105 CHAPTER 7 ANALYSIS OF VARIANCE (ANOVA) OF VARIOUS RATIOS FOR THE PLASTIC INDUSTRY OF GUJARAT, AMONG THE COMPANIES DURING THE PERIOD OF STUDY 7.1 Introduction Suppose we have m companies under study and have values on a particular composite ratio (which is useful for studying a particular aspect of performance of a company) for n years’ period, then on the basis of that particular ratio one would like to study (i) the difference or variation in that particular aspect of performance (for which the ratio under study is useful to study) among the m companies over the entire period and (ii) the difference or variation in performance of plastic industry of Gujarat among the n years. In order to study the difference or variation in performance among the companies during different years under study on the basis of a particular ratio, it is necessary to carry out ANOVA for the respective composite ratio of the company during the period of study. In other words if R 1 , R 2 , ........, R n are the values of a particular composite ratio for the companies under study for the n years period then one-way ANOVA on these n values of composite ratios provide us the variation in the performance of the plastic industry in Gujarat on the basis of that particular ratio for the n years period. Just as we study the difference or variation in the performance of a particular aspect of plastic industry in Gujarat during the period of n years on the basis of a ratio, we can also study the difference in performance among the companies strength on the basis of analysis values of the composite ratios of a particular company for the period under study. In other words, if R 1 , R 2 ,...............,R m are the values of a particular composite ratios of n companies for the period under study then one-way ANOVA on these values of that ratios will help us in studying the difference in performance of a particular aspect among the m companies for the period under study. In the sections to follow, the ANOVA for the first of above two aspects the difference or variation in that particular aspect of performance (for which the ratio under study is
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105
CHAPTER 7
ANALYSIS OF VARIANCE (ANOVA) OF VARIOUS RATIOS
FOR THE PLASTIC INDUSTRY OF GUJARAT, AMONG THE
COMPANIES DURING THE PERIOD OF STUDY
7.1 Introduction Suppose we have m companies under study and have values on a particular composite
ratio (which is useful for studying a particular aspect of performance of a company)
for n years’ period, then on the basis of that particular ratio one would like to study (i)
the difference or variation in that particular aspect of performance (for which the ratio
under study is useful to study) among the m companies over the entire period and (ii)
the difference or variation in performance of plastic industry of Gujarat among the n
years.
In order to study the difference or variation in performance among the companies
during different years under study on the basis of a particular ratio, it is necessary to
carry out ANOVA for the respective composite ratio of the company during the period
of study. In other words if R1, R2, ........, Rn are the values of a particular composite
ratio for the companies under study for the n years period then one-way ANOVA on
these n values of composite ratios provide us the variation in the performance of the
plastic industry in Gujarat on the basis of that particular ratio for the n years period.
Just as we study the difference or variation in the performance of a particular aspect of
plastic industry in Gujarat during the period of n years on the basis of a ratio, we can
also study the difference in performance among the companies strength on the basis
of analysis values of the composite ratios of a particular company for the period under
study. In other words, if R1, R2,...............,Rm are the values of a particular composite
ratios of n companies for the period under study then one-way ANOVA on these
values of that ratios will help us in studying the difference in performance of a
particular aspect among the m companies for the period under study.
In the sections to follow, the ANOVA for the first of above two aspects the difference
or variation in that particular aspect of performance (for which the ratio under study is
106
useful to study) among the 15 companies over the entire period of ten years have been
carried out.
7.2 Liquidity Ratios The following liquidity ratios have been studied:
(1) Current ratio
(2) Quick ratio
7.2.1 Current Ratio
ANOVA for Composite Current Ratios among the companies under study (for
the decade) and among the years of the decade (for the companies).
In this subsection ANOVA for composite current ratios among the companies under
study (for a decade) has been carried out on the basis of the data on composite current
ratios furnished in the following table no. - 7.2.1.1
107
Table no. - 7.2.1.1 (Composite Current Ratios) Composite Current Ratios based on Weighted Mean where weight (wi) are Paid-up capital & Ri are Current Ratios
The summary of ANOVA based on the data given in 7.3.1.1 is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Gross Profit Margin Ratio of 15 companies.
H1 = There is significant difference in Gross Profit Ratio of 15 companies.
