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SRI AYAN CHAKRABORTY: IMPACT OF DPS ON MPS: A STUDY ON LEADING INDIAN CEMENT COMPANIES

DOI: 10.21917/ijms.2018.0111

818

IMPACT OF DPS ON MPS: A STUDY ON LEADING INDIAN CEMENT COMPANIES

Sri Ayan Chakraborty Faculty of Management, Institute of Computer Accountants, Kolkata, India

Abstract

Risks and uncertainties are inherent in every organisation. Different

class of investors in do not shoulder the same degree of risk. An investor

in bonds earns return in from interest while shareholders depend on

dividends, stock price appreciation. Dividend refers to the distribution

of profit among the shareholders. Profit earned by a company can be

retained for future usage, or distributed in form of dividend or both.

Dividend decision is one of the important decisions, since it determines

the amount of profit to be distributed among shareholders and the

amount to be retained earnings for future investment purpose. This is

known as Dividend Policy. The main objective of every company is to

maximize shareholders wealth rather than profit. Shareholders gain

both from Dividend as well as Capital Appreciation. Moreover,

dividend policy of a company has an impact on its market price. Market

price increases only if a company provides stable return to its

shareholders. This paper focuses on the impact of dividend on Market

Price of a company.

Keywords:

Indian Cement Sector, Net Profit Margin, Dividend Per Share,

Dividend Yield, Earnings Per Share, Market Price Per Share, Price

Earnings Ratio

1. INTRODUCTION

Indian Cement Industry has the second largest market in the

world after China with production of 279.81 million tons per

annum. The Cement Industry comprises of 210 large and 365 mini

cement plants. Cement is a cyclical commodity with a high

correlation with GDP. The demand for cement in real estate sector

is spread across rural housing (40%), urban housing (25%) and

construction/infrastructure/industrial activities (25%). While the

rest 10% demand is contributed by commercial real estate sector.

The growth in the Real Estate sector has played a positive role

behind the development in the Cement Sector. Cement demand is

expected to reach 550 to 600 Million Tonnes Per Annum (MTPA)

by 2025 [1] [2].

Ultratech Cement: Headquartered in Mumbai, Ultra-Tech

Cement Ltd was founded in 1983. It has a production capacity of

93 million tonnes per annum (MTPA) of grey cement. It operates

across India, Bangladesh, Bahrain, UAE, and Sri Lanka. For

white cement segment, it adopts the brand name of Birla White.

ACC: Headquartered in Mumbai, Associated Cement

Companies Limited was founded in 1936. It is the second largest

Indian cement company with annual production capacity of 33.42

million tonnes. It operates with more than 40 ready mix concrete

plants, 21 sales offices, and several zonal offices.

Ambuja Cement: Headquartered in Mumbai, Ambuja Cements

Ltd was founded in 1983 and stated its production in 1986. It is

the third largest Indian cement company with annual production

capacity of 29.65 million tonnes. It has 5 integrated cement

manufacturing plants and 8 cement grinding units.

Shree Cements: Headquartered in Kolkata, Shree Cements

was founded in1979 in Bewar in Ajmer district of Rajasthan. It is

the fourth largest Indian cement company with annual production

capacity of 13.5 million tonnes. It has 6 cement manufacturing

plants located at Beawar, Ras, Khushkhera, Jaipur, Rajasthan and

Uttarakhand.

Ramco Cement: Headquartered in Chennai Ramco was

founded in 1984. It is the fifth largest Indian cement company

with annual production capacity of 16.45 million tonnes. It has 8

manufacturing plants including grinding unit. It also produces

Ready Mix Concrete and Dry Mortar products.

India Cements: Headquartered in Tirunelveli, The India

Cements Limited was founded in 1946. It is the sixth largest

Indian cement company with annual production capacity of 15.5

million tonnes. It manufactures cement for various applications,

including, precast concrete items, concrete components, and

multi-storey buildings, as well as runways, concrete roads,

bridges and for general-purpose use.

Prism Cement: Prism Cement Limited is India’s 8th leading

integrated Building Materials Company, with a wide range of

products from cement, ready-mixed concrete, tiles, and bath

products to kitchens. The company has three Divisions Prism

Cement, H and R Johnson (India), and RMC Readymix (India).

Binani Cement: Headquartered in Mumbai, Binani was

founded in the year 1872. It is the seventh largest Indian cement

company with annual production capacity of 11.25 million

tonnes. It has 2 integrated plants, one in India and another in

China, and grinding units in Dubai.

Birla Corp: M.P Birla is one of the top Industrial groups in

India. It offers wide range of products including auto interiors,

cables, jute, cement etc. The group include companies like

Vindhya Telelinks Ltd, Universal-ABB Power Cables Ltd,

Universal Cables Ltd, Hindustan Gum and Chemicals Ltd etc.

