Sir Nadeem r

Upload
gobindram 
Category
Documents

view
227 
download
0
Transcript of Sir Nadeem r

8/3/2019 Sir Nadeem r
1/38
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:
4. Fouji Fertilizer Company Limited (FFCL)
5. Engro Chemicals Pakistan Limited (Engro)
6. Fouji Fertilizer Bin Qasim Limited (FFBL)
7. Dawood Hercules Chemicals Limited (DHCL)
Research Topic:
Linkage of following financial and economic indicators with
profitability of Fertilizer sector in Pakistan;
8. Liquidity (Current Ratio & Quick Ratio)
9. Leverage
10.Market Price Per Share
11.Year to Year Growth In Revenues
12.GDP
13.GNP
Theories about Profitability:
"Perhaps no term or concept in economic discussion is used with a morebewildering variety of well established meanings than profit."
Frank Knight (1934, p, 480).

8/3/2019 Sir Nadeem r
2/38
In a noninflationary world of family firms using oneperiod capital inputs withno taxes or debt, measuring profit would be a relatively straightforwardmatter of deducting expenses from receipts. The accountant's books and theeconomist's books would coincide. But in the presence of longlived assets ofvarious maturities, price changes, debt financing, and taxation, the two bookkeeping systems diverge and researchers face some difficult questions.
Should profittype income include net interest payments? How holding gainson real assets or on net financial liabilities should be treated? Shouldprofitability be measured on gross capital stock (including depreciation in thenumerator) or net stock (excluding depreciation), and indeed are averageaccounting rates of profit meaningful at all?Tradeoff theory of capital structure basically entails offsetting the costs ofdebt against the benefits of debt. MM 1963 introduced the tax benefit ofdebt. Later work led to an optimal capital structure which is given by thetrade off theory. The first element usually considered as the cost of debt isusually the financial distress costs or bankruptcy costs of debt. It is importantto note that this includes the direct and indirect bankruptcy costs.
Tradeoff theory can also include the agency costs from agency theory as acost of debt to explain why companies dont have 100% debt as expectedfrom MM 1963. 95% of empirical papers in this area of study look at theconflict between managers and shareholders. The others look at conflictsbetween debt holders and shareholders. Both are equally important toexplain how the agency theory is related to the tradeoff 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 of leverage. Element of financial risk is high in highly leveragedcompanies as compared to low leveraged companies. Equity holders are tobe rewarded with a higher financial premium in case of highly gearedcompanies. The more the leveraged firm, more the profits are related to itaccording 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 companies with low profits. So it is perceived

8/3/2019 Sir Nadeem r
3/38
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 & Profitability
It 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, IMFapproved
government policies, bolstered by generous foreign assistance and renewedaccess 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 arelatively balanced economy based on services, industry and agriculture. Asof FY07, agriculture contributed 20% to the overall GDP. The governmentpolicies are directed towards improvement of agricultural output throughincreased credit disbursements to the agricultural sector and improvement inirrigation.
Fertilizer usage in Pakistan is low and the current fertilizer consumptionstands at 162.5kg per hectare. This is in large part responsible for the lowyield per hectare of cultivated land which stands at 1.44tn per hectare.Fertilizer consumption closely follows economic growth of the country asexhibited by the strong positive correlation (R2=0.9841) between fertilizerconsumption per hectare and nominal GDP. As the economy is expected toperform well in the future with an estimated nominal GDP growth of 14%, weexpect fertilizer penetration to increase to 187kg per hectare. This greaterdemand is expected to continue in the future as economic growth continues.
The industry capacity currently stands at 5.8mntpa whereas local demand is