Table no. - 7.3.1.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance
JBF 10 4084.5354 408.45354 37433.4
Sintex 9 2898.335 322.037222 15460.54
Nilkamal 10 854.7096 85.47096 443.5191
INEOS 3 749.1598 249.719933 1439.527
Essel 10 9147.392 914.7392 74963.42
Plastiblends 9 780.325 86.7027778 737.7024
Gopala 10 104.5895 10.45895 635.3147
Shaily 6 292.0266 48.6711 314.6078
Shree Ram 10 -5679.9294 -567.99294 2441175
Acrysil 10 357.5567 35.75567 230.4961
Jagdamba 6 56.6368 9.43946667 3.046479
Gujarat craft 10 130.2443 13.02443 16.35134
Polylink 10 -28.5411 -2.85411 2955.407
Promact 9 -44.6391 -4.9599 4343.124
Ashish 10 177.74 17.774 94.38935
Table no. - 7.3.1.3 (ANOVA)
Source of Variation SS df MS F P-value F crit
Between Groups 13097394 14 935528.142 4.719934 0.0000 1.777190142
Within Groups 23190324.5 117 198207.901
Total 36287718.5 131 Above table no. – 7.3.1.2 shows descriptive statistics related to the ANOVA. Table no.
- 7.3.1.3 gives sum of square, degree of freedom and mean sum of square for between
115
companies and within companies. For testing the hypothesis by ANOVA procedure, F
– test is applied. In ANOVA table calculated value of F – test with corresponding p –
value is given. F value is 4.719 and p – value is 0.000. Here p – value is less than
0.05. Hence the given hypothesis is rejected i.e. there is significant difference in
Composite Gross Profit Margin Ratios among selected companies.
Conclusion
It is found that the composite gross profit margin ratio was 7.5 for the industry
during the decade.
The highest composite gross profit ratio was 29.24 for Essel Propack and the
lowest was -19.8 for Shree Ram Multi-Tech.
Out of selected companies the composite gross profit ratio of 9 companies
were higher than 7.5 and 6 companies were having lower than 7.5.
All the companies having gross profit margin ratio less than 7.5 belong to
small and mid-cap segment.
Shree Ram Multitech was having most negative gross profit margin ratio
suffering from over capitalization.
9 companies have the gross profit margin ratios in the range of (7 to 29). And 6
have the ratios in the range of (-19 to 5).
7.3.2 Operating Profit Margin Ratio: ANOVA for Composite Operating Profit Margin Ratios among the companies
under study (for the decade).
In this sub section ANOVA for Composite Operating Profit Margin ratios of 15
companies under study (for the decade) has been carried out on the basis of Operating
Profit Margin ratios given from following table no. - 7.3.2.1
116
Table no. - 7.3.2.1 (Composite Operating Profit Margin Ratios) Composite operating profit margin ratios based on weighted mean where weights (Wi) are paid up capital and Ri are ratios
The summary of ANOVA based on the data given in 7.3.2.1 is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Operating Profit Margin Ratios of 15
companies.
H1 = There is significant difference in Operating Profit Margin Ratios of 15
companies.
Table no. - 7.3.2.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance JBF 10 5415.299 541.5299 25796.836
Sintex 9 3539.046 393.22731 17777.021
Nilkamal 10 1100.634 110.06342 1031.9972
INEOS 3 805.9738 268.65793 807.13228
Essel Pro. 10 9889.843 988.98428 48910.202
Plastiblend 9 793.618 88.179778 514.38228
Gopala 10 339.7179 33.97179 970.28878
Shaily 6 541.1445 90.19075 302.43437
Shree Ram 10 3408.081 340.80812 1220708.9
Acrysil 10 473.2032 47.32032 289.04994
Jagdamba 6 72.7288 12.121467 23.243528
Guj. Craft 10 206.3485 20.63485 90.687168
Polylink 10 880.6776 88.06776 1726.4723
Promact 10 272.4441 27.24441 3303.0455
Ashish 10 223.38 22.338 109.16981
Table no. - 7.3.2.3 (ANOVA)
Source of Variation SS df MS F P-value F crit
Between Groups 9973293 14 712378.05 7.0781901 0.0000 1.776457963
Within Groups 11876003 118 100644.1
Total 21849296 132 Above table no. – 7.3.2.2 shows descriptive statistics related to the ANOVA. Table no.
-7.3.2.3 gives sum of square, degree of freedom and mean sum of square for between
118
companies and within companies. For testing the hypothesis by ANOVA procedure, F
– test is applied. In the ANOVA table the calculated value of F – test with
corresponding p – value is given. F value is 7.078 and p – value is 0.00. Here p –
value is less than 0.05. Hence the given hypothesis is rejected i.e. there is significant
difference in Composite Operating Profit Margin Ratios among the selected
companies.
