2012  

JAHANGIRNAGAR UNIVERSITY  Khairuzzaman Mamun 

 

A REPORT ON CEMENT COMPANIES IN BANGLADESH

 

A Report

On

Cement Companies in Bangladesh

Prepared for

Prepared by

Md. Tarikul Islam Assistant Professor, Chireman, Department of Finance & Banking Jahangirnagar University Savar, Daka-1342

1. Khairuzzaman Mamun ID No :20113137 Contact no : 01761808592 Email : knpmmamun@gmail.com

2. Md. Keramat Ali ID No: 20113207

3. Md. Mojibur Rahman ID No: 20113238

4. Narayan Chandra Sarker ID No: 20113180

5. Kazi Hossain Ansary ID No: 20113149

Submission Date: December 22,2012

December 21, 2012

Md. Tarikul Islam

Chairman

Department of Finance & Banking

Jahangirnagar University,

Savar,Dhaka.

Dear Md. Tarikul Islam

Here is the report that you asked us to conduct on November 10, 2012 on A Report Study On Cement Companies in Bangladesh

This study focused on different types of discussion and result about the Historical Performance of Cement Companies in Bangladesh. We will be pleased if you have any further query for this you can call us at your convenient time and place.

Sincerely yours,

1. Khairuzzaman Mamun ID No :20113137 Contact no : 01761808592 Email : knpmmamun@gmail.com

2. Md. Keramat Ali ID No: 20113207

3. Md. Mojibur Rahman ID No: 20113238

4. Narayan Chandra Sarker ID No: 20113180

5. Kazi Hossain Ansary ID No: 20113149

   

ABSTRACT

This report is aimed at finding the relationship between the net income and the current asset, current liability, working capital, debt ratio, current ratio, quick ratio, taking cement companies of Bangladesh into consideration. It overviews some

theoretical literature on these financial factors and presents the regression outputs and their interpretation.

The findings of the study are:

1. Position of the various financial performances of these companies. 2. The regression output has components:

o Regression statistics table o Correlation table o Model summery o ANOVA table o Regression coefficients table o Excluded Variables table.

3. And their interpretation.

Quantitative data is taken from company’s annual reports, business research

companies’ archives and financial websites. The findings from the study can either have a positive or negative impact on financial performance.

 

Sequence of contents 

 

 

Introduction o Current asset o Current liabilities o Working capital o Debt Ratio o Quick ratio o Current ratio o Net income

Analysis and Interpretation regression output

o Regression statistics table o Correlation table o Model summery o ANOVA table o Regression coefficients table o Excluded Variables table.

Recommendations & suggestions Conclusions References

Introduction

This study focuses on current asset, current liability, working capital debt ratio, quick ratio and current ratio. The study also focuses on their impact on net income of the cement factories in Bangladesh.

A current asset current asset is an asset which can either be converted to cash or used to pay current liabilities within 12 months. Typical current assets include cash, cash equivalents, short-term investments, accounts receivable, inventory and the portion of prepaid liabilities which will be paid within a year.

On a balance sheet, assets will typically be classified into current assets and long-term assets.

Current liabilities are often understood as all liabilities of the business that are to be settled in cash within the fiscal year or the operating cycle of a given firm, whichever period is longer. A more complete definition is that current liabilities are obligations that will be settled by current assets or by the creation of new current liabilities. Accounts payable are due within 30 days, and are paid within 30 days, but do often run past 30 days or 60 days in some situations. The laws regarding late payment and claims for unpaid accounts payable is related to the issue of accounts payable. An operating cycle for a firm is the average time that is required to go from cash to cash in producing revenues.

Working capital (abbreviated WC) is a financial metric which represents operating liquidity available to a business, organization or other entity, including governmental entity. Along with fixed assets such as plant and equipment, working capital is considered a part of operating capital. Net working capital is calculated as current assets minus current liabilities.

WC = Current Assets – Current Liabilities

It is a derivation of working capital that is commonly used in valuation techniques such as DCFs (Discounted cash flows). If current assets are less than current liabilities, an entity has a working capital deficiency, also called a working capital deficit.

