Corporate Fin Report Final

7/31/2019 Corporate Fin Report Final

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The Relationship between PROFITABILITY &

Various Economic Indicators

ABSTRACT:Profitability is the most discussed issue of the business sector. A number of factors

have been suggested to increase the profits of a firm. Those factors are not always

useful for all companies of a specific industry. Sometimes situations deviate from

what theories say. We have discussed the same in this report that whether the

profitability of our industry is consistent with the theories. We have analyzed

Fertilizer industry of Pakistan, taking under consideration the statistics of four

listed companies of KSE, which are as follow:

1. Fouji Fertilizer Company Limited (FFCL)

2. Engro Chemicals Pakistan Limited (Engro)

3. Fouji Fertilizer Bin Qasim Limited (FFBL)

4. Dawood Hercules Chemicals Limited (DHCL)

Research Topic:

Linkage of following financial and economic indicators with profitability of

Fertilizer sector in Pakistan;

1. Liquidity (Current Ratio & Quick Ratio)

2. Leverage

3. Market Price Per Share

4. Year to Year Growth In Revenues

5. GDP

6. GNP

Theories about Profitability:

"Perhaps no term or concept in economic discussion is used with a more bewilderingvariety of well established meanings than profit."

Frank Knight (1934, p, 480).

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In a noninflationary world of family firms using one-period capital inputs with no taxesor debt, measuring profit would be a relatively straightforward matter of deductingexpenses from receipts. The accountant's books and the economist's books wouldcoincide. But in the presence of long-lived assets of various maturities, price changes,debt financing, and taxation, the two book keeping systems diverge and researchersface some difficult questions. Should profit-type income include net interest

payments? How holding gains on real assets or on net financial liabilities should betreated? Should profitability be measured on gross capital stock (includingdepreciation in the numerator) or net stock (excluding depreciation), and indeed areaverage accounting rates of profit meaningful at all?Trade-off theory of capital structure basically entails offsetting the costs of debtagainst the benefits of debt. MM 1963 introduced the tax benefit of debt. Later workled to an optimal capital structure which is given by the trade off theory. The firstelement usually considered as the cost of debt is usually the financial distress costsor bankruptcy costs of debt. It is important to note that this includes the direct andindirect bankruptcy costs.

Trade-off theory can also include the agency costs from agency theory as a cost ofdebt to explain why companies dont have 100% debt as expected from MM 1963.95% of empirical papers in this area of study look at the conflict between managersand shareholders. The others look at conflicts between debt holders andshareholders. Both are equally important to explain how the agency theory is relatedto the trade-off theory.

Following is a brief description of profitability in term of several financial andeconomic indicators.

Leverage and profitability

Theories of capital structure indicate that profitability is an important determinant ofleverage. Element of financial risk is high in highly leveraged companies as comparedto low leveraged companies. Equity holders are to be rewarded with a higher financialpremium in case of highly geared companies. The more the leveraged firm, more theprofits are related to it according to the general perception.

Liquidity & Profitability

The firms are considered more sustainable which have good liquidity. This is backed

by the phrase, one in hand is better than two in the bush. The profits are related to it

theoretically. More liquid a firm is, more strongly it can face its creditors. This will

ultimately increase firms strength.

Market price/share & profitability

Usually as per analysis market value of share is linked to profitability and dividends of

the company which is also inherently linked with profits of the company. Companies

in fertilizer sector with substantial profits have a higher market value as compared to

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companies with low profits. So it is perceived that higher market value of a firm leads

to higher profitability.

Growth in Revenues & profitability

Growth in revenues determines the future outlooks and market value of the company.

As revenue increases it not only helps to increase the value of shareholder but

provides liquidity to finance the profitable projects which may lead to integration and

diversification.

GDP & Profitability

GDP is an economic indicator showing income on domestic basis. Usually when GDP

of a country increases, the firms and industries flourish. Increase in GDP, thus, have a

direct impact on profitability.

GNP & ProfitabilityIt is also an economic indicator on national and international basis. Increase in

exports and decrease in imports of fertilizer products would lead to increase in GNP.

Hence exporting more products may lead firms to earn more and increased

profitability.