JK Cement: Headquartered in Mumbai, J.K Cement Ltd was

founded by Lala Kamlapat Singhania. It is one of the top

manufacturers of white cement in India. It has 3 cement

production plants located in Karnataka, Andhra Pradesh, and

Maharashtra. It produces 2 types of cements namely Portland Slag

Cement, Ordinary Portland Cement and Ground Granulated Blast

Furnace Slag.

1.1 OBJECTIVES OF THE STUDY

• To analysis the DPS and MPS of Leading Cement

Companies like Ultratech Cement, ACC, Ambuja Cement,

Shree Cement, India Cement, Prism Cement, Binani

Cement, Ramco Cement, Birla Corp, JK Cement

• To know the overall efficiency and performance of the firm

through financial analysis.

• To know the impact of Dividend on Market price

ISSN: 2395-1664 (ONLINE) ICTACT JOURNAL ON MANAGEMENT STUDIES, AUGUST 2018, VOLUME: 04, ISSUE: 03

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2. REVIEW OF LITERATURE

The concept of dividend policy has become an interesting

issue in financial literature. Many researches have been made on

dividend decision. Dividend is that part of the net earnings of a

corporation that is distributed to its stockholders. It is a payment

made to the equity shareholders for their investment in the

company. A large number of studies have been conducted in the

field of Dividend Policy and its impact on Market Price.

A brief review of some of these studies has been presented.

Krishman [3] propagated a bird in the hand theory, regarding

dividend distribution. According to this theory investors are risk

averse by their very nature.

Lintner [4] focussed on the behavioural side of the policy

regarding dividend payment decisions. He concluded that the

managers take the decisions to increase the proportion of

Dividend Payment, only when they are certain that the firm’s

earnings have increased permanently.

Kanval and Kapoor [5] examined the determinants of dividend

payment decision in the India’s Information Technology (IT)

sector. The time period of this study was 2000-2006. This study

found that only liquidity and year to year variation in profit are

the only two determinants of this decision.

Bose and Husain [6] explored the dividend payout policy of

five sectors in India, these five sectors were Software, Finance,

Steel, Electrical Machinery, and Pharmaceutical. Profitability of

the companies is found to be the sole Determinant of Dividend

Pay-out decisions.

Alzomania and Alkhadiri [7] examined the factors

determining dividend policy represented by dividend per share for

firms in the Saudi Arabia Stock Exchanges. They used regression

model and used a panel data covering the period during 2004-

2010 for 105 non-financial firms listed in the stock market. The

results consistently supported that Saudi Arabia non-financial

firms rely on current earning per share and past dividend per share

of the firm to set their dividend payments.

Baker et al. [8] surveyed 318 New York stock exchange firms

and concluded that the major determinants of dividend payments

are anticipated level of future earnings and pattern of past

dividends.

3. SCOPE OF STUDY

Dividend is a reward to equity shareholders for their

investment in the company. It is a basic right of equity

shareholders to get dividend from the earnings of a company. It is

generally paid in cash form but also it can be paid in allocation of

additional shares in the company. Dividend history report shows

the amount of dividend a company pays during its life cycle.

Normally investors want higher dividends from year to year. The

study is concerned with the impact of DPS on Dividend Yield,

EPS, MPS, P/E and Dividend Payout Ratio on 10 Leading Indian

Cement Companies. The study covers a period of 6 years from

2011-12 to 2016-17.

4. METHODOLOGY

4.1 SOURCES OF DATA

The study is based on secondary data. Information has been

collected from the Annual Reports of Ultratech Cement, ACC,

Ambuja Cement, Shree Cement, India Cement, Prism Cement,

Binani Cement, Ramco Cement, Birla Corp, JK Cement and

different books, journal, magazines, and data collected from

various websites.

4.2 TOOLS APPLIED

In this study various tools: Financial Tools [9] [10] - Ratio

Analysis and Statistical Tools (i.e.) Mean and ANOVA, t-test has

been used for data analysis.

Mean = Sum of variable/N

Standard Deviation is used to see how measurements for a

group are spread out from Mean. A low Standard Deviation means

that most of the numbers are very close to the average and vice-

versa.

SD =

2X

NX

N

Coefficient of Variation is a standardized measure of

dispersion of a probability distribution or frequency distribution.

It is the ratio of standard deviation to mean. Higher the coefficient

of variation, the greater the level of dispersion around mean and

vice-versa.

Coefficient of Variation (COV) = SD/Mean*100

• t-Test (Two-Sample Assuming Unequal Variances): t-test

assesses whether the means of two groups are statistically

different from each other.

• Hypothesis: An ANOVA is statistical hypothesis in which

the sampling distribution of test statistic when null

hypotheses is true. Null hypotheses have been set and

adopted for the analysis of data. The null hypotheses are

represented by H0. It is a negative statement which avoids

personal bias of investigator during data collection as well

as the time of drawing conclusion.

4.3 LIMITATION OF THE STUDY

• The study is related to a period of 6 years.