8/3/2019 Sir Nadeem r
4/38
6.8mntpa. This excessive demand ensures sales of total production.Pakistans fertilizer manufacturers have low resource costs due to feedstockgas subsidy advanced by the government. Through this subsidymanufacturers are able to get feed stock gas at significantly lower rates thanthe market which improves their profitability. This subsidy is expected toremain in place at least for the next three to four years i.e. until the industry
faces an excess supply situation. Later on the subsidy may be withdrawnfrom that portion of production which is exported. Production directedtowards local sales is expected to continue receiving the subsidy. TheCompanies in our coverage are dominant players who hold attractiveinvestment portfolios. This includes FFCs investments in FFBL and ENGROsinvestments in various subsidiaries.
Types of fertilizer
Urea, which represents 65% of total fertilizer consumed and diammoniumphosphate (DAP), which accounts for 18%, are the main types of fertilizerused in Pakistan, but there is a total of eight different fertilizer productswhich fall into three categories.
Urea, along with calcium ammonium nitrate (CAN) and ammonium sulphate(AS) together make up almost three fourths of total fertilizer consumptionand come under the nitrogenous category. Under the phosphatic categorywhich makes up about 27%, is DAP, triple super phosphate (TSP), singlesuper phosphate (SSP) and nitrophosphate (NP). And under the last category,potassic is sulphate of potash which makes up only 1%.
Since the soil in Pakistan generally tends to be deficient in nitrogen, urea isthe most used fertilizer. DAP is used, as most phosphatic fertilizers are tocounter the effect of the acidic urea and maintain levels of fertility in the soil.
Pakistans agricultural output has suffered in the recent past due to adverse
weather conditions and crop spoilage. The government is omitted to improveagriculture performance 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 it stands at 1.44tn per hectare.
Statistical AnalysisHYPOTHESIS TESTING
H0: Liquidity, measured by current ratio has no significant
effect on profitability.

8/3/2019 Sir Nadeem r
5/38
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 coefficient of determination(R=76%) indicates strong relationship between the two variables. Also looking at related
graph, we find upward 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 DurbinWatson
1 .760(a) .577 .436 5.80487 2.227

8/3/2019 Sir Nadeem r
6/38
a Predictors: (Constant), Current Ratio
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 = 1.28E15
Std. Dev. = 0.866
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 theheight of strength is not as much as for others. DW 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 DurbinWatson
1 .627(a) .393 .190 62.30031 2.805
a Predictors: (Constant), Current Ratiob Dependent Variable: %age change in EBIT

8/3/2019 Sir Nadeem r
7/38
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 = 9.44E16
Std. Dev. = 0.866
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
ExpectedC
umProb
Dependent Variable: %age change in EBIT
Normal PP Plot of Regression Standardized Residual
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
Dawood Hercules. We also ran regression and Fstats 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)

8/3/2019 Sir Nadeem r
8/38
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate DurbinWatson
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.
Regression
901.015 1 901.015 .443 .553(a)
Residual 6100.633 3 2033.544
Total 7001.648 4
a Predictors: (Constant), Current Ratiob Dependent Variable: %age change in EBIT
Coefficients(a)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(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 = 8.33E17
Std. Dev. = 0.866
N = 5
Dependent Variable: %age change in EBIT
Histogram

8/3/2019 Sir Nadeem r
9/38
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 PP 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
ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
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

8/3/2019 Sir Nadeem r
10/38
Coefficients(a)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(Constan
t)
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
Expected
CumProb
Dependent Variable: EBIt % age change
Normal PP Plot of Regression Standardized Residual
LINKAGE OF LEVERAGE WITH PROFITABILITY
FAUJI FERTILIZERS:
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 DurbinWatson
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 wedont see any strong relation between profitability and leverage. But positivevalue of beta (.486) tells that an upward slope exist between variables, so at

8/3/2019 Sir Nadeem r
11/38
least they have connection.
Coefficients
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta(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
Frequenc
y
Mean = 5.55E16
Std. Dev.= 0.866
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 PP Plot of Regression Standardized Residual
FAUJI FERTILIZERS BIN QASIM LIMITED:
Model Summary
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate DurbinWatson
1 .808(a) .653 .538 .81198 1.708
a Predictors: (Constant), EBIT %age change