A Brief Overview of Fertilizer Sector in Pakistan:

Pakistan, an impoverished and underdeveloped country, has suffered from decades of

internal political disputes, low levels of foreign investment, and a costly, ongoing

confrontation with neighboring India. However, IMF-approved government policies,bolstered by generous foreign assistance and renewed access to global markets since

2001, have generated solid macroeconomic recovery the last five years.

Pakistan has moved from an economy heavily dependent on agriculture to a relativelybalanced economy based on services, industry and agriculture. As of FY07,agriculture contributed 20% to the overall GDP. The government policies are directedtowards improvement of agricultural output through increased credit disbursementsto the agricultural sector and improvement in irrigation.

Fertilizer usage in Pakistan is low and the current fertilizer consumption stands at162.5kg per hectare. This is in large part responsible for the low yield per hectare ofcultivated land which stands at 1.44tn per hectare. Fertilizer consumption closelyfollows economic growth of the country as exhibited by the strong positive correlation(R2=0.9841) between fertilizer consumption per hectare and nominal GDP. As theeconomy is expected to perform well in the future with an estimated nominal GDPgrowth of 14%, we expect fertilizer penetration to increase to 187kg per hectare. Thisgreater demand is expected to continue in the future as economic growth continues.

The industry capacity currently stands at 5.8mntpa whereas local demand is6.8mntpa. This excessive demand ensures sales of total production.Pakistans fertilizer manufacturers have low resource costs due to feedstock gas

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subsidy advanced by the government. Through this subsidy manufacturers are ableto get feed stock gas at significantly lower rates than the market which improvestheir profitability. This subsidy is expected to remain in place at least for the nextthree to four years i.e. until the industry faces an excess supply situation. Later onthe subsidy may be withdrawn from that portion of production which is exported.Production directed towards local sales is expected to continue receiving the subsidy.

The Companies in our coverage are dominant players who hold attractive investmentportfolios. This includes FFCs investments in FFBL and ENGROs investments in varioussubsidiaries.

Types of fertilizer

Urea, which represents 65% of total fertilizer consumed and di-ammonium phosphate(DAP), which accounts for 18%, are the main types of fertilizer used in Pakistan, butthere is a total of eight different fertilizer products which fall into three categories.

Urea, along with calcium ammonium nitrate (CAN) and ammonium sulphate (AS)together make up almost three fourths of total fertilizer consumption and come under

the nitrogenous category. Under the phosphatic category which makes up about 27%,is DAP, triple super phosphate (TSP), single super phosphate (SSP) andnitrophosphate (NP). And under the last category, potassic is sulphate of potashwhich makes up only 1%.

Since the soil in Pakistan generally tends to be deficient in nitrogen, urea is the mostused fertilizer. DAP is used, as most phosphatic fertilizers are to counter the effect ofthe acidic urea and maintain levels of fertility in the soil.

Pakistans agricultural output has suffered in the recent past due to adverse weatherconditions and crop spoilage. The government is omitted to improve agricultureperformance through the following measures1) Irrigation system improvement2) Subsidy to farmers.3) Encouraging use of fertilizer.4) Above average credit disbursementsAs a result of these policies, yield per hectare of Pakistan is showing gradualimprovement although it is still low as compared to other countries. Currently itstands at 1.44tn per hectare.

Statistical Analysis

HYPOTHESIS TESTING

H0: Liquidity, measured by current ratio has no significant effect

on profitability.

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H0: Higher degree of leverage does not lead to change in

profitability in fertilizer sector firms listed on KSE.

H0: MARKET PRICE PER SHARES has no significant effect on

profitability.H0: GDP has no significant effect on profitability.

H0: GNP has no significant effect on profitability.

H0: Growth in Revenues has no significant effect on profitability.

Before going to an industry analysis, there is an individual analysis of each firm how

the profitability of the firm is affected by liquidity ratio.

Testing tool: CHI SQUARE and LINEAR REGRESSION

LINKAGE OF CURRENT RATIO ON PROFITABILITY

FAUJI FERTILIZERS:-

Fauji Fertilizer is directly affected by liquidity, as the co-efficient of determination (R=76%)indicates strong relationship between the two variables. Also looking at related graph, we findupward trend in profitability as liquidity increases.

For Fouji Fertilizer, there is positive relationship between profitability and current ratio ofliquidity.