• Data is secondary i.e. they are collected from the published

Annual Reports

• Profitability, structural and valuation ratio have been taken

for the study.

Dividend policy of a company is closely linked to its

profitability and need for cash for financing future growth. Profit

is the prime motive of every business. It plays a pivotal role

behind the growth of an enterprise. It is the main base for liquidity

as well as solvency.


820

Net Margin Ratio: It shows the relationship between net profit

and sales. i.e., profit left for equity shareholders as a percentage

of net sales.

Table.1. Exhibit - 1: Net Profit Margin (%)

Year Ultratech ACC Ambuja Shree India Prism Binani Ramco Birla

Corp

JK

Cement

2011 -

12 12.57 12.60 14.41 10.49 5.61 -0.37 -5.41 11.95 10.47 6.88

2012 -

13 12.71 9.24 13.28 17.96 3.46 -1.27 -4.65 10.54 10.38 7.94

2013 -

14 10.32 9.70 14.03 13.37 -4.77 -1.71 -13.79 3.11 4.30 2.69

2014 -

15 8.74 9.80 14.97 6.61 -0.02 0.09 -14.78 6.73 5.46 4.19

2015 -

16 9.86 4.88 8.61 20.73 2.10 0.47 -11.40 15.22 5.13 1.45

2016 -

17 10.69 5.33 7.06 15.89 2.69 0.30 -12.80 16.74 5.05 5.43

Mean 10.81 8.59 12.06 14.17 1.51 -0.42 -10.47 10.71 6.80 4.76

SD 1.56 2.95 3.35 5.13 3.58 0.89 4.37 5.13 2.84 2.47

COV 0.14 0.34 0.28 0.36 2.37 -2.14 -0.42 0.48 0.42 0.52

CAGR

(%) -3.2 -15.8 -13.3 8.7 -13.7 -195.9 18.8 7.0 -13.6 -4.6

Exhibit-1 (Table.1) depicts that Shree Cements reported the

highest mean value in terms of Net Profit Margin followed by

Ambuja, Ultratech, Ramco etc. Standard deviation of Ramco

Cement is the highest followed by Shree Cement, Binani, Ambuja

etc. Binani Cement reported the highest CAGR of 18.8%.

Ultratech, ACC, Ambuja, India Cement, Prism Cement, Birla

Corp and JK Cement reported a negative CAGR.

Hypothesis:

H0: µ1=µ2=µ3=µ4=µ5=µ6=µ7=µ8=µ9=µ10 (Net Profit of

Cement Companies does not differ over years)

H1: µ1≠µ2≠µ3≠µ4≠µ5 ≠µ6≠µ7≠µ8≠µ9≠µ10 (Net Profit of

Cement Companies differ over years)

Table.2. Exhibit-2: Net Profit Margin: Anova Single Factor

Groups Count Sum Average Variance

Ultratech cement 6 64.88 10.81 2.425863

ACC 6 51.56 8.59 8.716298

Ambuja cement 6 72.36 12.06 11.254178

Shree cement 6 85.04 14.17 26.357876

India cement 6 9.07 1.51 12.827023

Prism cement 6 -2.50 -0.42 0.791994

Binani cement 6 -62.83 -10.47 19.072502

Ramco cement 6 64.29 10.71 26.366906

Birla Corp 6 40.80 6.80 8.037906

JK cement 6 28.58 4.76 6.117504

Table.3. Anova Variation

Source of

Variation SS df MS F

P-

value

F

criteria

Between

Groups 2,941.38 9 326.8204 26.79557 0.000 2.073351

Within

Groups 609.84 50 12.1968

Total 3,551.22 59

Above analysis shows that the F value (26.79557) is more than

the table value (2.073351) in Table.3, therefore null hypothesis is

rejected. Therefore, it is concluded that Net Profit Margin of the

Cement Companies differs over the years.

Earnings per Share (EPS): EPS is an important financial

measure, which indicates the profitability of a company. It shows

the relationship between Profit after Tax and no of Equity Shares

outstanding.

Table.3. Exhibit - 3: Earnings Per Share (EPS)


Corp

JK

Cement

2011-12 87.5 69.1 7.95 178 8.5 -0.33 -56.0 16.2 31.1 25.0

2012-13 98.1 56.3 8.37 288 5.8 -1.20 -70.4 17.0 35.1 33.0

2013-14 80.8 58.2 8.27 226 -7.9 -1.69 -220.5 4.8 16.9 10.7

2014-15 76.7 61.7 9.62 122 0.0 0.10 -204.1 10.3 22.8 20.3

2015-16 90.5 31.2 5.23 328 3.8 0.49 -137.6 22.9 21.8 7.8

2016-17 99.0 32.1 7.15 384 5.1 0.30 -149.6 27.9 28.5 32.4

Mean 89 51 8 254 3 0 -140 17 26 22

SD 9 16 1 98 6 1 67 8 7 11

COV 0.10 0.31 0.19 0.38 2.29 -2.24 -0.48 0.50 0.26 0.49

CAGR

(%) 2.5 -14.2 -2.1 16.7 -9.52 -197.8 21.7 11.5 -1.7 5.3

The Exhibit-3 (Table.3) depicts that Shree Cements reported

the highest mean value in terms of EPS followed by Ultratech,

ACC etc. Standard deviation of Shree Cement is the highest

indicating the maximum deviation from the Mean value followed

by Binani, ACC etc. Binani Cement reported the highest CAGR

of 21.7%. ACC, Ambuja, India Cement, Prism Cement and Birla

Corp reported a negative CAGR.

