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TERM
RESEARCH REPORT
INFLUENCE OF WORKING CAPITAL MANAGEMENT
ON PROFITABILITY OF PACKAGING SECTOR
FIRMS IN PAKISTAN
TERM REPORT
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Date: 3rd Jan 2011
Submitted To:
Mr. Jamal Zubairi
Course Instructor: Corporate Finance
Submitted by:
Ali Azhar (5522) (MOB: 0333-321-7763)
Sami ahmad vohra (7167) (MOB: 0321-820-9793)
Mohsin shahid (5505) (MOB: 0333-209-6789)
Syed Kamran (9248) (MOB: 0332-302-4054)
Sohaib Rasool (9076) (MOB: 0300-306-7654)
Letter of Transmittal
January 3rd 2011
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Mr. Jamal Zubairi
Professor
Institute of Business Management
Korangi Creek
Karachi
Respected sir,
Attached is the term report on Influence of working capital
management on profitability of packaging sector firms in
Pakistan. This report has been prepared with utmost responsibility
and honesty.
We have conducted various tests in order to determine the relationship
of profitability with different ratios of packaging industry of Pakistan.
We are confident that results of these tests would be helpful to identify
relationship, if any, between profitability and different ratios.
We are grateful to you for giving us a chance to conduct this research
which proved to be very informative and a learning experience for all
of us.
Sincerely,
Ali Azhar
Sami AhmedMohsin Shahid
Sohaib Rasool
Kamran Ahmed
ABSTRACT
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This paper investigates how profitability of firms, in the packaging
sector of Pakistan, is influenced by working capital management. To
examine this, various Liquidity ratios and Asset turn over ratios have
been conducted. Liquidity ratios were taken as benchmark for working
capital management. Incremental analysis was also undertaken to
evaluate the impact of Asset turn over on profitability. Using linear
Regression Models and statistical analysis, the rationale of the study
was to determine empirically, the existence of any relationships
between Profitability and Liquidity-Asset turnover ratios.
I. INTRODUCTION
Working capital along with fixed assets is considered part of
operating liquidity. Working capital is a financial gauge whichrepresents operating liquidity available to firms. If current liabilities are
more than current assets, firm has a working capital deficiency,
also called as working capital deficit.
A profitable company can be endowed with assets but short of liquidity
if its assets cannot readily be converted into cash. To ensure smooth
operations, firm is required to have positive working capital and that it
has sufficient funds to satisfy both maturing short-term debt and
upcoming operational expenses. The management of working capital
involves managing account receivables, payables, cash andinventories.
Current ratio determines the firm's ability to pay off its short term
obligations with available current assets. In theory, higher the current
ratio of the firm better will be the liquidity position. The current ratio is
a good tool to evaluate firm's liquidity but sometimes its misleading
too as it takes times to turn current asset into cash which can be vary
from company to company.
Quick ratio is more conservative than current ratio as it does notinclude inventories which can sometimes be difficult to liquidate.
Although the quick ratio better evaluate companys ability to meet
current obligations then current ratio. As the inventories of undertaken
firms are not extremely liquid, so a concern of theorist for not taking it
as a measure is negligible.
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Cash conversion cycle is a gauge that measures the period, in days,
that company takes to convert its resources into cash flows. It
attempts to measure the amount of time each net rupee is tied up in
the production and sales process before it is converted into cash
through sales to customers.
The rationale of the study is to find out the influence of working capital
management on profitability of packaging industry of Pakistan. The
empirical findings of the study are based on panel data of packaging
companies listed on the Karachi Stock Exchange from the year 2004 to
year 2009.
II. BACKGROUND OF PAKISTAN'S PACKAGING
INDUSTRY
According to survey, there are more than 210 firms directly or
indirectly associated with packaging industry in Pakistan. The demand
to fulfill the space is not over yet as the technology up-gradation in
firms continue to endeavor and competitive advantage over other
neighboring countries have not achieved yet. In addition the upcoming
years poses stiff challenges for the Pakistani industry in the wake of
rising costs of production due to high raw material costs as well as
other costs directly attributable to energy and general overheads. This
is primarily due to high level of inflation prevailing in the economy, a
fast depreciating rupee and a sharp increase in interest rates all
hampering industry's ability to optimize their profits thorough cost
minimization.