Model R R SquareAdjusted RSquare

Std. Error ofthe Estimate Durbin-Watson

1 .760(a) .577 .436 5.80487 2.227

a Predictors: (Constant), Current Ratio

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b Dependent Variable: %age change in EBIT

-1.5 -1.0 -0.5 0.0 0.5 1.0

Regression Standardized Residual

0.0

0.5

1.0

1.5

2.0

Frequency

Mean =

Std. De

N = 5

Dependent Variable: %age change in EBIT

Histogram

FAUJI FERTILIZERS BIN QASIM:-

Model of FFBL indicates that the company is not as much dependent on the liquidity

as Fouji Fertilizers. Again strong correlation can be seen in the above table. But the

co efficient of determination is weaker, which shows that though a positive relation

exist between profitability and liquidity, but the height of strength is not as much as

for others. D-W value is more than 2, which mean that there is no auto correlation in

the data.



1 .627(a) .393 .190 62.30031 2.805

a Predictors: (Constant), Current Ratiob Dependent Variable: %age change in EBIT

6

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb


Normal P-P Plot of Regression Standardized Residu


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-1.0 -0.5 0.0 0.5 1.0 1.5


0.0

0.5

1.0

1.5

2.0

Frequency

Mean =

Std. De

N = 5


Histogram

DAWOOD HERCULES:-

Dawood Hercules has less affect

of liquidity, as R2 is 12.9% which

mean that the relation is not

significantly strong. Also

adjusted R square is negative,

which is also clearly indicating

that the liquidity is not a big

consideration in DawoodHercules. We also ran regression

and F-stats for Dawood Hercules,

so that we should have better

insight of the liquidity and

profitability. That showed no

any significant relation between the two variables.

Model Summary(b)



1 .359(a) .129 -.162 45.09484 3.288


ANOVA(b)

ModelSum of Squares Df Mean Square F Sig.

1 Regression

901.015 1 901.015 .443 .553(a)

7

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb




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Residual 6100.633 3 2033.544

Total 7001.648 4


Coefficients(a)

Model

UnstandardizedCoefficients

StandardizedCoefficients

t Sig.B Std. Error Beta

1 (Constant) 36.348 43.596 .834 .466

CurrentRatio

-14.602 21.936 -.359 -.666 .553

a Dependent Variable: %age change in EBIT

-1.0 -0.5 0.0 0.5 1.0 1.5


0.0

0.5

1.0

1.5

2.0

Frequency

Mean

Std. D

N = 5

Dependent Variable: %age change in EBI

Histogram

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb


Normal P-P Plot of Regression Standardized Residual

ENGRO CHEMICALS:-

Engro Chemicals is surprisingly different from the rest of industry, while analyzing for

liquidity. The company has no significant effect of current ratio on profits. Very low

values of R and R2 mean that the positive relation between CR and profitability has no

any significance. For certainty, we also analyzed this company by running regression

and constructing ANOVA table, but it did not show any indication which can prove

strong relation between liquidity and profitability.

Model Summary(b)


Std. Error ofthe Estimate

1 .047(a) .002 -.497 17.10329

a Predictors: (Constant), Current ratiob Dependent Variable: EBIt % age change

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ANOVA(b)

ModelSum of Squares df Mean Square F Sig.

1 Regression

1.307 1 1.307 .004 .953(a)

Residual 585.045 2 292.522

Total 586.352 3

a Predictors: (Constant), Current ratiob Dependent Variable: EBIt % age change

Coefficients(a)

Model




1 (Constant) 27.257 28.322 .962 .437

Currentratio

-.898 13.433 -.047 -.067 .953

a Dependent Variable: EBIt % age change

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb

Dependent Variable: EBIt % age change

Normal P-P Plot of Regression Standardized Resid

LINKAGE OF LEVERAGE WITH PROFITABILITY

FAUJI FERTILIZERS:-

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Even debt is the most dependent variable of todays firms, but here in the fertilizer

sector of Pakistan, its contradictory to that. The Fouji Fertilizer is less dependent on

the debt so this is a low leveraged firm. Following model is giving clear indication that

there is very low association (R2=.236) between the two variables.

Model Summary



1 .486(a) .236 -.018 7.79986 2.183

a Predictors: (Constant), Leverage%b Dependent Variable: EBIT % age change

Also Adjusted R square is negative, which tells that after the adjustment we dont seeany strong relation between profitability and leverage. But positive value of beta(.486) tells that an upward slope exist between variables, so at least they haveconnection.