Hypothesis:

H0: µ1=µ2=µ3=µ4=µ5=µ6=µ7=µ8=µ9=µ10 (EPS of Cement

Companies doesn’t differ over years)

H1: µ1≠µ2≠µ3≠µ4≠µ5 ≠µ6≠µ7≠µ8≠µ9≠µ10 (EPS of Cement

Companies differ over years)

Table.4. Exhibit - 4: Earnings Per Share: Anova Single Factor



ACC 6 308.62 51.44 253.90

Ambuja cement 6 46.59 7.77 2.18

Shree cement 6 1,526.57 254.43 9,523.99

India cement 6 15.27 2.54 33.94

Prism cement 6 -2.34 -0.39 0.77

Binani cement 6 -838.18 -139.70 4,515.66

Ramco cement 6 99.07 16.51 69.12

Birla Corp 6 156.09 26.02 45.39

JK cement 6 129.17 21.53 113.22


821


Source of

Variation SS df MS F P-value F criteria

Between

Groups 5,12,612.59 9 56,956.95 38.9064488 1.52E-19 2.073351

Within

Groups 73,197.32 50 1,463.95

Total 5,85,809.91 59

Above analysis shows that the F value (38.9064488) is more

than the table value (2.073351) in Table.5, therefore null

hypothesis is rejected. Therefore, it is concluded that EPS of

Cement Companies differs over years.

Market Price Per Share (MPS): It is the price prevailing at

NSE as on 31st March of the respective years. This reveals the

value that the market currently assigns to each share.

Table.6. Exhibit - 5: Market Price Per Share (MPS)

Year Ultratech ACC Ambuja Shree India Prism Binani Ramco Birla Corp JK Cement

2011-

12 1,507 161 172 3,219 111.5 50.8 119 154 284.85 161.3

2012-

13 1,868 266 174 4,043 83.7 42.1 99 254 244.50 265.5

2013-

14 2,189 240 202 5,671 60.9 38.4 75 215 290.45 240.0

2014-

15 2,939 669 257 10,752 89.2 99.3 91 294 402.80 668.8

2015-

16 3,227 676 233 12,421 86.3 80.5 62 400 370.15 675.5

2016-

17 3,990 935 237 17,083 162.5 97.9 73 673 739.75 935.0

Mean 2,620 491 212 8,865 99 68 87 332 389 491

SD 931 312 35 5,460 35 28 21 186 182 312

COV 0.36 0.63 0.17 0.62 0.35 0.41 0.24 0.56 0.47 0.63

CAGR

(%) 21.5 42.12 6.6 39.6 7.83 14.0 -9.2 34.3 21.0 42.12

Exhibit-5 (Table.6) depicts that Shree Cements reported the

highest mean value in terms of MPS followed by Ultratech, ACC

etc. Standard deviation of Shree Cement is the highest indicating

the maximum deviation from the Mean value followed by

Ultratech, ACC etc. Both ACC and JK Cement reported the

highest CAGR of 42.12%. Only, Binani Cements reported a

negative CAGR.

Hypothesis:

H0: µ1=µ2=µ3=µ4=µ5=µ6=µ7=µ8=µ9=µ10 (MPS of Cement


H1: µ1≠µ2≠µ3≠µ4≠µ5 ≠µ6≠µ7≠µ8≠µ9≠µ10 (MPS of Cement


Table.7. Exhibit - 6: Market Price Per Share: Anova Single

Factor


Ultratech cement 6 15,719.80 2,619.97 8,67,440.90

ACC 6 2,946.00 491.00 97,066.20

Ambuja cement 6 1,274.90 212.48 1,234.29

Shree cement 6 53,189.85 8,864.98 2,98,13,050.31

India cement 6 593.85 98.98 1,226.11

Prism cement 6 408.90 68.15 774.42

Binani cement 6 519.50 86.58 420.75

Ramco cement 6 1,989.40 331.57 34,715.26

Birla Corp 6 2,332.50 388.75 33,002.10

JK cement 6 2,946.00 491.00 97,066.20


Source of

Variation SS df MS F

P-

value

F

criteri

a

Between

Groups

40,57,23,8

92.35 9

4,50,80,4

32.48

14.5674

5218

3.27E

-11

2.0733

51

Within

Groups

15,47,29,9

82.75 50

30,94,599

.66

Total 56,04,53,8

75.10 59


than the table value (2.073351) in Table.8, therefore null

hypothesis is rejected. Therefore, it is concluded that MPS of

Cement Companies differs over years.