A company can be endowed with assets and profitability but short of liquidity if its assets cannot readily be converted into cash. Positive working capital is required to ensure that a firm is able to continue its operations and that it has sufficient funds

to satisfy both maturing short-term debt and upcoming operational expenses. The management of working capital involves managing inventories, accounts receivable and payable, and cash.

Debt Ratio is a financial ratio that indicates the percentage of a company's assets that are provided via debt. It is the ratio of total debt (the sum of current liabilities and long-term liabilities) and total assets (the sum of current assets, fixed assets, and other assets such as 'goodwill').

or alternatively:

The Acid-test or quick ratio or liquid ratio measures the ability of a company to use its near cash or quick assets to extinguish or retire its current liabilities immediately. Quick assets include those current assets that presumably can be quickly converted to cash at close to their book values. A company with a Quick Ratio of less than 1 cannot currently pay back its current liabilities.

Note that Inventory is excluded from the sum of assets in the Quick Ratio, but included in the Current Ratio. Ratios are tests of viability for business entities but do not give a complete picture of the business' health. If a business has large amounts in Accounts Receivable which are due for payment after a long period (say 120 days), and essential business expenses and Accounts Payable due for immediate payment, the Quick Ratio may look healthy when the business is actually about to run out of cash. In contrast, if the business has negotiated fast payment or cash from customers, and long terms from suppliers, it may have a very low Quick Ratio and yet be very healthy. Notice that very often Acid test refers instead of Quick ratio to Cash ratio:

The current ratio is a financial ratio that measures whether or not a firm has enough resources to pay its debts over the next 12 months. It compares a firm's current assets to its current liabilities. The current ratio is calculated by dividing total current assets by total current liabilities. It is frequently used as an indicator of a company's liquidity, its ability to meet short-term obligations.

It is expressed as follows:

The current ratio is an indication of a firm's market liquidity and ability to meet creditor's demands. Acceptable current ratios vary from industry to industry and are generally between 1.5 and 3 for healthy businesses. If a company's current ratio is in this range, then it generally indicates good short-term financial strength. If current liabilities exceed current assets (the current ratio is below 1), then the company may have problems meeting its short-term obligations. If the current ratio is too high, then the company may not be efficiently using its current assets or its short-term financing facilities. This may also indicate problems in working capital management.

Net income also referred to as the bottom line, net profit, or net earnings is an entity's income minus expenses for an accounting period. It is computed as the residual of all revenues and gains over all expenses and losses for the period, and has also been defined as the net increase in stockholder's equity that results from a company's operations. In the context of the presentation of financial statements, the IFRS Foundation defines net income as synonymous with profit and loss.

   

Analysis and Interpretation

For analyzing and interpretation we have selected four cement company’s data. The companies are HEIDEBERG CEMENT, ARMIT CEMENT, CONFIDENCE CEMENT, MEGNA CEMENT. Then we have run regression by SPSS taking NETINCOME as dependent variable and CA, CL, WC, DR, QT, CR as independent variable. WC = WORKING CAPITAL CA = CURRENT ASSET DR = DEFT RATIO CL = CURRENT LIABITY QT = QUICK TEST CR = CURRENT RATIO

YEAR CA CL WC DR QT CR NET INCOME HEIDEBERG CEMENT

1995 291776135 232312702 59463433 0.42 0.63 1.26 49063770 1996 283936620 280331281 3605339 0.35 0.45 1.01 87222766 1997 487728422 466639344 21089078 0.23 1.02 1.43 90162723 1998 656544310 483855466 172688844 0.186 1.09 1.36 137490404 1999 662942602 500088523 162854079 0.166 1.11 1.33 190134844 2000 1090451 590807 499644 0.307 1.8 2.12 203966 2001 1049119 496514 552605 0.368 2.09 2.5 209023 2002 814110 402845 411265 0 2.06 2.3 46570 2003 958958 1659205 -700247 0 2.1 2.12 55373

ARMIT CEMENT 1999 69982997 133915884 -63932887 0.489 0.2 0.52 12584566 2000 95485808 113300823 -17815015 0.391 0.16 0.84 63728613 2001 106532929 1168944862 -1062411933 0.374 0.22 0.63 22605647 2002 92676487 193194810 -100518323 0.336 0.25 0.48 45325802 2003 82506088 170931414 -88425326 0.292 0.17 0.48 -56047924 2004 58364763 158144182 -99779419 0.292 0.17 0.37 -63145695 2005 118037786 274693852 -156656066 0.186 0.18 0.43 -26640998 2006 150168808 343833723 -193664915 0.121 0.17 0.44 6971807