Coefficients

Model




1 (Constant)

-93.998 109.682 -.857 .454

Leverage%

1.906 1.977 .486 .964 .406

a Dependent Variable: EBIT % age change

-1.0 -0.5 0.0 0.5 1.0 1.5


0.0

0.5

1.0

1.5

2.0

Frequency

Mean =

Std. De

N = 5

Dependent Variable: EBIT % age change

Histogram

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb

Dependent Variable: EBIT % age change

Normal P-P Plot of Regression Standardized Resid

FAUJI FERTILIZERS BIN QASIM LIMITED:-

Model Summary

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1 .808(a) .653 .538 .81198 1.708

a Predictors: (Constant), EBIT %age changeb Dependent Variable: Leverage %

The negative value of beta (-0.808) in the following table indicates an inverse

relationship between debt and profitability. The results are surprising in this industry.There are some valid reasons for this, we will discuss them later. So even the theoryis opposite to it, but there is no dependence of profitability on leverage.

Coefficients

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

95% Confidence Interval for B

B Std. Error Beta Lower Bound Upper Bound

1 (Constant) 69.600 .460 151.415 .000 68.137 71.063

EBIT %agechange

-.014 .006 -.808 -2.379 .098 -.033 .005

a Dependent Variable: Levergae %

-1.0 -0.5 0.0 0.5 1.0 1.5


0.0

0.5

1.0

1.5

2.0

Frequency

Mean =

Std. De

N = 5

Dependent Variable: Levergae %

Histogram

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb

Dependent Variable: Levergae %


DAWOOD HERCULES:-

Model Summary



1 .535(a) .287 .049 40.80494 2.634

a Predictors: (Constant), leverage%b Dependent Variable: %age change in EBIT

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Following table of coefficients shows a negative beta (-0.535), which mean the debtand profitability are oppositely related. Because there is no positive relation betweentwo variables, discussion of strength of correlation is useless.

Coefficients

Model




1 (Constant)

81.926 67.470 1.214 .312

leverage%

-2.574 2.345 -.535 -1.098 .353


-1.0 -0.5 0.0 0.5 1.0 1.5


0.0

0.5

1.0

1.5

2.0

Frequency

Mean =

Std. De

N = 5


Histogram

ENGRO CHEMICALS:-

Model Summary(b)



1 .261(a) .068 -.398 16.52835

a Predictors: (Constant), Leverageb Dependent Variable: EBIT % age change

ANOVA(b)


1 Regressio

n39.979 1 39.979 .146 .739(a)

Residual 546.373 2 273.186

Total 586.352 3

a Predictors: (Constant), Leverageb Dependent Variable: EBIt % age change

Positive value of beta (0.261) indicates a positive relation between leverage andprofitability. Engros profits are related to debt, though not strongly. There are very

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low values of R2 and a negative value of adjusted R2, which mean that the correlationis weak.

Coefficients(a)

Model



t Sig.B Std. Error Beta1 (Constant

)15.868 26.383 .601 .609

Leverage .321 .840 .261 .383 .739

a Dependent Variable: EBIt % age change

We also constructed ANOVA table to see deeply, that either the relation is reallyweak. The answer is, yes. This is due to the low F-value, which is not significant forthe hypothesis to be accepted.

-1.0 -0.5 0.0 0.5 1.0


0.0

0.2

0.4

0.6

0.8

1.0

Frequency

Mean =

Std. De

N = 4


Histogram

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb



INDUSTRY ANALYSIS AND

HYPOTHESIS TESTING

H0: Liquidity, measured by current ratio has no significant

effect on profitability.

TEST OF ASSOCIATION USING CHI SQUARE:-

Chi-Square Tests

Value Df Asymp. Sig.(2-sided)

Pearson Chi-Square 304.000(a) 289 .261

Likelihood Ratio 106.344 289 1.000Linear-by-Linear

Association.046 1 .830

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N of Valid Cases19

a 324 cells (100.0%) have expected count less than 5. The minimum expected count is .05.

Results:

Pearson chi square test rejects the above described null hypothesis.