Dividend per Share (DPS): It is an important financial metric

which shows the money a company pays as dividend for each

share. It is the relationship between Dividend Declared and no of

Shares outstanding

Dividend per Share = Total Dividends / Shares Outstanding or

Dividend per Share = Earnings per Share × Dividend Payout

Ratio

Table.9. Exhibit - 7: Dividend Per Share (DPS)


Corp

JK

Cement

2011-12 7.99 24.00 3.17 19.4 2.08 0.50 3.79 2.50 6 5.00

2012-13 9 30 4 20.0 2.01 0.00 3 3.00 7 6.50

2013-14 9.01 33.77 3.59 22.0 0.00 0.00 3.00 0.99 6 3.00

2014-15 9.02 16.89 5.00 24.0 0.00 0.00 2.83 1.49 6 4.00

2015-16 9.51 16.89 2.80 24.0 1.00 0.00 2.83 2.98 6 4.00

2016-17 11.35 16.89 2.45 116.1 1.14 0.00 0.00 2.97 6 8.00

Mean 9 23 3 38 1 0 3 2 6 5

SD 1 7 1 39 1 0 1 1 0 2

COV 0.12 0.32 0.26 1.02 0.88 2.45 0.51 0.38 0.07 0.36

CAGR

(%) 7.3 -6.78 -5.0 43.0 -11.4 -100.0 -100.0 3.5 0.0 9.8

The Exhibit 7 depicts that Shree Cements reported the highest

mean value in terms of DPS followed by ACC, Ultratech etc.

Standard deviation of Shree Cement is the highest indicating the

maximum deviation from the Mean value followed by ACC, JK

Cement etc. Shree Cements reported the highest CAGR of 43%.

ACC, Ambuja, Inia, Prism and Binani Cements reported negative

CAGR.

Hypothesis:

H0: µ1=µ2=µ3=µ4=µ5=µ6=µ7=µ8=µ9=µ10 (DPS of Cement


H1: µ1≠µ2≠µ3≠µ4≠µ5 ≠µ6≠µ7≠µ8≠µ9≠µ10 (DPS of Cement



822

Table.10. Exhibit - 8: Dividend Per Share: Anova Single Factor



ACC 6 138.24 23.04 55.07

Ambuja cement 6 20.58 3.43 0.79

Shree cement 6 225.62 37.60 1,483.47

India cement 6 6.24 1.04 0.84

Prism cement 6 0.50 0.08 0.04

Binani cement 6 15.45 2.57 1.72

Ramco cement 6 13.93 2.32 0.76

Birla Corp 6 37.00 6.17 0.17

JK cement 6 30.51 5.08 3.44


Source of


Between

Groups 7,790.96 9 865.66 5.593791305 2.54E-05 2.073351

Within

Groups 7,737.70 50 154.75

Total 15,528.66 59


than the table value (2.073351) therefore null hypothesis is

rejected. Therefore, it is concluded that DPS of Cement

Companies differs over years.

Dividend Yield: It is a financial ratio that indicates how much

a company pays out as dividends each year relative to its share

price.

Table.12. Exhibit - 9: Dividend Yield (%)


Corp

JK

Cement

2011-12 0.53 14.88 1.84 0.60 1.87 0.99 3.19 1.63 2.11 3.10

2012-13 0.48 11.22 2.05 0.50 2.41 0.00 3.04 1.18 2.86 2.45

2013-14 0.41 14.07 1.78 0.39 0.00 0.00 4.00 0.46 2.07 1.25

2014-15 0.31 2.53 1.94 0.22 0.00 0.00 3.10 0.51 1.49 0.60

2015-16 0.29 2.50 1.21 0.19 1.16 0.00 4.54 0.74 1.62 0.59

2016-17 0.28 1.81 1.03 0.68 0.70 0.00 0.00 0.44 0.81 0.86

Mean 0.38 7.8 1.6 0.43 1.0 0.2 3.0 0.8 1.8 1.5

SD 0.1 6.2 0.4 0.2 1.0 0.4 1.6 0.5 0.7 1.1

COV 0.27 0.79 0.26 0.46 0.96 2.45 0.53 0.58 0.38 0.72

CAGR

(%) -11.7 -34.4 -10.9 2.4 -17.8 -100.0 -100.0 -23.0 -17.4 -22.7

Exhibit 9 depicts that ACC reported the highest mean value in

terms of Dividend Yield followed by Binani Cements, Birla Corp,

Ambuja etc. Standard deviation of ACC is the highest indicating

the maximum deviation from the Mean value followed by Binani,

JK Cement etc. All the Cement Companies reported negative

CAGR except Shree Cements.