Packaging materials are integral to numerous industries. Perhaps the
industry in which these materials play the most important role is the
food industry and pharmaceutical industry. Food packaging contains
and preserves food items, as well as communicates vital information to
the consumers. For the longest time, glass and plastic containers were
the main products used for packaging.
Glass is one of the oldest packaging materials in history. There is
minimal reaction between glass and the environmental factors
surrounding it. This is because of the immobile state of the product,
which is also the reason why it is an effective packaging material.
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Whatever is stored inside the glass container is sheltered from oxygen,
moisture, organisms, insects and small animals, and harmful light.
The plastic packaging industry is one of the fastest-growing fields in
commerce. There is a high demand for plastic-based packaging
containers in businesses across the globe. The onset and subsequentboom of the online shopping industry is one of the reasons behind the
materials increasing popularity. Plastic is a very popular packaging
material because of its durability and convenience. It also weighs less
than the previously discussed packaging material. The product is also
an effective sealant for food items. On the other hand, the use of
plastic has disadvantages as well. The flavor of the food can cling to
the packaging and thus, become less tasteful. Compound transfer is
also possible between the plastic packaging and the contained item.
Paper is the most environmentally-friendly packaging material. Themost popular form of paper packaging is the corrugated cardboard
which is used to make transport boxes. Although paper does not
provide protection from oxygen, moisture and micro-organisms, it is
incredibly lightweight and cheap to produce. It also benefits the
environment because the production process is not as damaging as
that of plastic.
III. LITERATURE REVIEW
A firm is required to maintain a balance between liquidity andprofitability while conducting its day to day operations. Liquidity is a
precondition to ensure that firms are able to meet its short-term
obligations and its continued flow can be guaranteed from a profitable
venture. The importance of cash as an indicator of continuing financial
health should not be surprising in view of its crucial role within the
business. This requires that business must be run both efficiently and
profitably. In the process, an asset-liability mismatch may occur which
may increase firms profitability in the short run but at a risk of its
insolvency.(for e.g see Gitman, 1984 and Bhattacharya, 2001)
While the performance levels of small businesses have traditionally
been attributed to general managerial factors such as manufacturing,
marketing and operations, working capital management may have a
consequent impact on small business survival and growth (Kargar and
Blumenthal, 1994). The management of working capital is important to
the financial health of businesses of all sizes. The amounts invested in
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working capital are often high in proportion to the total assets
employed and so it is vital that these amounts are used in an efficient
and effective way. However, there is evidence that small businesses
are not very good at managing their working capital. Given that many
small businesses suffer from under capitalisation, the importance of
exerting tight control over working capital investment is difficult to
overstate.
IV. Variables Description, Methodology, and
Sample
SAMPLEAND SOURCESOF DATAThe study has been focused on the Packaging Industry of Pakistan. Six
firms are listed on the Karachi Stock Exchange (KSE) and we selectedfour for our study. The study uses the financial data from the year
2004 to 2009. Hence, we have 300 observations, which would
reasonably explain Profitability.
LIMITATIONSOFTHESTUDYInitially, we were trying to get the financial data of all the companies.
But, due to the unavailability of financial information of some
companies, we were only able to take only four companies into
consideration.
VARIABLES
Two Dependent and ten Independent variables have been taken.
DEPENDENT VARIABLES:
Return on Assets (Measure of Profitability): An indicator of how
profitable a company is relative to its total assets. ROA gives an
idea as to how efficient management is at using its assets to generate
earnings. Calculated by dividing a company's annual earnings by itstotal assets, ROA is displayed as a percentage.
Return on Equity (Measure of Profitability: The amount of net
income returned as a percentage of shareholders equity. Return on
equity measures a corporation's profitability by revealing how
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much profit a company generates with the money shareholders have
invested.
INDEPENDENT VARIABLES:
Current Ratio: A liquidity ratio that measures a company's ability to
pay its short-term obligations. The current ratio can give a sense of the
efficiency of a company's operating cycle or its ability to turn its
product into cash.