8/3/2019 Sir Nadeem r
12/38
b Dependent Variable: Leverage %
The negative value of beta (0.808) in the following table indicates an inverserelationship between debt and profitability. The results are surprising in thisindustry. There are some valid reasons for this, we will discuss them later. Soeven the theory is opposite to it, but there is no dependence of profitabilityon leverage.
Coefficients
UnstandardizedCoefficients
StandardizedCoefficients 95% Confidence Interval fo
B Std. Error Beta Lower Bound Upper Bo
(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
Frequ
ency
Mean = 2.1E14
Std. Dev. = 0.866
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
ExpectedCumPr
ob
Dependent Variable: Levergae %
Normal PP Plot of Regression Standardized Residual
DAWOOD HERCULES:
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate DurbinWatson1 .535(a) .287 .049 40.80494 2.634
a Predictors: (Constant), leverage%b Dependent Variable: %age change in EBIT
Following table of coefficients shows a negative beta (0.535), which meanthe debt and profitability are oppositely related. Because there is no positiverelation between two variables, discussion of strength of correlation isuseless.
Coefficients

8/3/2019 Sir Nadeem r
13/38
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(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
Fre
quency
Mean = 2.5E16
Std. Dev. = 0.866
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.
Regression
39.979 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 leverageand profitability. Engros profits are related to debt, though not strongly.
There are very low values of R2 and a negative value of adjusted R2, whichmean that the correlation is weak.
Coefficients(a)
UnstandardizedCoefficients
StandardizedCoefficients

8/3/2019 Sir Nadeem r
14/38
B Std. Error Beta
(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 isreally weak. The answer is, yes. This is due to the low Fvalue, which is notsignificant for the 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 = 5.55E17
Std. Dev.= 0.816
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
ExpectedC
umProb
Dependent Variable: EBIt % age change
Normal PP Plot of Regression Standardized Residual
INDUSTRY ANALYSIS AND
HYPOTHESIS TESTING
H0: Liquidity, measured by current ratio has no
significant effect on profitability.
TEST OF ASSOCIATION USING CHI SQUARE:
ChiSquare Tests
Value Df Asymp. Sig.(2sided)
Pearson ChiSquare 304.000(
a) 289 .261Likelihood Ratio 106.344 289 1.000LinearbyLinearAssociation
.046 1 .830
N of Valid Cases19
a 324 cells (100.0%) have expected count less than 5. The minimum expected count is .05.
Results:

8/3/2019 Sir Nadeem r
15/38
Pearson chi square test rejects the above described null hypothesis.
0.94 0 .9 0.9 1 1 .07 1.0 4 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 .5 4
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 1 3 14 15 16 17 18 19
EBIT % age change
CurrentRatio
]Curre
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.
Regression
80.414 1 80.414 .043 .837(a)
Residual 31481.866
17 1851.874
Total 31562.280
18
a Predictors: (Constant), Current Ratio

8/3/2019 Sir Nadeem r
16/38
b Dependent Variable: %age change in EBIT
Results:
Running simple regression on the fertilizer industry, the hypothesis isrejected, due to insignificant value of Fstats.
Thus we can interpret that the fertilizer sectors profitability is dependent
upon liquidity measured by current ratio.Coefficients(a)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(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 = 1.13E16
Std. Dev. = 0.972
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
ExpectedC
umProb
Dependent Variable: %age change i n EBIT
Normal PP Plot of Regression Standardized Residual

8/3/2019 Sir Nadeem r
17/38
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 1 2 13 14 15 16 17 18 19 2 0
LEVERAGE%
EBIT%C
hange
EBIT %
REGRESSION ANALYSIS:

8/3/2019 Sir Nadeem r
18/38
Coefficients(a)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(Constan
t)
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 increasingthe profitability.
2 1 0 1 2 3 4
Regression Standardized Residual
0
1
2
3
4
5
6
7
Frequency
Mean = 1.39E17
Std. Dev. = 0.972
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 PP Plot of Regression Standardized Residual
Results:
The regression and chi square tests conclude that the fertilizer industry has
positive association 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

8/3/2019 Sir Nadeem r
19/38
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.
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)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(Constant) 36.787 30.843 1.193 .355
Market priceper share
.062 .163 .260 .381 .740
a Dependent Variable: EBIT % age change