Hypothesis:

H0: µ1=µ2=µ3=µ4=µ5=µ6=µ7=µ8=µ9=µ10 (Dividend Yield of

Cement Companies doesn’t differ over years)

H1: µ1≠µ2≠µ3≠µ4≠µ5 ≠µ6≠µ7≠µ8≠µ9≠µ10 (Dividend Yield of

Cement Companies differ over years)

Table.13. Exhibit - 10: Dividend Yield (%): Anova Single

Factor



ACC 6 47.01 7.84 38.62

Ambuja cement 6 9.85 1.64 0.18

Shree cement 6 2.58 0.43 0.04

India cement 6 6.14 1.02 0.97

Prism cement 6 0.99 0.16 0.16

Binani cement 6 17.87 2.98 2.48

Ramco cement 6 4.96 0.83 0.23

Birla Corp 6 10.96 1.83 0.48

JK cement 6 8.85 1.47 1.12

Table.14. Anova: Variation

Source of


Between

Groups 276.11 9 30.68 6.928264531 2.09E-06 2.073351

Within Groups 221.40 50 4.43

Total 497.51 59


than the table value (2.073351) therefore null hypothesis is

rejected. Therefore, it is concluded that DPS of Cement

Companies differs over years.

T-Test: It is used to test the null hypothesis that the variances

of two populations are not equal. If t Stat value lies between - t

Critical two tail and + t Critical two test we don’t reject Null

Hypothesis.

Dividend Policy is one of the major decisions in financial

management. It determines the proportion of earnings to be paid

by way of dividends and the proportion to be ploughed back for

reinvestment purpose.

Every firm must develop a DP i.e., divide its earnings into

dividend and retained earnings in such a way which in turn,

focuses on maximizing its shareholders’ wealth i.e., MPS.

Table.15. Exhibit - 11: T-Test: Two-Sample Assuming Unequal

Variances (Ultratech Cement)

DIY Yield EPS MPS P/E DPR DPS

Mean 0.0038494 88.77 2619.96666 29.6042 0.1053 9.31

Variance 1.109E-06 81.3 867440.901 99.5375 0.0001 1.2453

Observations 6 6 6 6 6 6

Pearson

Correlation -0.732306 0.518067 0.896724 0.734289 0.566807

Hypothesized

Mean Difference 0 0 0 0 0

df 5 5 5 5 5

t Stat -20.4205732 22.917517 6.87340086 5.4090307 -20.3294294

P(T≤t) one-tail 0.00000261 0.0000014 0.00049848 0.0014604 0.00000266

t Critical one-tail 2.01504837 2.0150483 2.01504837 2.0150483 2.01504837

P(T≤t) two-tail 0.00000521 0.00000294 0.00099695 0.00292086 0.00000533

t Critical two-tail 2.57058183 2.57058183 2.57058183 2.57058183 2.57058183


823

Dividend Yield and DPS

H0: µ12 = µ2

2 (There is significant relationship between

Dividend Yield and DPS, Variance is not Equal)

H1: µ12 ≠ µ2

2 (There is significant no relationship between

Dividend Yield and DPS, Variance is Equal)

Here the t Stat value don’t lie between - 2.57058183 and +

2.57058183. Therefore, we accept Null Hypothesis stating that

the variances are unequal.

EPS and DPS

H0: µ12 = µ2

2 (There is significant relationship between EPS

and DPS, Variance is not Equal)

H1: µ12 ≠ µ2

2 (There is significant no relationship between EPS

and DPS, Variance is Equal)




MPS and DPS

H0: µ12 = µ2

2 (There is significant relationship between MPS


H1: µ12 ≠ µ2


MPS and DPS, Variance is Equal)




Price Earnings Ratio and DPS

H0: µ12 = µ2

2 (There is significant relationship between P/E and

DPS, Variance is not Equal)

H1: µ12 ≠ µ2

2 (There is significant no relationship between P/E





DPR and DPS

H0: µ12 = µ2


DPR, Variance is not Equal)

H1: µ12 ≠ µ2


and DPR, Variance is Equal)




Table.16. Exhibit -12: T-test: Two-Sample Assuming Unequal

Variances (ACC)


Mean 0.0783552 51.44 491 12.1277 0.4663 23.04

Variance 3.862E-03 253.9 97066.201 119.1219 0.0155 55.068


Pearson Correlation 0.863881 0.510612 -0.821273 -0.741776 0.411014

Hypothesized Mean

Difference 0 0 0 0 0

df 5 5 5 5 5

t Stat -7.63471689 5.0700082 3.6082575 -1.55810062 -7.50234583

P(T≤t) one-tail 0.00030663 0.0019335 0.0077043 0.08997322 0.00033264


P(T≤t) two-tail 0.00061327 0.0038670 0.0154086 0.17994643 0.00066529



H0: µ12 = µ2



H1: µ12 ≠ µ2






EPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2






MPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2



Here the t Stat value lies between - 2.57058183 and +

2.57058183. Therefore, we reject Null Hypothesis stating that the

variances are not unequal.