Quick Ratio: An indicator of a company's short-term liquidity. The quick
ratio measures a company's ability to meet its short-term obligationswith its most liquid assets. Higher the quick ratio, the better the
position of the company.
Average Collection Period: The approximate amount of time that it
takes for a business to receive payments owed, in terms of
receivables, from its customers and clients.
Days Sales in Inventory: A financial measure of a company's
performance that gives investors an idea of how long it takes a
company to turn its inventory (including goods that are work in
progress, if applicable) into sales.
Accounts Payable Turnover in Days: The cash conversion cycle attempts
to measure the amount of time each net input dollar is tied up in the
production and sales process before it is converted into cash through
sales to customers. This metric looks at the amount of time needed to
sell inventory, the amount of time needed to collect receivables and
the length of time the company is afforded to pay its bills without
incurring penalties.
Cash Conversion Cycle: A metric that expresses the length of time, indays, that it takes for a company to convert resource inputs into cash
flows. The cash conversion cycle attempts to measure the amount of
time each net input dollar is tied up in the production and sales
process before it is converted into cash through sales to customers.
This metric looks at the amount of time needed to sell inventory, the
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amount of time needed to collect receivables and the length of time
the company is afforded to pay its bills without incurring penalties.
ECONOMETRIC MODELS
For more precise results, we have categorized the econometric model
depending upon the relevancy of given variables into these stated
models
MODEL 1
PF = 0 + 1CR + 2QR + 3 ACP + 4DSI + 5 APT +
6CCC + where ROA is dependent variable
MODEL 2
PF = 0 + 1CR + 2QR + 3 ACP + 4DSI + 5 APT +
6CCC + where ROE is dependent variable
MODEL 3
PF = 0 + 1CATA + 2CLTA + 3 ICA + 4 ARCA +
where ROA is dependent variable
MODEL 4
PF = 0 + 1CATA + 2CLTA + 3 ICA + 4 ARCA +
where ROE is dependent variable
V. HYPOTHESISANDRESULTSOFSTATISTICALANALYSIS
Tabele-1 Descriptive Statistics
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Table-1 shows descriptive statistics of given variables. Descriptiveanalysis has been conducted to show average, maximum and
minimum and standard deviation of selected variables. Skewness and
kurtosis indicates how much a distribution varies from a normal
distribution. Results from the table shows that liquidity ratios do not
follow normal distribution. Due to the size of relative firms, mean
values of liquidity ratios are also higher and volatile too. Asset Turn
over ratios to some extent follow normal distribution but volatility can
be easily seen due to manufacturing capacity of individual firms.
Finally, the Profitability ratios are less volatile comparatively and
progressively increasing then declining with lowers pace.
REGRESSION ANALYSIS RESULTS
HYPOTHESIS
Minimum Maximum Mean
Std.
Deviation Skewness Kurtosis
current Ratio 55.1 522.0 168.692 115.9324 1.681 2.671
Quick ratio 32.8 446.5 118.733 100.0590 1.922 4.033
ACP 24.60 68.53 42.1733 9.31396 .891 1.866
DSI 26.31 184.90 93.4458 47.50949 .746 -.729
APT 33.18 115.40 67.3525 25.27880 .442 -1.104
CCC -2.3 190.1 68.265 55.9211 .786 -.340
CATA .13 .54 .3498 .13275 -.321 -1.097
CLTA .09 .55 .3364 .13366 -.260 -.934
ICA .10 .49 .2692 .10532 .301 -.706
ARCA .08 .45 .2538 .10664 -.101 -.960
ROA -5.7 27.2 11.283 8.6572 -.318 -.631
ROE -26.9 55.2 20.946 19.2207 -.719 1.402
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Ho: There is no relationship between dependent and
independent variable
H1: There is relationship between dependent and independent
variable
MODEL 1
PF = 0 + 1CR + 2QR + 3 ACP + 4DSI + 5 APT +
6CCC + where ROA is dependent variable
Using pooled regression technique, we ran the regression of the
profitability on Liquidity ratios and Asset turnover ratios. These were
used with an aim to investigate whether these mentioned variables
have significant explanatory power or not.
