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.
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate Durbin-Watson
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
Dependent Variable: %age change in EBIT
Normal P-P Plot of Regression Standardized Residu
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-1.0 -0.5 0.0 0.5 1.0 1.5
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
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate Durbin-Watson
1 .359(a) .129 -.162 45.09484 3.288
a Predictors: (Constant), Current Ratiob Dependent Variable: %age change in EBIT
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
Dependent Variable: %age change in EBIT
Normal P-P Plot of Regression Standardized Residu
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Residual 6100.633 3 2033.544
Total 7001.648 4
a Predictors: (Constant), Current Ratiob Dependent Variable: %age change in EBIT
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
Regression Standardized Residual
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
Dependent Variable: %age change in EBIT
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)
Model R R SquareAdjusted RSquare
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
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
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
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate Durbin-Watson
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
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
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
Regression Standardized Residual
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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Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate Durbin-Watson
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
Regression Standardized Residual
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 %
Normal P-P Plot of Regression Standardized Residu
DAWOOD HERCULES:-
Model Summary
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate Durbin-Watson
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
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
1 (Constant)
81.926 67.470 1.214 .312
leverage%
-2.574 2.345 -.535 -1.098 .353
a Dependent Variable: %age change in EBIT
-1.0 -0.5 0.0 0.5 1.0 1.5
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
ENGRO CHEMICALS:-
Model Summary(b)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .261(a) .068 -.398 16.52835
a Predictors: (Constant), Leverageb Dependent Variable: EBIT % age change
ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
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
UnstandardizedCoefficients
StandardizedCoefficients
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
Regression Standardized Residual
0.0
0.2
0.4
0.6
0.8
1.0
Frequency
Mean =
Std. De
N = 4
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 Residu
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .050(a) .003 -.056 43.03341
a Predictors: (Constant), Current Ratiob Dependent Variable: %age change in EBIT
ANOVA(b)
ModelSum of Squares Df Mean Square F Sig.
1 Regression
80.414 1 80.414 .043 .837(a)
Residual 31481.866 17 1851.874
Total 31562.280 18
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a Predictors: (Constant), Current Ratiob Dependent Variable: %age change in EBIT
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
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
1 (Constant) 28.480 24.197 1.177 .255
CurrentRatio
-3.035 14.565 -.050 -.208 .837
a Dependent Variable: %age change in EBIT
-2 -1 0 1 2 3 4
Regression Standardized Residual
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
UnstandardizedCoefficients
StandardizedCoefficients
T Sig.B Std. Error Beta
1 (Constant) 4.153 26.130 .159 .876
Leverage%
.426 .524 .193 .813 .428
a Dependent Variable: %age change in EBIT
Result:
We shall reject the null hypothesis. So the leverage is significant in increasing theprofitability.
-2 -1 0 1 2 3 4
Regression Standardized Residual
0
1
2
3
4
5
6
7
Frequency
Mean =
Std. De
N = 19
Dependent Variable: %age change in EBIT
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 EBIT
Normal P-P Plot of Regression Standardized Residu
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .260(a) .068 -.398 16.53155
Predictors: (Constant), Market price per shareB Dependent Variable: EBIT % age change
ANOVA (b)
ModelSum of Squares Df Mean Square F Sig.
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
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
1 (Constant) 36.787 30.843 1.193 .355
Market priceper share
-.062 .163 -.260 -.381 .740
a Dependent Variable: EBIT % age change
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-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 = 4
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 Residu
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
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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ModelSum of Squares df Mean Square F Sig.
1 Regression
15.854 1 15.854 .213 .676(a)
Residual 223.194 3 74.398
Total 239.048 4
a Predictors: (Constant), GDPb Dependent Variable: %age change in EBIT
Coefficients(a)
Model
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
1 (Constant)
2.778 19.665 .141 .897
GDP 1.279 2.771 .258 .462 .676
a Dependent Variable: %age change in EBIT
-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5
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
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 EBIT
Normal P-P Plot of Regression Standardized Residu
The trend can be seen from the graph above, that GDP is an indicator of increasing
profits.
FAUJI FERTILIZERS BIN QASIM:-
Model Summary(b)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .204(a) .041 -.278 78.27698
a Predictors: (Constant), GDPb Dependent Variable: %age change in EBIT
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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ModelSum of Squares df Mean Square F Sig.
1 Regression
795.240 1 795.240 .130 .743(a)
Residual 18381.858 3 6127.286
Total 19177.099 4
a Predictors: (Constant), GDPb Dependent Variable: %age change in EBIT
Coefficients(a)
Model
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
1 (Constant)
-14.979 178.466 -.084 .938
GDP 9.058 25.144 .204 .360 .743
a Dependent Variable: %age change in EBIT
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 EBIT
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .302(a) .091 -.212 46.05497
a Predictors: (Constant), GDPb Dependent Variable: %age change in EBIT
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)
ModelSum of Squares df Mean Square F Sig.