CONFIDENCE CEMENT

1996 140230667 147230786 -7000119 0.411 0.21 0.95 5596310 1997 374423669 70780203 303643466 0.167 4.02 5.29 18563667 1998 170259858 86527911 83731947 0.297 1.03 1.97 70458069

MEGNA CEMENT 1996 205110279 251268787 -46158508 0.566 0.811 0.811 22792205 1997 342103994 335576756 6527238 0.583 0.979 1.019 32144414

1998 452766064 437159410 15606654 0.576 0.958 1.036 31311683 1999 393683728 364468510 29215218 0.703 1.012 1.08 49641627 2000 744257833 670755663 73502170 0.644 0.988 1.11 110573729 2001 1018622921 990863219 27759702 0.597 0.965 1.028 132743297 2002 1253123650 1229932887 23190763 0.577 0.884 1.019 51939193 2003 1003252653 952991742 50260911 0.597 1.035 1.053 26021799 2004 952008134 943392659 8615475 0.559 0.987 1.009 34311762 2005 1180027914 1188086536 -8058622 0.517 0.941 0.993 75106875 2006 1001283610 1064853393 -63569783 0.452 0.881 0.94 56437753

The regression output has components:

• Regression statistics table • Correlation table • Model summery • ANOVA table • Regression coefficients table • Excluded Variables table.

INTERPRET REGRESSION STATISTICS TABLE Descriptive Statistics

Mean Std. Deviation N NETINCOME 41213343.2258 54399845.30082 31CA 399733915.0645 390685882.39495 31CL 427652409.6452 394522244.70347 31WC -27918494.5806 214100614.82741 31DR .3792 .18861 31QR .9539 .80888 31CR 1.2557 .93617 31

This table presents mean and deviation of dependent variable net income and independent variables CA, CL, WC, DR, QR, CR.

Correlations

NETINCOME CA CL WC DR QR CR Pearson Correlation

NETINCOME 1.000 .545 .381 .292 .165 .040 .022

CA .545 1.000 .851 .256 .507 .046 -.080 CL .381 .851 1.000 -.289 .501 -.197 -.311 WC .292 .256 -.289 1.000 .001 .447 .426

DR .165 .507 .501 .001 1.000 -.270 -.345 QR .040 .046 -.197 .447 -.270 1.000 .952 CR .022 -.080 -.311 .426 -.345 .952 1.000Sig. (1-tailed) NETINCOME

. .001 .017 .055 .187 .414 .452

CA .001 . .000 .082 .002 .403 .334 CL .017 .000 . .057 .002 .143 .045 WC .055 .082 .057 . .498 .006 .008 DR .187 .002 .002 .498 . .071 .029 QR .414 .403 .143 .006 .071 . .000 CR .452 .334 .045 .008 .029 .000 .N NETINCOME

31 31 31 31 31 31 31

CA 31 31 31 31 31 31 31 CL 31 31 31 31 31 31 31 WC 31 31 31 31 31 31 31 DR 31 31 31 31 31 31 31 QR 31 31 31 31 31 31 31 CR 31 31 31 31 31 31 31

This table presents the correlation and significance between the variables net income, CA, CL, WC, DR, QR, CR by matrix representation.

Model Summary

This is the following output of greatest interest is R Square.

Explanation Multiple R .605(a) R = square root of R2 R Square .366 R2 Adjusted R Square .239 Adjusted R2 used if more than one x variable

Standard Error 47452486.75859 This is the sample estimate of the standard deviation of the error u

Observations 31 Number of observations used in the regression (n)

The above gives the overall goodness-of-fit measures: R2 = 0.366 Correlation between y and y-hat is 0.366 (when squared gives 0.366). Adjusted R2 = R2 - (1-R2 )*(k-1)/(n-k) =0.239

R2 = 0.366 means that 36.6% of the variation of NETINCOME can be explained by the regressors CA, WC, DR, QR, and CR.