Table-2 Linear Regression Results
Model 1
Un-standardized
Coefficients
BStd.
Error
Constant 11.690 9.554
Current Ratio .165 .140
Quick ratio -.153 .157
Average collection
period-.375 .214
Accounts payable
turnover in days.033 .077
Cash conversion cycle .050 .039
Days sales in
Inventory.064 .036
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From the regression model, we can give the following relationship;
PF = 11.690 + .165CR - .153QR - .375ACP + .064DSI + .033APT + .033CCC
Table-3 Model Summary
Mod
el R
R-
Square
Adjuste
d R-
Square
Std. Error
of the
Estimate
Durbin-
Watson
1 .648 .419 .258 7.4571 1.920
In theory, the relation between the ROA and Liquidity ratio should have
a positive relation and follow a linear pattern. But as we mentioned
earlier, due to distinct size of firms, the pattern is not normally
distributed. R value is 64.8% which implies that any variation in
profitability is explained by these variables and 35.2% variation is due
to other factors. Significance value of F- statistics is 0.061, which
indicates the independent variables do poor job explaining the
variation in the dependent variable. The Durbin Watson value
associated with pooled regression is 1.920; there is evidence of
positive serial correlation but it also indicates to some extent noautocorrelation. The P-value associated with F-statistics is 0.061 which
is more than 0.05.Also significance value associated with all the
variables are more then 0.005, therefore we fail to reject H0 and
conclude that all these above mentioned variables do not significantly
explain variation in profitability.
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MODEL 2
PF = 0 + 1CR + 2QR + 3 ACP + 4DSI + 5 APT +
6CCC + where ROE is dependent variable
HYPOTHESIS
Ho: There is no relationship between dependent and
independent variable
H1: There is relationship between dependent and independent
variable
Using pooled regression technique, we ran the regression of Return on
Equity on Liquidity ratios and Asset turnover ratios. These were used
with an aim to examine whether these mentioned variables have
considerable descriptive influence or not.
Table-4 Linear Regression Results
Table-5 Model Summary
Mod
el R
R-
Square
Adjuste
d R-
Square
Std. Error
of the
Estimate
Durbin-
Watson
1 .430(a) .185 -.041 19.6122 2.282
Model 1
Un-standardized
Coefficients
BStd.
Error
Constant 27.077 25.128
Current Ratio .464 .368
Quick ratio -.470 .413
Average collection
period-.789 .563
Accounts payable
turnover in days.075 .202
Cash conversion cycle -.006 .102
Days sales in
Inventory
.035 .086
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From the regression model, we can give the following relationship;
PF = 27.077 + .464CR - .470QR - .789ACP + .035DSI + .
075APT - .006CCC
R value is 43% only, which implies that any variation in profitability is
explained by these variables and 57% variation is due to other factors.
Significance value of F- statistics is 0.681, which indicates the
independent variables do deprived job in explaining the variation in the
dependent variable.The Durbin Watson value associated with pooled
regression is 2.282; there is evidence of negative serial correlation but
it also indicates to some extent no autocorrelation. The P-value
associated with F-statistics is 0.681 and significance value of t-
statistics for all the variables are higher; more than 0.05, therefore we
fail to reject H0 and conclude that all these above mentioned variablesdo not significantly explain variation in profitability.
MODEL 3
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PF = 0 + 1CATA + 2CLTA + 3 ICA + 4 ARCA
where ROA is dependent variable.
HYPOTHESIS
Ho: There is no relationship between dependent andindependent variable
H1: There is relationship between dependent and independent
variable
Table-6 Model Summary
We ran the regression of the profitability(ROA) on current asset to
total assets, current liabilities to total asset, and inventory tocurrent assets and account receivables to current asset.