8/3/2019 Sir Nadeem r
20/38
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 = 1.94E16
Std. Dev.= 0.816
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 PP Plot of Regression Standardized Residual
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

8/3/2019 Sir Nadeem r
21/38
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 8.62542a Predictors: (Constant), GDPb Dependent Variable: %age change in EBIT
ANOVA table shows that the significance of relation is very weak.
ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
Regressi
on
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)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(Constant)
2.778 19.665 .141 .897
GDP 1.279 2.771 .258 .462 .676a 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 = 1.25E16
Std. Dev.= 0.866
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
Ex
pectedCumProb
Dependent Variable: %age change in EBIT
Normal PP Plot of Regression Standardized Residual
The trend can be seen from the graph above, that GDP is an indicator of
increasing profits.

8/3/2019 Sir Nadeem r
22/38

8/3/2019 Sir Nadeem r
23/38
Model Summary(b)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .302(a) .091 .212 46.05497
a Predictors: (Constant), GDP
b Dependent Variable: %age change in EBITDawood Hercules has a positive and greater value of beta than that ofprevious. Mean there is positive slope between GDP and profitability ofDawood Hercules.
ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
Regression
638.467 1 638.467 .301 .621(a)
Residual 6363.181 3 2121.060
Total 7001.648 4
a Predictors: (Constant), GDP
b 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)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(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
E
xpectedCumProb
Dependent Variable: %age change in EBIT
Normal PP Plot of Regression Standardized Residual

8/3/2019 Sir Nadeem r
24/38
GDP AND EBIT
50
0
50
100
150
200
2007 2006 2005 2004 2003
%
ofsa
le
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:
Engro Chemicals is strongly correlated with GDP. The very high value of Rand 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 significantlylarge indicating strong relationship between profitability and GDP.
ANOVA (b)
ModelSum of Squares Df Mean Square F Sig.
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)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(Constant)
61.659 35.255 1.749 .222

8/3/2019 Sir Nadeem r
25/38
GDP 11.576 4.651 .869 2.489 .131
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 PP Plot of Regression Standardized Residual
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 the relation is inverse between the two variables.
Model Summary(b)

8/3/2019 Sir Nadeem r
26/38
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 .070(a) .005 .327 8.90487
a Predictors: (Constant), GNPb Dependent Variable: %age change in EBIT
ANOVA table also does not give any strong relation between two variables asthe F value is very low.ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
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)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(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

8/3/2019 Sir Nadeem r
27/38
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 i n EBIT
Normal PP Plot of Regression Standardized Residual
The insignificance can be seen in the above graph between EBIT and GNP, for
Fouji Fertilizer.
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.
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 Fvalue, indicating no significant relationbetween two variables.
ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
Regression
976.137 1 976.137 .161 .715(a)
Residual 18200.962
3 6066.987
Total 19177.099
4
a Predictors: (Constant), GNPb Dependent Variable: %age change in EBIT
Coefficients(a)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(Constant)
164.562 292.511 .563 .613
GNP 16.225 40.450 .226 .401 .715

8/3/2019 Sir Nadeem r
28/38
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 PP Plot of Regression Standardized Residual
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 inverselyrelated. So apparently there is no relationship between EBIT and GNP.
ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
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

8/3/2019 Sir Nadeem r
29/38
ANOVA is also unable to build any significant relation between two variables.
Coefficients(a)
Unstandardized
Coefficients
Standardized
Coefficients
B Std. Error Beta
(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.The significance is strengthened by large and significant value of F in ANOVAtable.
ANOVA (b)
ModelSum of Squares df Mean Square F Sig.
Regression
252.638 1 252.638 1.514 .344(a)
Residual 333.713 2 166.857
Total 586.352 3
a Predictors: (Constant), GNP

8/3/2019 Sir Nadeem r
30/38
B Dependent Variable: EBIT % age change
Coefficients (a)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(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 PP Plot of Regression Standardized Residual
GNP AND EBIT
0
5
10
15
20
25
30
35
40
45
2007 2006 2005 2004 2003
%ofsales
GNP EBIT
The fluctuations in the graph can be noticed. They are along the same

