Final TERM Report Cf

8/3/2019 Final TERM Report Cf

1/28

TERM

RESEARCH REPORT

INFLUENCE OF WORKING CAPITAL MANAGEMENT

ON PROFITABILITY OF PACKAGING SECTOR

FIRMS IN PAKISTAN

TERM REPORT


2/28

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


3/28

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


4/28

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.


5/28

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.


6/28

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


7/28

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


8/28

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


9/28

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


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


10/28

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


11/28

Ho: There is no relationship between dependent and

independent variable

H1: There is relationship between dependent and independent

variable

MODEL 1


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


12/28

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.


13/28

MODEL 2


6CCC + where ROE is dependent variable

HYPOTHESIS




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.



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


14/28


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


15/28

PF = 0 + 1CATA + 2CLTA + 3 ICA + 4 ARCA

where ROA is dependent variable.

HYPOTHESIS

Ho: There is no relationship between dependent andindependent variable


variable


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.


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


16/28


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


17/28

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




variable


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


18/28

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.


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


19/28

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


Sig. (1-tailed) 0.088Table-11 w.r.t. ROE


20/28

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.



Table-12 w.r.t. ROA



Table-13 w.r.t. ROE


21/28

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



are tested individually. Here are the results of the test:



Table-14 w.r.t. ROA



Table-15 w.r.t. ROE


22/28

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


Table-16 w.r.t. ROA



Table-17 w.r.t. ROE


Sig. (1-tailed) 0.011Table-18 w.r.t. ROA



Table-19 w.r.t. ROE


23/28

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



are tested individually. Here are the results of the test:



Table-20 w.r.t. ROA



Table-21 w.r.t. ROE



Table-22 w.r.t. ROA


24/28

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



Table-23 w.r.t. ROE


25/28

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


26/28

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


27/28

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


28/28

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

Documents

Final TERM Report Cf