Table-7 Linear Regression Results
Mod
el R
R-
Square
Adjuste
d R-
Square
Std. Error
of the
Estimate
Durbin-
Watson
1 .647(a) .418 .296 7.2640 2.275
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From the regression model, we can give the following relationship;
PF = 16.945 - 7.481CATA - 15.518CLTA + 35.129 ICA -
28.679 ARCA
R value again 64.7%, which implies that any variation in profitability is
explained by these variables and only 35.3% variation, is due to other
factors. The Durbin-Watson statistic is also 2.275 that imply that the
following values of estimated residuals are not dependent on each
other. The overall model is good and there is an evidence to accept
that there is no autocorrelation problem exit in the model. If the
Model 1
Un-standardized
Coefficients
BStd.
Error
Constant 16.945 6.715
CATA -7.481 11.623
CLTA -15.518 15.322
ICA 35.129 14.833
ARCA -28.679 19.582
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significance value of the F statistic is small (smaller than say 0.05)
then the independent variables do a good job explaining the variation
in the dependent variable. Here the sig. value or the P-value is 0.029
which again proves that the independent variables do a good job in
explaining the variation with the dependent variable. The t statistic
and its significance value are used to test the null hypothesis that the
regression coefficient is zero. Inventory to current asset has the sig.
value 0.029 which is less than 0.05 so for Inventory to current asset we
reject H0 and accept H1 that there is a significance relation with
variable and return on asset. Other variables have sig. value that are
greater than 0.05 so for them we accept H0 claiming that there is no
relationship b/w them and ROA.
MODEL 4
PF = 0 + 1CATA + 2CLTA + 3 ICA + 4 ARCA
where ROE is dependent variable.
HYPOTHESIS
Ho: There is no relationship between dependent and
independent variable
H1: There is relationship between dependent and independent
variable
Table-8 Model Summary
Mod
el R
R-
Square
Adjuste
d R-
Square
Std. Error
of the
Estimate
Durbin-
Watson
1 .580(a) .336 .196 17.2342 2.260
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We ran the regression of the profitability(ROE) on current asset to
total assets, current liabilities to total asset, and inventory to
current assets and account receivables to current asset.
Table-9 Linear Regression Results
The Durbin-Watson statistic is also 2.260 that imply following values of
estimated residuals are not dependent on each other. There is an
evidence to accept that there is no autocorrelation problem exit in the
model. R value is 58% indicating more than half of the profitability
variation is due to these stated variables. Significance value of F-
statistics is 0.086, greater then 0.05, which indicates that independent
variables do a meager job in explaining the variation with the
Model 1
Un-standardized
Coefficients
BStd.
Error
Constant 5.253 15.932
CATA 18.298 27.576
CLTA -12.306 36.352
ICA 92.812 35.192
ARCA -45.505 46.458
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dependent variable. Inventory to current asset has a significance value
of 0.016 associated with t-statistics, so we reject null hypothesis and
accept H1 for this variable only. All the other variables have higher
values; therefore, we fail to reject null Hypothesis for those variables.
TESTING VARIABLES INDIVIDUALLY
Profitability & Current Ratio
Ho: Profitability of the firms is notsignificantly affected by current
ratio
H1: Profitability of the firm is significantly affected by current ratio
In order to check the relationship between the two variables, we used
Pearsons Correlation technique. Profitability variables ROA and ROE
are tested individually. Here are the results of the test
In conclusion, as the p value is 0.05, we can say that there is a
significant relationship between ROA and current ratio and 26.1% of
the variation in ROA is explained by current ratio. But with respect to
Pearson Correlation 0.511
Sig. (1-tailed) 0.005
Table-10 w.r.t. ROA
Pearson Correlation 0.286
Sig. (1-tailed) 0.088Table-11 w.r.t. ROE
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ROE, p value is greater, 0.088; and only 8.17% (0.2862) variation in
ROE is explained by current ratio. Therefore we can say there is no
significant relationship between ROE and current ratio.
Profitability & Quick Ratio
Ho: Profitability of the firms is not significantly affected by Quick
ratio
H1: Profitability of the firm is significantly affected by Quick ratio
P value is 0.008 associated with ROA; correlation is significant at the
0.01 level. Also 23.3% variation in ROA is explained by quick ratio.
Therefore we can say there is a significant relationship between ROA
and quick ratio and reject null hypothesos. As the p value for ROE is
greater then 0.05, correlation is not significant and we can say there is
no considerable relationship exists between ROE and quick ratio and
accept null Hypothesis.