8/3/2019 Sir Nadeem r
31/38
proportion, giving strong relationship between GNP and EBIT.
LINKAGE OF GROWTH IN REVENUE WITHPROFITABILITY:
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 6.53108
a Predictors: (Constant), MKT PRICEb Dependent Variable: %age change in EBIT
ANOVA (b)
Model
Sum of
Squares df Mean Square F Sig.Regression
111.083 1 111.083 2.604 .205(a)
Residual 127.965 3 42.655
Total 239.048 4
a Predictors: (Constant), MKT PRICEb Dependent Variable: %age change in EBIT
The value of Fstats is also significantly high that we can easily conclude thestrong relationship between the two variables.
Coefficients(a)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(Constant)
20.823 20.352 1.023 .382
MKTPRICE
.273 .169 .682 1.614 .205
a Dependent Variable: %age change in EBIT

8/3/2019 Sir Nadeem r
32/38
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 = 6.66E16
Std. Dev. = 0.866
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 PP Plot of Regression Standardized Residual
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 strongR values (98.1%).
ANOVA (b)
ModelSum of Squares df Mean Square F Sig.
Regression
18461.536
1 18461.536 77.400 .003(a)
Residual 715.563 3 238.521

8/3/2019 Sir Nadeem r
33/38
Total 19177.099
4
a Predictors: (Constant), GROWTH IN REVENUESb Dependent Variable: %age change in EBIT
Coefficients(a)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(Constant) 6.433 8.373 .768 .498
GROWTH INREVENUES
1.283 .146 .981 8.798 .003
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 PP Plot of Regression Standardized Residual
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.

8/3/2019 Sir Nadeem r
34/38
Model Summary (b)
Model R R SquareAdjusted RSquare
Std. Error ofthe Estimate
1 1.000(a) 1.000 1.000 .00000
a Predictors: (Constant), GROWTH IN REVENUES %
b Dependent Variable: %age change in EBIT
ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
Regression 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)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(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
%ofsales Growth in
RevenuesEBIT

8/3/2019 Sir Nadeem r
35/38
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
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.
Regressi
on 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 Fvalue is not as highly significant as in the case of other companies.Coefficients(a)
UnstandardizedCoefficients
StandardizedCoefficients
B Std. Error Beta
(Constant)24.120 8.846 2.727 .112Growth in
revenues.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 = 2.78E17
Std. Dev. = 0.816
N = 4
Dependent Variable: EBIt % age change
Histogram

8/3/2019 Sir Nadeem r
36/38
CONCLUSION
The four firms are analyzed in our study of fertilizer sector of Pakistan.
We came with following results.
14.Liquidity has statistically significant positive effect on the
profitability of fertilizer industry.
15.In fertilizer sector, leverage does not significantly affect the
profitability of firm.
16.Average market Price per Share has no significant effect on
profitability of fertilizer industry.
17.Year to year Growth in Revenues has significant effect on the
profitability of firms in Fertilizer Industry of Pakistan
18.GNP of country has significantly positive effect on the
profitability of firms.
19.GDP of Pakistan has statistically significant effect on the
profitability of the firms in Fertilizer Industry of Pakistan.

8/3/2019 Sir Nadeem r
37/38
KEY FINDINGS
20.After having deep insight of the fertilizer sector, we see that the
sector keeps high level of liquidity. Because this is a chemical
industry, and all chemical industries keep high liquidity. Becausethe 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.
21.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.
22.All over the world, the corporations and financial institutes aremoving 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.
23.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 have any risk in the business, and the
profits are not highly related to the leverage.

8/3/2019 Sir Nadeem r
38/38
REFERENCES:
http://wiki.answers.com
www.levy.org/pubs
www.engro.com
www.ffc.com.pk
www.ffbl.com
www.dawoodhercules.com
www.sbp.org.pk
www.fertilizer.org
www.pakistaneconomist.com
www.allbusiness.com
www.goliath.ecnext.com