchange website, and we have retrieved a sample of 35 companies for the year 2014 after

erasing those with insufficient data. After a deep research in what are the factors that could

influence the stock price, we have found ourselves with only three main factors applicable in the

Moroccan context that are earning per share, book value, and return on equity. The sample size

is equal to 35, so the central limit theorem is applicable for this study and the population is

normally distributed.

Descriptive statistics:

First, we will analyze the data using descriptive analysis techniques.

Figure 1: Scatter plot of the Stock Price versus the Book Value.

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Figure 2: Scatter plot of the Stock Price versus the Return on Equity (%).

Figure 3: Scatter plot of the Stock Price versus the Earnings per Share.

After the analysis of the data, we should be able to conclude that earnings per share, book

value and return on equity positively affect the stock price of the companies that we selected for

the study.

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Assumptions:

1st Assumption: Linearity.

Using SPSS and Excel, we plotted the independent variables, which are earnings per share

EPR, book value and return on equity ROE (%) against the dependent variable which is the stock

price separately in three different graphs. From the three graphs, we were able to conclude the

linearity.

Please refer to Appendices B and C for the linearity graphs.

2nd Assumption: Normal Distribution.

Figure 4: Histogram of the Frequency versus the Regression Standardized Residual.

The figure above shows a histogram of frequency vs. regression-standardized residuals. The

graph demonstrates that the residuals are normally distributed.

3rd Assumption: Independence of errors.

Durbin-Watson: We have found that Durbin-Watson = 1.953 close to 2

Which means that we do not have a positive autocorrelation.

4th Assumption: Equality of variances.

Using SPSS, the graphs confirm that there is no pattern of residual errors. (See Appendix C).

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3. Methodology and Findings:

Methodology:

To reach the objective of our project, we have conducted a research in order to know what

are the factors influencing the stock price of the Moroccan firms. We have conducted a multiple

regression analyses by using the statistical tools we have learned throughout this semester. The

way our team have preceded is as followed:

Looking for the factors influencing the stock price of companies in other

countries.

Select only the factors that are significant to our study and applicable to the

Moroccan context.

Dependent variable:

Y: Stock price is the price of a single share of a number

of saleable stocks of a company, derivative or other

financial asset.

Independent variables:

X1: Book value is a measure of all of a company's

assets: stocks, bonds, inventory, manufacturing

equipment, real estate, etc.

X2: Return on equity (%) effectively measures how

much profit a company can generate on the equity

capital investors have deployed in the business, and can

be used over time to evaluate changes in a company’s

financial situation. In other words, Return on Equity

indicates the amount of earnings generated by each

dollar of equity.

X3: Earnings per share is the amount earned on behaves

of each outstanding common stock not the distributed

amount to shareholders. This is perhaps the most

important factor for deciding the health of any company

and they influence the buying tendency in the market. It

can measure the profitability of the company.

Plot the data and run the regression through SPSS software and Excel also.

Make sure that we met all four assumptions.

Analyze and interpret all the output results.

Conclusion.

Findings:

Multiple Regression Analysis:

Empirical Model:

Stock Price = β0 + β1 (Book Value) + β2 (Return on Equity) + β3 (Earnings per share) +ε

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Interpretations:

Table 1: Multiple Regression Table using Excel.

Coefficients Standard Error t Stat P-value Lower 95% Upper 95%

Intercept -34,9231 120,8476 -0,2890 0,7745 -281,3933 211,5472

Book Value 171,1294 37,2119 4,5988 0,0001 95,2353 247,0235

Return on Equity (%) -19,4181 8,7620 -2,2162 0,0342 -37,2884 -1,5478

Earnings per Share 15,8461 1,1718 13,5231 0,0000 13,4562 18,2360

From Table 1, we can get the following multiple regression equation:

Ŷ = – 34,9231 + 171,1294 X1 – 19,4181 X2 +15,8461 X3

b0: When all the independent variables: the book value, return on equity and earnings per

share are equal to zero, the stock price is equal to – 34,9231.

b1: If the book value decreases by one precent (holding all the other independent variables

constant), the stock price decreases by 171,1294.

b2: If the return on equity increases by one precent (holding all the other independent

variables constant), the stock price increases by – 19,4181.

b3: If the earnings per share increase by one precent (holding all the other independent

variables constant), the stock price increases by 15,8461.