0.94 0 .9 0 .91 1.07 1.04 1.17 1.34 1.46 1.53 1.53 3.15 1.2 0.45 2.07 2.033.1 1.6 1.8 1.54

10.5

2.1

11.6

23.78

10.5

3.8

-4

37.46

167.4

35.67

-30.2

46.2

1.7

61.8

-26.4

22.9

6.99

39.07

32.79

-50

0

50

100

150

200

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

EBIT % age change

CurrentRatio

Current Ratio EBIT %

REGRESSION ANALYSIS:-

Model Summary(b)



1 .050(a) .003 -.056 43.03341


ANOVA(b)


1 Regression

80.414 1 80.414 .043 .837(a)

Residual 31481.866 17 1851.874

Total 31562.280 18

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Results:

Running simple regression on the fertilizer industry, the hypothesis is rejected, due toinsignificant value of F-stats.

Thus we can interpret that the fertilizer sectors profitability is dependent uponliquidity measured by current ratio.

Coefficients(a)

Model




1 (Constant) 28.480 24.197 1.177 .255

CurrentRatio

-3.035 14.565 -.050 -.208 .837


-2 -1 0 1 2 3 4


0

1

2

3

4

5

6

Frequency

Mean

Std. D

N = 19

Dependent Variable: %age change in EBI

Histogram

0.0 0.2 0.4 0 .6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb

Dependent Variable: %age change in E

Normal P-P Plot of Regression Standardize

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H0: Higher degree of leverage does not lead to change

in profitability in fertilizer sector firms listed on KSE.

TEST OF ASSOCIATION USING CHI SQUARE:-

-50

0

50

100

150

200

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

LEVERAGE%

EBIT%C

hange

EBIT %

REGRESSION ANALYSIS:-

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Coefficients(a)

Model



T Sig.B Std. Error Beta

1 (Constant) 4.153 26.130 .159 .876

Leverage%

.426 .524 .193 .813 .428


Result:

We shall reject the null hypothesis. So the leverage is significant in increasing theprofitability.

-2 -1 0 1 2 3 4


0

1

2

3

4

5

6

7

Frequency

Mean =

Std. De

N = 19


Histogram

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb



Results:

The regression and chi square tests conclude that the fertilizer industry has positiveassociation with debt in term of profitability. Thus the correlations are not strong

enough, but the positive values of R and beta mean that leverage effects the industry

according to the theory.

LINKAGE OF MARKET PRICE PER SHARES WITH

PROFITABILTY

H0: MARKET PRICE PER SHARES has no significant effect

on profitability.

FAUJI FERTILIZERS

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FAUJI FERTILIZERS BIN QASIM

DAWOOD HERCULES

ENGRO CHEMICALS

The model of regression is constructed for all the companies simultaneously. Looking

at the coefficients, the negative value of beta tells that the market price per share

has no positive relation with profitability. The values of R and R2 are very low, so it

comes out that profitability is independent of market price per share, for these four

fertilizer companies.

Model Summary (b)



1 .260(a) .068 -.398 16.53155

Predictors: (Constant), Market price per shareB Dependent Variable: EBIT % age change

ANOVA (b)


1 Regression

39.768 1 39.768 .146 .740(a)

Residual 546.584 2 273.292

Total 586.352 3

Predictors: (Constant), Market price per shareB Dependent Variable: EBIT % age change

Coefficients (a)

Model




1 (Constant) 36.787 30.843 1.193 .355

Market priceper share

-.062 .163 -.260 -.381 .740


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-1.5 -1.0 -0.5 0.0 0.5 1.0


0.0

0.5

1.0

1.5

2.0

Frequency

Mean =

Std. De

N = 4


Histogram

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb



Hence we concluded that there is no significant relationship between profits before

taxes and interests and market price per share.

LINKAGE OF GDP WITH PROFITABILTY

H0: GDP has no significant effect on profitability.

FAUJI FERTILIZERS:-

Positive value of beta indicates relationship of profitability and GDP. Increasing the

GDP, increases the profits of fertilizer companies. Though the relationship is not very

strong but it exists.

Model Summary (b)



1.258(a) .066 -.245 8.62542

a Predictors: (Constant), GDPb Dependent Variable: %age change in EBIT

ANOVA table shows that the significance of relation is very weak.