Dividend Payout Ratio and DPS

H0: µ12 = µ2

2 (There is significant relationship between DPR


H1: µ12 ≠ µ2


DPR and DPS, Variance is Equal)




Table.17. Exhibit - 13: T-TEST: Two-Sample Assuming

Unequal Variances (Ambuja)


Mean 0.0164180 7.77 212.4833333 28.5361 0.4429 3.43

Variance 1.758E-05 2.2 1234.29066 80.3544 0.0054 0.7874


Pearson Correlation 0.740296 0.797688 0.236409 -0.435513 0.517805

Hypothesized Mean

Difference 0 0 0 0 0

df 5 5 5 5 5

t Stat -9.45607878 11.3264409 14.6586018 6.5529688 -8.5918413

P(T≤t) one-tail 0.0001117 0.0000469 0.00001335 0.0006200 0.0001761


P(T≤t) two-tail 0.0002233 0.0000938 0.00002669 0.0012400 0.0003522



824


H0: µ12 = µ2



H1: µ12 ≠ µ2






EPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2






MPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







Variances (Shree Cement)


Mean 0.0043045 254.43 8864.975 37.9042 0.1413 37.60

Variance 3.935E-06 9,524.0 29813050.3 732.8141 0.0083 1483.47


Pearson

Correlation 0.575608 0.651605 0.769089 0.156322 0.872549

Hypothesized


df 5 5 5 5 5

t Stat -2.3912639 6.79516155 3.98163912 0.01694356 -2.3874131

P(T≤t) one-tail 0.03114510 0.00052533 0.00525678 0.49356848 0.03129389


P(T≤t) two-tail 0.06229021 0.00105067 0.01051356 0.98713696 0.06258777



H0: µ12 = µ2



H1: µ12 ≠ µ2






EPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2






MPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







Variances (India Cement)


Mean 0.0102292 2.54 98.975 -371.2871 0.1797 1.04

Variance 9.690E-05 33.9 1226.1097 894792.955 0.0211 0.8422


Pearson

Correlation 0.956385 0.864874 0.340784 0.560056 0.908625

Hypothesized


df 5 5 5 5 5

t Stat -2.77567256 0.7295077 6.9105609 -0.96466004 -2.67246204

P(T≤t) one-tail 0.01955090 0.2492085 0.0004862 0.18950990 0.02210889


P(T≤t) two-tail 0.03910180 0.4984170 0.0009725 0.37901980 0.04421777



825


H0: µ12 = µ2



H1: µ12 ≠ µ2






EPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2






MPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







Variances (Prism Cement)


Mean 0.0016417 -0.39 68.15 219.8393 -0.2491 0.08

Variance 1.617E-05 0.8 774.418 188622.6317 0.3724 0.0417


Pearson

Correlation 1.000000 0.031252 -0.305434 -0.419158 -1.000000

Hypothesized


df 5 5 5 5 5

t Stat -1.000000 -1.30100328 5.9777635 1.23917754 -1.000000

P(T≤t) one-tail 0.1816087 0.12499141 0.0009385 0.13513641 0.1816087


P(T≤t) two-tail 0.3632174 0.24998283 0.0018770 0.27027281 0.3632174



H0: µ12 = µ2



H1: µ12 ≠ µ2






EPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2






MPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







Variances (Binani Cement)


Mean 0.0297819 -139.70 86.5833333 -0.8756 -0.0264 2.57

Variance 2.482E-04 4,515.7 420.750666 0.5246 0.0006 1.7211


Pearson

Correlation 0.853062 0.242087 0.509168 -0.481696 -0.714016

Hypothesized


df 5 5 5 5 5

t Stat -4.8012622 -5.2096681 10.352902 -4.7537591 -4.7925298

P(T≤t) one-tail 0.0024391 0.0017196 0.0000723 0.0025437 0.0024579


P(T≤t) two-tail 0.0048782 0.0034392 0.0001447 0.0050875 0.0049159



826


H0: µ12 = µ2



H1: µ12 ≠ µ2






EPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2






MPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







Variances (Ramco Cement)


Mean 0.0082695 16.51 331.56667 23.2076 0.1531 2.32

Variance 2.311E-05 69.1 34715.259 156.1308 0.0012 0.7604


Pearson

Correlation 0.396630 0.896575 0.452445 -0.810896 -0.600920

Hypothesized


df 5 5 5 5 5

t Stat -6.51314101 4.6085218 4.3376163 3.8721351 -5.94495177

P(T≤t) one-tail 0.00063745 0.0028976 0.0037228 0.0058674 0.00096190


P(T≤t) two-tail 0.00127489 0.0057953 0.0074456 0.0117348 0.00192380



H0: µ12 = µ2



H1: µ12 ≠ µ2






EPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2






MPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







Variances (Birla Corp)