R² and R² adjusted:

We know that: 𝐑𝟐 =𝐑𝐞𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧 𝐒𝐮𝐦 𝐨𝐟 𝐒𝐪𝐮𝐚𝐫𝐞𝐬

𝐓𝐨𝐭𝐚𝐥 𝐒𝐮𝐦 𝐨𝐟 𝐒𝐪𝐮𝐚𝐫𝐞𝐬=

𝐒𝐒𝐑

𝐒𝐒𝐓

From the table, R² = 0,873 which means that 87.3% of the variability in the company’s stock

price is explained by the variation in book value, return on equity, and earnings per share of this

company.

𝐑𝟐𝒂𝒅𝒋𝒖𝒔𝒕𝒆𝒅 = 𝟏 −

(𝟏−𝐑𝟐)(𝒏−𝟏)

(𝒏−𝒌−𝟏)

From the table, R² adjusted = 0,861 meaning that 86.1% variance in the stock price is

explained by the multiple regression model adjusted of book value, return on equity, and the

earnings per share.

Table 2: Table of R² and R² adjusted generated by SPSS software.

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 0,934 0,873 0,861 325,10701

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F-Test:

H0: β1 = β2 = β3 = 0 (There is no linear relationship between book value, return on equity

and earnings per share).

H1: At least one βj is different from zero (at least one independent variable affects the stock

price).

Table 3: Simple Regression Table using Excel.

ANOVA

df SS MS F Significance F

Regression 3 22543967,53 7514655,84 71,10 5,42E-14

Residual 31 3276531,61 105694,57

Total 34 25820499,13

We know that: 𝐅 =𝐌𝐒𝐑

𝐌𝐒𝐄 with: MSR = 7514655.84 and MSE = 105694,57

FSTAT = 71,10

For FCRIT, we consider α = 0,05, and since k = 3 the degrees of freedom are 3 and 31:

FCRIT(0,05; 3; 31) = 2.92

Therefore, since FSTAT > FCRIT: We Reject H0. Thus, there is sufficient evidence of a

significant relationship between the stock price and the three independent variables.

T-Test:

Table 4: Multiple Regression Table for t Stat using Excel.

Coefficients Standard Error t Stat P-value Lower 95% Upper 95%

Intercept -34,9231 120,8476 -0,2890 0,7745 -281,3933 211,5472

Book Value 171,1294 37,2119 4,5988 0,0001 95,2353 247,0235

Return on Equity (%) -19,4181 8,7620 -2,2162 0,0342 -37,2884 -1,5478

Earnings per Share 15,8461 1,1718 13,5231 0,0000 13,4562 18,2360

We use the t-test: 𝑻𝑺𝑻𝑨𝑻 =𝒃𝟏− 𝜷𝟏

𝑺𝒃𝟏

We already have the results of TSTAT of each variable from Table 4, so we will compare each

one with the critical value to give the appropriate interpretations.

The critical value will be the same for the three variables, we consider α/2= 0.025, df = 33:

TCRIT(0,025; 33) = ±2.0345

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Test for b1:

Ho: β1= 0 (The Book Value does not have a significant effect on Stock Price).

H1: β1 ≠0 (The Book Value has a significant effect on Stock Price).

We have TSTAT = 4,5988

Since, TSTAT > TCRIT(0,025; 33): We Reject H0. Thus, the Book Value has a significant effect on Stock

Price.

Test for b2:

Ho: β2= 0 (The Return on Equity does not have a significant effect on Stock Price).

H1: β2 ≠0 (The Return on Equity has a significant effect on Stock Price).

We have TSTAT = -2,2162

Since, TSTAT = -2.2162 < TCRIT(0,025; 33) = -2.0345: We Reject H0. Thus, the Return on Equity has

a significant effect on Stock Price.

Test for b3:

Ho: β3= 0 (The Earnings per Share does not have a significant effect on Stock Price).

H1: β3 ≠0 (The Earnings per Share has a significant effect on Stock Price).

We have TSTAT = 13,5231

Since, TSTAT > TCRIT(0,025; 33): We Reject H0. Thus, the Earnings per Share has a significant effect

on Stock Price.

Confidence Interval Estimation:

We know that df = 31 and α = 0.05.

Test for b1:

b1 ± tCRIT(0,025; 31)*Sb1

95,235 < β1 < 247,02

Thus, we are 95% confident that β1 will lie between 95,235 and 247,02.

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Test for b2:

b2 ± tCRIT(0,025; 31)*Sb2

-37,288 < β2 < -1,548

Thus, we are 95% confident that β2 will lie between -37,288 and -1,548.