1 Regression
638.467 1 638.467 .301 .621(a)
Residual 6363.181 3 2121.060
Total 7001.648 4
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a Predictors: (Constant), GDPb Dependent Variable: %age change in EBIT
The value of F is not so significant that we can conclude a strong relationshipbetween the two variables.
Coefficients(a)
Model
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
1 (Constant)
-45.870 105.002 -.437 .692
GDP 8.116 14.793 .302 .549 .621
a Dependent Variable: %age change in EBIT
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 EBIT
Normal P-P Plot of Regression Standardized Residu
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
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)
ModelSum of Squares Df Mean Square F Sig.
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
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
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
Dependent Variable: EBIt % age change
Normal P-P Plot of Regression Standardized Residu
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .070(a) .005 -.327 8.90487
a Predictors: (Constant), GNP
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b Dependent Variable: %age change in EBIT
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
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta1 (Constant
)15.692 33.441 .469 .671
GNP -.559 4.624 -.070 -.121 .911
a Dependent Variable: %age change in EBIT
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
Dependent Variable: %age change in EBIT
Normal P-P Plot of Regression Standardized Residua
The insignificance can be seen in the above graph between EBIT and GNP, for FoujiFertilizer.
FAUJI FERTILIZERS BIN QASIM:-
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .226(a) .051 -.265 77.89087
a Predictors: (Constant), GNP
b Dependent Variable: %age change in EBIT
ANOVA table gives very low F-value, indicating no significant relation between twovariables.
ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
1 Regression
976.137 1 976.137 .161 .715(a)
Residual 18200.962 3 6066.987
Total 19177.099 4
a Predictors: (Constant), GNP
b Dependent Variable: %age change in EBITCoefficients(a)
Model
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
1 (Constant)
164.562 292.511 .563 .613
GNP -16.225 40.450 -.226 -.401 .715
a Dependent Variable: %age change in EBIT
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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
Dependent Variable: %age change in EBIT
Normal P-P Plot of Regression Standardized Residu
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .507(a) .257 .009 41.64856
a Predictors: (Constant), GNPb Dependent Variable: %age change in EBIT
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
a Predictors: (Constant), GNPb Dependent Variable: %age change in EBIT
ANOVA is also unable to build any significant relation between two variables.
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Coefficients(a)
Model
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta1 (Constant
)168.719 156.407 1.079 .360
GNP -22.019 21.629 -.507 -1.018 .384
a Dependent Variable: %age change in EBIT
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
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
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
1 (Constant)
-34.191 48.900 -.699 .557
GNP 8.401 6.827 .656 1.230 .344
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 Residu
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .682(a) .465 .286 6.53108a Predictors: (Constant), MKT PRICEb Dependent Variable: %age change in EBIT
ANOVA (b)
ModelSum of Squares df Mean Square F Sig.
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
b Dependent Variable: %age change in EBIT
The value of F-stats is also significantly high that we can easily conclude the strongrelationship between the two variables.
Coefficients(a)
Model
UnstandardizedCoefficients
StandardizedCoefficients
T Sig.B Std. Error Beta
1 (Constant)
-20.823 20.352 -1.023 .382
MKTPRICE
.273 .169 .682 1.614 .205
a Dependent Variable: %age change in EBIT
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-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
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 EBIT
Normal P-P Plot of Regression Standardized Residu
FAUJI FERTILIZERS BIN QASIM:-
Model Summary(b)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
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)
ModelSum of Squares df Mean Square F Sig.
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
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta1 (Constant) 6.433 8.373 .768 .498
GROWTH INREVENUES
1.283 .146 .981 8.798 .003
a Dependent Variable: %age change in EBIT
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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
Dependent Variable: %age change in EBIT
Normal P-P Plot of Regression Standardized Residu
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
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)
ModelSum of Squares df Mean Square F Sig.
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
UnstandardizedCoefficients
StandardizedCoefficients
T Sig.B Std. Error Beta
1 (Constant) .000 .000 . .
GROWTHINREVENUES %
1.000 .000 1.000 . .
a Dependent Variable: %age change in EBIT
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)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
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)
ModelSum of Squares df Mean Square F Sig.
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
UnstandardizedCoefficients
StandardizedCoefficients
t Sig.B Std. Error Beta
1 (Constant) 24.120 8.846 2.727 .112Growth inrevenues
.120 .294 .278 .409 .722
a Dependent Variable: EBIT % age change
-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 = 4
Dependent Variable: EBIt % age change
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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