Mean 0.0182612 26.02 388.75 15.6678 0.2497 6.17

Variance 4.793E-05 45.4 33002.105 46.4534 0.0039 0.1667


Pearson

Correlation 0.733676 0.660707 -0.389001 -0.625506 -0.394883

Hypothesized


df 5 5 5 5 5

t Stat -37.3526763 7.50897268 5.15407143 3.2879788 -33.194295

P(T≤t) one-tail 0.00000013 0.00033128 0.00180129 0.01088099 0.00000023


P(T≤t) two-tail 0.00000026 0.00066256 0.00360258 0.02176199 0.00000047



827


H0: µ12 = µ2



H1: µ12 ≠ µ2






EPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2






MPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







Variances (JK Cement)


Mean 0.0147460 21.53 491 30.8115 0.2720 5.08

Variance 1.115E-04 113.2 97066.20 850.3229 0.0148 3.4404


Pearson

Correlation 0.185105 0.874132 0.391950 -0.298112 -0.325441

Hypothesized


df 5 5 5 5 5

t Stat -6.7022613 4.4435915 3.8292196 2.1171084 -6.2115080

P(T≤t) one-tail 0.0005594 0.0033711 0.0061287 0.0439134 0.0007900


P(T≤t) two-tail 0.0011189 0.0067423 0.0122574 0.0878268 0.0015801



H0: µ12 = µ2



H1: µ12 ≠ µ2






EPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2






MPS and DPS

H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2







H0: µ12 = µ2



H1: µ12 ≠ µ2






5. ANOVA FINDINGS

The study reveals that:

• Shree Cements reported the highest mean value in terms of

Net Profit Margin, EPS, DPS

• The Mean Value of all the Cement Companies are positive

in terms of EPS except Ramco

• In case of MPS, both ACC and JK Cement reported the

highest CAGR of 42.12%

• In case of DPS, Prism Cement reported zero DPS from since

2012. Moreover, ACC, Ambuja, Inia, Prism and Binani

Cements reported negative CAGR.


828

• ACC reported the highest mean value in terms of Dividend

Yield followed by Binani Cements, Birla Corp, Ambuja

T-Test Conducted with selected Cement Firms revealed that,

• There is significant relationship between Dividend Yield

and DPS

• There is significant relationship between EPS and DPS

• There is significant relationship between MPS and DPS

• There is significant relationship between Price Earnings

Ratio and DPS

• There is significant relationship between Dividend Payout

Ratio and DPS

6. CONCLUSION

DPS has significant effect on MPS. When a firm pays

dividend regularly with periodic enhancements, the Shareholders

Wealth gets maximized Retained earnings per share (RPS) act as

an important factor in determining the SW since, increase in RPS

lead to increase in net-worth. Shareholders prefer current dividend

than future income so, dividend is considered to be an important

variable, which maximizes Shareholders Wealth.

REFERENCES

[1] “Cement Sector Analysis Report”, Available at:

https://www.equitymaster.com/research-it/sector-

info/cement/Cement-Sector-Analysis-

Report.asp?utm_source=stockquote.

[2] Sri Ayan Chakraborty, “Value Based Analysis: A Study On

Leading Indian Cement Firms”, International Journal of

Business and Administration Research Review, Vol. 2, No.

21, pp. 39-65, 2018.

[3] J.E. Krishman, “Principles of Investment”, McGraw Hill,

1963.

[4] J. Lintner, “Distribution of Incomes of Corporations among

Dividends, Retained Earnings and Taxes”, The American

Economic Review, Vol. 46, No. 2, pp. 97-113, 1956.

[5] A. Kanwal and S. Kapoor, “Determinants of Dividend

Payout Ratios- A Study of Indian Information Technology

Sector”, International Research Journal of Finance and

Economics, Vol. 7, No. 5, pp. 63-71, 2008.

[6] S. Bose and Z. Husain, “Asymmetric Dividend Policy of

Indian Firms: An Econometric Analysis”, International

Journal of Applied Economics and Finance, Vol. 5, No. 3,

pp. 78-85, 2011.

[7] T.S.F. Alzomania and A. Al-Khadiri, “Determination of

Dividend Policy: The evidence from Saudi Arabia”,

International Journal of Business and Social Science, Vol.

4, No. 1, pp. 181-192, 2013.

[8] H.K. Baker, G.E. Farrelly and R.B. Edelman, “A Survey of

Management Views on Dividend Policy”, Financial

Management, Vol. 14, No. 3, pp. 78-84, 1985.

[9] Chandra Prasanna, “Financial Management Theory and

Practice”, 8th Edition, McGraw Hill Education, 2011.

[10] I.M. Pandey, “Financial Management”, 11th Edition, Vikas,

2018.

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