Pearson Correlation 0.483
Sig. (1-tailed) 0.008
Table-12 w.r.t. ROA
Pearson Correlation 0.271
Sig. (1-tailed) 0.100
Table-13 w.r.t. ROE
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Profitability & Cash Conversion Cycle
Ho: Profitability of the firms is notsignificantly affected by CCC
H1: Profitability of the firm is significantly affected by CCC
This metric looks at the amount of time needed to sell inventory, the
amount of time needed to collect receivables and the length
of time the company is afforded to pay its bills without incurring
penalties. So it would be more appropriate to consider this variable
rather then taking DIO, DSO and DPO separately. Profitability variables
ROA and ROE are tested individually. Here are the results of the test:
From the above results we can see that the p-value is 0.019 which is
less than 0.05, so we fail to accept H0 and conclude that cashconversion cycle does have a significant impact on ROA. The Pearsons
correlation value is .428 which shows that these two variables have a
positive correlation with each other. This means that the greater the
cash conversion cycle the greater would be profitability.
Profitability & Current Assets to total assets
Ho: Profitability of the firms is notsignificantly affected byCATA
H1: Profitability of the firm is significantly affected by CATA
In order to check the relationship between the two variables, we used
Pearsons Correlation technique. Profitability variables ROA and ROE
are tested individually. Here are the results of the test:
Pearson Correlation 0.428
Sig. (1-tailed) 0.019
Table-14 w.r.t. ROA
Pearson Correlation 0.109
Sig. (1-tailed) 0.306
Table-15 w.r.t. ROE
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From the results, we can easily envisage that Profitability ratios are not
very much explained by this ratio. As the p values are also greater
then 0.05, we conclude that there is no significant relation exists
therefore accepting Ho. However, the sign of the correlation coefficient
for ROA indicates the negative direction of the relationship.
Profitability & Current Liabilities to total assets
Ho: Profitability of the firms is notsignificantly affected byCLTA
H1: Profitability of the firm is significantly affected by CLTA
For ROA p value is 0.011, means correlation is significant at the 0.05
level. The sign of the correlation coefficient indicates the negative
direction. Therefore, we conclude that significant relationship exitsbetween ROA and this variable and we fail to accept null Hypothesis. In
contrast, the p value is quite high for ROE and we cannot conclude
significant relationship existence between these two variables and
accept Ho.
Pearson Correlation -0.75
Sig. (1-tailed) 0.364
Table-16 w.r.t. ROA
Pearson Correlation 0.173
Sig. (1-tailed) 0.209
Table-17 w.r.t. ROE
Pearson Correlation -0.467
Sig. (1-tailed) 0.011Table-18 w.r.t. ROA
Pearson Correlation -0.230
Sig. (1-tailed) 0.140
Table-19 w.r.t. ROE
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Profitability & Inventory to Current Assets
Ho: Profitability of the firms is notsignificantly affected byICA
H1: Profitability of the firm is significantly affected by ICA
Surprisingly, the results show very much correlation with this specific
ratio. Correlation is significant at 0.05 level, however the extent of
variations in profitability ratios due to this variable is not very much
substantial. Therefore, we reject null hypothesis and conclude that
profitability of firms is affected by ICA.
Profitability & Accounts Receivable to Current Assets
Ho: Profitability of the firms is notsignificantly affected byARCA
H1: Profitability of the firm is significantly affected by ARCA
In order to check the relationship between the two variables, we used
Pearsons Correlation technique. Profitability variables ROA and ROE
are tested individually. Here are the results of the test:
Pearson Correlation 0.348
Sig. (1-tailed) 0.048
Table-20 w.r.t. ROA
Pearson Correlation 0.468
Sig. (1-tailed) 0.011
Table-21 w.r.t. ROE
Pearson Correlation -0.422
Sig. (1-tailed) 0.020
Table-22 w.r.t. ROA
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For ROA p value is 0.020, means correlation is significant at the 0.05
level. The sign of the correlation coefficient indicates the negative
direction. Therefore, we conclude that significant relationship exits
between ROA and this variable and we fail to accept null Hypothesis. In
contrast, the p value is quite high for ROE and we cannot conclude
significant relationship existence between these two variables and
accept Ho.