INTERPRET ANOVA TABLE

An ANOVA table is given. This is often skipped.

df SS MS F Significance F

Regression 5 32486832573223480 6497366514644690 2.885 0.034(a)

Residual 25 56293462489355600 2251738499574224

Total 30 88780295062579000

The ANOVA (analysis of variance) table splits the sum of squares into its components.

Total sums of squares = Residual (or error) sum of squares + Regression (or explained) sum of squares.

The column labeled F gives the overall F-test of H0: βi = 0 versus Ha: at least one of βi does not equal zero. F = 2.885

The column labeled significance F has the associated P-value. Since 0.034 < 0.05, we reject H0 at significance level 0.05.

INTERPRET REGRESSION COEFFICIENTS TABLE

The regression output of most interest is the following table of coefficients and associated output:

Coefficient St. error t Stat P-value Lower 95% Upper 95% Intercept 22270965.80 29952516.092 0.744 0.464 -39417395.839 83959327.447CA 0.090 0.029 3.142 0.004 0.031 0.149WC 0.044 0.047 0.938 0.357 -0.053 0.142DR -40844164.44 56981244.240 -0.717 0.480 -158199233.740 76510904.852QR -42245774.55 38256908.829 -1.104 0.280 -121037353.198 36545804.088CR 31910230.87 33546570.740 0.951 0.351 -37180224.878 101000686.625 a Dependent Variable: NETINCOME. Let βj denote the population coefficient of the jth regressor (intercept, CA, WC, DR, QR and CR). Then

• Column "Coefficient" gives the least squares estimates of βj. • Column "Standard error" gives the standard errors (i.e.the estimated standard deviation)

of the least squares estimates bj of βj. • Column "t Stat" gives the computed t-statistic for H0: βj = 0 against Ha: βj ≠ 0.

This is the coefficient divided by the standard error. It is compared to a t with (n-k) degrees of freedom.

• Column "P-value" gives the p-value for test of H0: βj = 0 against Ha: βj ≠ 0..

This equals the Pr{|t| > t-Stat}where t is a t-distributed random variable with n-k degrees of freedom and t-Stat is the computed value of the t-statistic given in the previous column. Note that this p-value is for a two-sided test. For a one-sided test divide this p-value by 2 (also checking the sign of the t-Stat).

• Columns "Lower 95%" and "Upper 95%" values define a 95% confidence interval for βj.

A simple summary of the above output is that the fitted line is

NETINCOME = 22270965.80 + 0.090 CA + .044 WC - 40844164.44 DR - 42245774.55 QR + 31910230.87 CR

CONFIDENCE INTERVALS FOR SLOPE COEFFICIENTS

95% confidence interval for slope coefficient CA is from output (0.031, 0 .149).

95% confidence interval for slope coefficient WC is from output (-0.053, 0.142).

95% confidence interval for slope coefficient DR is from output (-158199233.740, 76510904.852).

95% confidence interval for slope coefficient QR is from output (-121037353.198, 36545804.088).

95% confidence interval for slope coefficient CR is from output (-37180224.878, 101000686.625).

Excluded Variables(b)

Model Beta In t Sig. Partial

Correlation Collinearity Statistics

Tolerance 1 CL .(a) . . . .000

a Predictors in the Model: (Constant), CR, CA, WC, DR, QR b Dependent Variable: NETINCOME

Recommendations & suggestions

Since R2 = 0.366. It means that 36.6% of the variation of NETINCOME can be explained by the regressors CA, WC, DR, QR, and CR. So, it should take into consideration.

Again since, fitted line is

NETINCOME = 22270965.80 + 0.090 CA + .044 WC - 40844164.44 DR - 42245774.55 QR + 31910230.87 CR.

So, we are recommending that current asset, working capital and current ratio should be increased and debt ratio, quick ratio should be decreased to increase net income in cement companies in Bangladesh. We know, And also coefficient of quick ratio is negative so inventories per unit liabilities must be increased for increasing the value of net income of cement factories in Bangladesh.

Conclusions

Based on this study it can be said that if cement companies in Bangladesh follow the suggestion of this study then they will be more benefited and more successful in their business. 

References

Book Name: Principles of Financial Management Satish M. Inamdar Sixth Edition, 2009

Search engine: www.google.com Wikipedia Company’s Annual Report: Dhaka Stock Exchange