ANOVA(b)

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1 Regression

15.854 1 15.854 .213 .676(a)

Residual 223.194 3 74.398

Total 239.048 4


Coefficients(a)

Model




1 (Constant)

2.778 19.665 .141 .897

GDP 1.279 2.771 .258 .462 .676


-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5


0.0

0.5

1.0

1.5

2.0

Frequency

Mean =

Std. De

N = 5


Histogram

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb



The trend can be seen from the graph above, that GDP is an indicator of increasing

profits.


Model Summary(b)



1 .204(a) .041 -.278 78.27698


Fouji Fertilizer BIN Qasim also has positive relation with GDP. The positive value ofbeta (.204) means the profitability is dependent upon GDP. But the relation is not sosignificant due to negative value of adjusted R2 and low value of F in the ANOVAtable.

ANOVA(b)

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1 Regression

795.240 1 795.240 .130 .743(a)

Residual 18381.858 3 6127.286

Total 19177.099 4


Coefficients(a)

Model




1 (Constant)

-14.979 178.466 -.084 .938

GDP 9.058 25.144 .204 .360 .743


0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb


Normal P-P Plot of Regression Standardized Residua

GDP AND EBIT

-50

0

50

100

150

200

2007 2006 2005 2004 2003

%

ofsales

GDP EBIT

If we see the graph, we can conclude that the relation is not as much stronger asshould be.

DAWOOD HERCULES:-Model Summary(b)



1 .302(a) .091 -.212 46.05497


Dawood Hercules has a positive and greater value of beta than that of previous. Mean

there is positive slope between GDP and profitability of Dawood Hercules.ANOVA(b)


1 Regression

638.467 1 638.467 .301 .621(a)

Residual 6363.181 3 2121.060

Total 7001.648 4

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The value of F is not so significant that we can conclude a strong relationshipbetween the two variables.

Coefficients(a)

Model




1 (Constant)

-45.870 105.002 -.437 .692

GDP 8.116 14.793 .302 .549 .621


0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb



GDP AND EBIT

-50

0

50

100

150

200

2007 2006 2005 2004 2003

%

ofsale

GDP EBIT

Looking at the graph we cannot conclude a relationship, but the positive value of R

and beta cannot be ignored so easily.

ENGRO CHEMICALS:

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Engro Chemicals is strongly correlated with GDP. The very high value of R and beta

(0.869) mean a positive slope between profitability and GDP. The value of R2 (75.6%)

and adjusted R2 are both consistent with the relationship.

Model Summary (b)



1 .869(a) .756 .634 8.45896

a Predictors: (Constant), GDPb Dependent Variable: EBIT % age change

While we constructed ANOVA table, we see that the value of F is significantly largeindicating strong relationship between profitability and GDP.

ANOVA (b)


1 Regression

443.244 1 443.244 6.195 .131(a)

Residual 143.108 2 71.554

Total 586.352 3

a Predictors: (Constant), GDPB Dependent Variable: EBIT % age change

Coefficients (a)

Model




1 (Constant)

-61.659 35.255 -1.749 .222

GDP 11.576 4.651 .869 2.489 .131

A Dependent Variable: EBIT % age change

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0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb



GDP AND EBIT

0

5

10

15

20

25

30

35

40

45

2007 2006 2005 2004 2003

%

ofsales

GDP EBIT

From the graph, the results can be interpreted, that the fluctuations in profitability

are connected to the GDP.

LINKAGE OF GNP WITH PROFITABILTY

H0: GNP has no significant effect on profitability.

FAUJI FERTILIZERS:-

The relation between GNP and EBIT (profitability) is not much significant. The reason

is negative value of beta (-0.070). The values of R and R2 are of no use that therelation is inverse between the two variables.

Model Summary(b)



1 .070(a) .005 -.327 8.90487

a Predictors: (Constant), GNP

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ANOVA table also does not give any strong relation between two variables as the Fvalue is very low.

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.

1 Regression

1.158 1 1.158 .015 .911(a)

Residual 237.890 3 79.297

Total 239.048 4

a Predictors: (Constant), GNPb Dependent Variable: %age change in EBIT

Coefficients(a)

Model




)15.692 33.441 .469 .671

GNP -.559 4.624 -.070 -.121 .911


0

5

10

15

20

25

2007 2006 2005 2004 2003

GDP

EBIT %AGE CHANGE

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb


Normal P-P Plot of Regression Standardized Residua

The insignificance can be seen in the above graph between EBIT and GNP, for FoujiFertilizer.