Conclusion
In this study, we analyzed a sample of 4 out of 6 Packaging firms by
using a linear regression model and calculated their specific ratios to
measure the determinants of profitability of the firms. The study used
the data of 6 years from 2004 to 2009.After forming hypotheses andtesting them, we found out whether the various ratios that we had
Pearson Correlation -0.224
Sig. (1-tailed) 0.147
Table-23 w.r.t. ROE
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calculated have any relation or linkage with profitability (ROA, ROE).
We have thus gathered reasonable evidence to show that:
There is a relationship between Liquidity ratios (Current and
Quick) and return on assets of the packaging firms, whereas
when we compare Liquidity ratios with the return on equity,
there is no relationship.
There is a relationship between ROA and Cash Conversion
Cycle but no significant relationship between ROE and CCC
Profitability does have relation with Current liabilities to total
asset ratio.
An increase in the liquidity ratio (both Quick and Current
Ratios) leads to an increase in the ROA of the firm.
APPENDIX-I
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APPENDIX-I
2004 2005 2006 2007 2008 2009
COMPAN
Y GHGL GHANI GLASS LTD
CR266.5 307.8 133.8 143.1 140.4 157.7
QR161.2 216.4 94.7 104.1 102.2 104.3
AVP68.53 56.1 49.3 43.4 33.75 24.6
DSI 172.67 159.35 165.84 172.52 184.9 141.66
APD51.13 38.4 63.2 89.9 77.9 79.1
CCC190.1 177 151.94 126 140.75 87.16
CATA0.23 0.19 0.13 0.14 0.14 0.16
CLTA 0.21 0.2 0.34 0.35 0.37 0.3
ICA0.39 0.29 0.3 0.27 0.27 0.34
ARCA0.28 0.29 0.26 0.211 0.18 0.15
ROA21.1 21.2 16.1 12 17.3 20
ROE 28.4 27.7 25.1 18.7 27.7 28.7
8/3/2019 Final TERM Report Cf
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APPENDIX-I
2004 2005 2006 2007 2008 2009
COMPAN
Y PKGS Packages Limited
CR149.8 186.7 314.6 522 241.1 389.7
QR99.5 146.8 259.7 446.5 184.5 292.5
AVP33.9 35.08 29.9 40.25 38.87 45.4
DSI 72.2 51.15 60.13 68.9 93.2 106.6
APD38.9 33.18 44.62 56.1 39.9 44
CCC67.2 53.05 45.41 53.05 92.17 108
CATA0.53 0.46 0.42 0.456 0.44 0.46
CLTA 0.35 0.25 0.13 0.09 0.18 0.12
ICA0.34 0.21 0.17 0.14 0.23 0.25
ARCA0.16 0.15 0.09 0.08 0.1 0.11
ROA15.6 11.4 27.2 16.6 -0.9 16.2
ROE 24.5 17.2 45.1 30.5 -1.9 26.5
8/3/2019 Final TERM Report Cf
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APPENDIX-I
2004 2005 2006 2007 2008 2009
COMPAN
Y ECOP ECOPACK Ltd
CR55.1 79.8 84.8 89.5 80.6 56.6
QR32.8 39.7 44.4 41.8 44.3 34
AVP43.9 43.1 36.9 43.7 44.9 45.7
DSI 69.2 86.9 75.4 111.7 61.2 53.6
APD115.4 109.1 100.6 105.1 62.5 87.1
CCC-2.3 20.9 11.7 50.3 43.6 12.2
CATA0.25 0.32 0.36 0.41 0.39 0.31
CLTA 0.45 0.41 0.43 0.45 0.5 0.55
ICA0.099 0.16 0.17 0.22 0.18 0.12
ARCA0.33 0.3 0.28 0.24 0.36 0.38
ROA5.6 5.1 7 0.5 -4 -5.7
ROE 16.4 15.4 22 2 -21 -26.9
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