Test for b3:

b3 ± tCRIT(0,025; 31)*Sb3

13,456 < β3 < 18,236

Thus, we are 95% confident that β3 will lie between 13,456 and 18,236.

Durbin Watson Analysis:

Table 5: Table of Durbin Watson factor generated by SPSS software.

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate Durbin-Watson

1 0,934 0,873 0,861 325,10701 1,953

Ho: There is no positive autocorrelation among residuals.

H1: There is a positive autocorrelation among residuals.

D = ∑(𝒆𝒊−(𝒆(𝒊−𝟏))^𝟐)

(𝒆𝒊^𝟐 )

𝒏𝒊=𝟐 DSTAT = 1.953

We have n = 35, k = 3 and α = 0.05

So: Dlower = 1,28 and Dupper = 1,65

Since 1,65 < 1.953 < 2, we fail to reject H0. Thus, there is no positive autocorrelation among

residuals.

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4. Conclusion:

The research we conducted on what factors affect the stock price of companies lead us to find

other variables like dividend, market capitalization, variances and others. However, our research

enabled us to choose only three independent variables due to the non-significance and non-

availability of some data of some Moroccan firms that we were interested on. Therefore, our

dependent variable was the stock price and the independent variables were the book value, the

return on equity and earnings per share. We have taken the financial key indicators from

Casablanca’s Stock Exchange official website, as all the necessary information were listed there.

Statistical tools learned in class have been very helpful and were used to demonstrate how the

stock price is influenced by the variables stated above in our study. Moreover, we have used

SPSS and Excel software to generate the necessary information. The generated graphs and tables

allowed us to give a good interpretation of our collected data. Our regression model is:

Stock Price = β0 + β1 (Book Value) + β2 (Return on Equity) + β3 (Earnings per share) +ε (Error)

All our chosen independent variable were significant as the p-value was less than our

significance level α. Also, our R²= 0.873 meant that 87.3% of the variability in the stock price is

explained by the variation in earnings per share, return on equity and book value of the same

corporation.

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Literature Cited

AL Khalaileh, M. “The Relationship between Accounting Performance Indexes and Market Performance Indexes”,

An Applied Study on Listed Corporations at Amman Security Exchange, Administrative Sciences Studies Magazine,

Jordan University, Amman, issue 1, 2001.

A.Seetharaman :”An Empirical study on the impact of earning per share on stock prices of a listed bank in

Malaysia”. The International Journal of Applied Economics and Finance. 2011

Casablanca Stock Exchange. “Cours des valeurs.” Retrieved November 23, 2014 from: http://www.casablanca-

bourse.com/bourseweb/Cours-Valeurs.aspx?Cat=24&IdLink=300

Sharma, S. (2011), “Determinants of equity share prices in India”, Journal of Arts, Science & Commerce, 2(4): 51-

60.

Srivastava, R. M. (1984), “Testing Modigliani - Millers Dividend Valuation Model in Indian Context - A Case Study