The value of beta is negative again, so the relation is inverse between GNP and EBIT.

Adjusted R2 is also negative, insisting to not accept the correlation between the

variables.

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Model Summary(b)



1 .226(a) .051 -.265 77.89087



ANOVA table gives very low F-value, indicating no significant relation between twovariables.

ANOVA(b)


1 Regression

976.137 1 976.137 .161 .715(a)

Residual 18200.962 3 6066.987

Total 19177.099 4


b Dependent Variable: %age change in EBITCoefficients(a)

Model




1 (Constant)

164.562 292.511 .563 .613

GNP -16.225 40.450 -.226 -.401 .715


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0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb



GNP AND EBIT

-50

0

50

100

150

200

2007 2006 2005 2004 2003

%

ofsales

GNP EBIT

The graph tells the opposite fluctuations among the two variables, indicating weak

relationship.

DAWOOD HERCULES:-

Model Summary (b)



1 .507(a) .257 .009 41.64856


The negative beta value (-.507) tells that the variables are again inversely related. Soapparently there is no relationship between EBIT and GNP.

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.

1 Regression

1797.841 1 1797.841 1.036 .384(a)

Residual 5203.807 3 1734.602

Total 7001.648 4


ANOVA is also unable to build any significant relation between two variables.

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Coefficients(a)

Model




)168.719 156.407 1.079 .360

GNP -22.019 21.629 -.507 -1.018 .384


GNP AND EBIT

-50

0

50

100

150

200

2007 2006 2005 2004 2003

%

ofsale

GNP EBIT

The graph is again oppositely sketched, so no direct relationship of profitability on

GNP.

ENGRO CHEMICALS:-

Model Summary(b)



1 .656(a) .431 .146 12.91730

a Predictors: (Constant), GNPB Dependent Variable: EBIT % age change

Engro is positively correlated with GNP, like in GDP, in term of profitability. Thesignificance is strengthened by large and significant value of F in ANOVA table.

ANOVA (b)

Model

Sum of

Squares df Mean Square F Sig.1 Regressio

n252.638 1 252.638 1.514 .344(a)

Residual 333.713 2 166.857

Total 586.352 3

a Predictors: (Constant), GNPB Dependent Variable: EBIT % age change

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Coefficients (a)

Model




1 (Constant)

-34.191 48.900 -.699 .557

GNP 8.401 6.827 .656 1.230 .344


0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb



GNP AND EBIT

0

5

10

15

20

25

30

35

40

45

2007 2006 2005 2004 2003

%

ofsale

GNP EBIT

The fluctuations in the graph can be noticed. They are along the same proportion,

giving strong relationship between GNP and EBIT.

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LINKAGE OF GROWTH IN REVENUE WITH PROFITABILITY:

H0: Growth in Revenues has no significant effect on

profitability.

FAUJI FERTILIZERS:-

There is very strong relation between growth in revenues and profitability. The large

values of R and adjusted R2 are clear indications that the profits are dependent upon

change in revenues.

Model Summary (b)



1 .682(a) .465 .286 6.53108a Predictors: (Constant), MKT PRICEb Dependent Variable: %age change in EBIT

ANOVA (b)


1 Regression

111.083 1 111.083 2.604 .205(a)

Residual 127.965 3 42.655

Total 239.048 4

a Predictors: (Constant), MKT PRICE


The value of F-stats is also significantly high that we can easily conclude the strongrelationship between the two variables.

Coefficients(a)

Model




1 (Constant)

-20.823 20.352 -1.023 .382

MKTPRICE

.273 .169 .682 1.614 .205


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-1.0 -0.5 0.0 0.5 1.0


0.0

0.5

1.0

1.5

2.0

Frequency

Mean =

Std. De

N = 5


Histogram

0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb




Model Summary(b)



1 .981(a) .963 .950 15.44412

a Predictors: (Constant), GROWTH IN REVENUESb Dependent Variable: %age change in EBIT

Fauji Fertilizer Bin Qasim is also strongly correlated with Revenues in term of profitability, due to very strong R values(98.1%).

ANOVA (b)


1 Regression

18461.536 1 18461.536 77.400 .003(a)

Residual 715.563 3 238.521

Total 19177.099 4

a Predictors: (Constant), GROWTH IN REVENUESb Dependent Variable: %age change in EBIT

Coefficients(a)

Model



t Sig.B Std. Error Beta1 (Constant) 6.433 8.373 .768 .498

GROWTH INREVENUES

1.283 .146 .981 8.798 .003


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0.0 0.2 0.4 0.6 0.8 1.0

Observed Cum Prob

0.0

0.2

0.4

0.6

0.8

1.0

ExpectedCumProb



Growth in ReVenue AND EBIT

-50

0

50

100

150

200

2007 2006 2005 2004 2003

%ofsales

GROWTH IN

REVENUES %EBIT

Looking at the graph, we can see the strong relation between two variables.

DAWOOD HERCULES:-

The profitability of Dawood Hercules is strongly dependent upon the change in

revenues. The R value is high which shows strong correlation.

Model Summary (b)



1 1.000(a) 1.000 1.000 .00000a Predictors: (Constant), GROWTH IN REVENUES %b Dependent Variable: %age change in EBIT

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ANOVA(b)


1 Regressio

n 7001.648 1 7001.648 . .(a)Residual .000 3 .000

Total 7001.648 4

a Predictors: (Constant), GROWTH IN REVENUES %b Dependent Variable: %age change in EBIT

Coefficients(a)

Model




1 (Constant) .000 .000 . .

GROWTHINREVENUES %

1.000 .000 1.000 . .


Growth in revenues AND EBIT

-50

0

50

100

150

200

2007 2006 2005 2004 2003

%

ofsale Growth in

RevenuesEBIT

The graph also tells strong association between profitability and growth in revenues.

ENGRO CHEMICALS:-

Model Summary (b)



1 .278(a) .077 -.384 16.44862

a Predictors: (Constant), Growth in revenuesB Dependent Variable: EBIT % age change

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Though the relationship is direct due to positive values of R and beta, but thestrength is not as high as in the other company case.

ANOVA(b)


1 Regression 45.237 1 45.237 .167 .722(a)

Residual 541.114 2 270.557

Total 586.352 3

a Predictors: (Constant), Growth in revenuesb Dependent Variable: EBIT % age change

The F-value is not as highly significant as in the case of other companies.Coefficients(a)

Model




1 (Constant) 24.120 8.846 2.727 .112Growth inrevenues

.120 .294 .278 .409 .722


-1.5 -1.0 -0.5 0.0 0.5 1.0


0.0

0.5

1.0

1.5

2.0

Frequency

Mean =

Std. De

N = 4


Histogram

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CONCLUSION

The four firms are analyzed in our study of fertilizer sector of Pakistan. We

came with following results.

1. Liquidity has statistically significant positive effect on the profitability of

fertilizer industry.

2. In fertilizer sector, leverage does not significantly affect the profitability

of firm.

3. Average market Price per Share has no significant effect on profitability

of fertilizer industry.

4. Year to year Growth in Revenues has significant effect on the

profitability of firms in Fertilizer Industry of Pakistan

5. GNP of country has significantly positive effect on the profitability of

firms.

6. GDP of Pakistan has statistically significant effect on the profitability of

the firms in Fertilizer Industry of Pakistan.

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KEY FINDINGS

1. After having deep insight of the fertilizer sector, we see that the sectorkeeps high level of liquidity. Because this is a chemical industry, and all

chemical industries keep high liquidity. Because the chemicals used in

the production cannot be acquired once in a year due to their

vulnerability to expire. So they have to buy on regular basis. So their

liquidity is high.

2. We came with another finding, that the current ratio and quick ratios are

almost same. Which simply mean that they dont have high inventory

piled up? That is why; we didnt use the quick ratio along with current

ratio.

3. All over the world, the corporations and financial institutes are moving

toward debt financing to be saved against government taxes. But

contrary to this all, the fertilizer sector in Pakistan is mostly not

depending upon it, as per statistical analysis.

4. The reason for above said implications is simple. The fertilizer sector is a

selling sector like automobile industry. Whatever they produce is must

be sold because of higher demand. So they dont have high level of

receivables, instead they take money in advance. So they dont haveany risk in the business, and the profits are not highly related to the

leverage.

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Corporate Fin Report Final

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