of 327 Joint Stock

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APPENDIX A – Data Set

Company Name Stock Price Book Value Return on Equity (%) Earnings per Share

AFRIQUIA GAZ 1860,00 2,89 19,83 116,14

ALLIANCES 371,95 1,15 11,08 47,41

ALUMINIUM DU MAROC 1035,00 1,40 12,58 101,12

ATLANTA 70,00 3,34 8,88 1,83

ATTIJARIWAFA BANK 341,90 1,64 10,92 20,35

AUTO HALL 85,00 2,24 12,79 4,52

AUTO NEJMA 1760,00 2,48 15,76 91,49

AXA CREDIT 350,00 1,28 7,92 24,56

BALIMA 121,00 2,95 14,78 7,65

BCP 217,55 0,97 5,66 11,27

BMCE BANK 223,25 1,92 6,43 6,86

BMCI 760,00 1,24 7,54 48,19

BRASSERIES DU MAROC 2250,00 4,44 18,73 94,88

CARTIER SAADA 18,55 1,11 5,76 0,93

CDM 550,00 1,49 6,59 26,95

CENTRALE LAITIERE 1450,00 9,89 16,31 23,41

CGI 725,00 3,23 8,18 19,93

CIH 344,95 1,44 10,74 19,35

CIMENT DU MAROC 965,00 1,98 13,05 56,03

COLORADO 76,89 1,62 14,41 5,34

COSUMAR 1700,00 2,28 17,53 150,01

CTM 329,00 0,93 12,69 28,55

DELTA HOLDING 31,00 1,64 8,45 1,64

EQDOM 1550,00 2,00 11,51 106,56

HOLCIM (Maroc) 2498,00 2,18 11,42 76,28

ITISSALAT AL-MAGHRIB 116,50 4,23 27,79 6,30

LABEL VIE 1349,00 2,90 4,39 21,98

LAFARGE CIMENTS 1713,00 4,50 27,36 79,98

LESIEUR CRISTAL 102,00 1,97 8,56 4,52

LYDEC 393,00 1,58 17,66 36,98

MAGHREB OXYGEN 136,00 0,53 3,52 8,93

MICRODATA 139,00 2,60 38,00 17,98

NEXANS MAROC 190,00 0,49 1,50 4,44

OULMES 874,50 3,22 15,35 40,10

WAFA ASSURANCE 3700,00 2,38 17,68 222,86

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APPENDIX B – Excel Data Output

SUMMARY OUTPUT

Regression Statistics

Multiple R 0,934400062

R Square 0,873103475

Adjusted R Square 0,860823166

Standard Error 325,10701

Observations 35

ANOVA

df SS MS F Significance F

Regression 3 22543967,53 7514655,84 71,10 5,42E-14

Residual 31 3276531,61 105694,57

Total 34 25820499,13

Coefficients Standard Error t Stat P-value Lower 95% Upper 95%

Intercept -34,9231 120,8476 -0,2890 0,7745 -281,3933 211,5472

Book Value 171,1294 37,2119 4,5988 0,0001 95,2353 247,0235

Return on Equity (%) -19,4181 8,7620 -2,2162 0,0342 -37,2884 -1,5478

Earnings per Share 15,8461 1,1718 13,5231 0,0000 13,4562 18,2360

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RESIDUAL OUTPUT PROBABILITY OUTPUT

Observation Predicted Stock Price Residuals

Standard

Residuals Percentile Stock Price

1 2391,9268 -691,9268 -2,2289 1,4286 18,55

2 207,6075 -105,6075 -0,3402 4,2857 31

3 57,9194 -39,3694 -0,1268 7,1429 70

4 1711,7952 -261,7952 -0,8433 10,0000 76,89

5 393,2150 -323,2150 -1,0412 12,8571 85

6 3560,5155 139,4845 0,4493 15,7143 102

7 356,1520 -14,2520 -0,0459 18,5714 116,5

8 277,4914 -54,2414 -0,1747 21,4286 121

9 794,4887 -34,4887 -0,1111 24,2857 136

10 199,7517 17,7983 0,0573 27,1429 139

11 519,1471 30,8529 0,0994 30,0000 190

12 309,5752 35,3748 0,1140 32,8571 217,55

13 938,3644 26,6356 0,0858 35,7143 223,25

14 1325,1252 1172,8748 3,7782 38,5714 329

15 1471,2520 241,7480 0,7787 41,4286 341,9

16 1562,7365 -527,7365 -1,7000 44,2857 344,95

17 1864,6691 385,3309 1,2413 47,1429 350

18 47,1103 29,7797 0,0959 50,0000 371,95

19 724,4042 624,5958 2,0120 52,8571 393

20 697,9872 -326,0372 -1,0503 55,7143 550

21 674,7979 50,2021 0,1617 58,5714 725

22 1914,9467 -54,9467 -0,1770 61,4286 760

23 478,5271 -85,5271 -0,2755 64,2857 874,5

24 419,5117 -69,5117 -0,2239 67,1429 965

25 107,6341 -76,6341 -0,2469 70,0000 1035

26 249,1566 -132,6566 -0,4273 72,8571 1349

27 330,2181 -1,2181 -0,0039 75,7143 1450

28 90,1599 99,8401 0,3216 78,5714 1550

29 853,4749 21,0251 0,0677 81,4286 1700

30 128,9296 7,0704 0,0228 84,2857 1713

31 171,6740 -86,6740 -0,2792 87,1429 1760

32 1533,2088 226,7912 0,7306 90,0000 1860

33 304,1323 -183,1323 -0,5899 92,8571 2250

34 -42,9604 181,9604 0,5862 95,7143 2498

35 1772,3943 -222,3943 -0,7164 98,5714 3700

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Figure 1: Scatter plot of Book Value versus Residuals

Figure 2: Scatter plot of Return on Equity (%) versus Residuals

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Figure 3: Scatter plot of Earnings per Share versus Residuals

Figure 4: Scatter plot of Stock Price versus Sample Percentile (Normal Probability Plot)

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APPENDIX C – SPSS Data Output

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