Conclusion
It is found that the composite operating profit margin ratio of the industry
during the decade was 12.58.
The highest composite operating profit margin ratio was 31.61 for Essel
Propack, followed by Sintex 19.08, Acrysil 17.86 and INEOS ABS 15.27. All
these companies belong to large size group except Acrysil India Ltd. It
indicates healthy ratios and efficient management.
The lowest composite operating profit margin ratio among the companies was
3.98 for Gopala Ployplast, followed by Promact 4.64, Ashish 6.57, Gujarat
Craft 6.64. All these companies belong to small and mid-cap segment, these
companies need to reduce the cost of production and to raise the sales.
Out of the selected companies the composite operating profit margin ratio 7
companies were higher than 12.58 and 8 companies have less than 12.58.
The composite operating profit margin ratio was in the range between (4 to
31).
7.3.3 Net Profit Margin Ratio: ANOVA for Composite Net Profit Margin Ratios among the companies under
study (for the decade).
In this sub section ANOVA for Composite Net Profit Margin Ratios among the
companies under study (for the decade) has been carried out on the basis of the data
on composite net profit margin ratios furnished in the following table no. - 7.3.3.1
119
Table no. - 7.3.3.1 (Composite Net Profit Margin Ratios) Composite Net Profit Margin ratios based on weighted mean where weights (Wi) are paid up capital & Ri are ratios
WiRi Company 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 ∑(wiRi) ∑w wei R W
The summary of ANOVA based on the data given in 7.3.3.1 is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Net Profit Ratio of 15 companies.
H1 = There is significant difference in Net Profit Ratio of 15 companies.
Table no. - 7.3.3.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance
JBF 10 1618.1138 161.8114 29840.63
Sintex 9 1937.106 215.234 15242.85
Nilkamal 10 363.8414 36.38414 629.1384
INEOS ABS 10 1125.4082 112.5408 1937.828
Essel Propack 10 4370.2592 437.0259 17423.73
Plastiblend 9 609.558 67.72867 415.0934
Gopala 10 -151.4793 -15.1479 586.3143
Shaily 6 74.5008 12.4168 410.5448
Shree Ram 10 -24549.73 -2454.97 11025160
Acrysil 10 175.6976 17.56976 198.2484
Jagdamba 6 21.34 3.556667 1.779336
Gujarat Craft 10 42.5137 4.25137 19.8549
Polylink 10 -363.4833 -36.3483 21344.65
Promact 9 -666.8979 -74.0998 114086.2
Ashish 10 60.18 6.018 26.74111
Table no. - 7.3.3.3 (ANOVA)
Source of Variation SS Df MS F P-value F crit
Between Groups 61416970 14 4386926 5.390492 0.00000 1.772315666
Within Groups 100914515 124 813826.7
Total 162331484 138
121
Above table no. – 7.3.3.2 shows descriptive statistics related to the ANOVA. Table no.
-7.3.3.3 gives sum of square, degree of freedom and mean sum of square for between
companies and within companies. For testing the hypothesis by ANOVA procedure, F
– test is applied. In ANOVA table calculated value of F – test with corresponding p –
value is given. F value is 5.39 and p – value is 0.00. Here p – value is less than 0.05.
Hence the given hypothesis is rejected i.e. there is significant difference in Composite
Net Profit margin Ratios among the selected companies.
7.3.3(A) ANOVA for Composite Net Profit Margin Ratios among the companies
under study (for the decade) when Shree Ram Multi-tech is excluded from the
analysis.
In this subsection ANOVA for composite Net profit Margin ratios among the 14
companies (i.e. after excluding the company Shree Ram Multitech from the analysis
for the reasons given in the section 6.2.2.3 of chapter-VI) has been carried out on the
basis of the data on composite Net Profit margin ratio furnished in the following table
no.7.3.3(A).1
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Table no. - 7.3.3(A).1 (Composite Net Profit Margin Ratios) Revised Composite Net Profit Margin ratios based on weighted mean where weights (Wi) are paid up capital & Ri are ratios
W 14.025 13.076 13.078 13.085 12.249 13.897 14.554 15.866 15.987 15.996 where, weighted wiwiRiR / nwiW / n = no. of years
Excluding the data of Shree Ram.
123
The summary of ANOVA based on the data given in 7.3.3(A).1 is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Net Profit Ratio of 14 companies.
H1 = There is significant difference in Net Profit Ratio of 14 companies.
Table no.-7.3.3(A).2
Groups Count Sum Average Variance JBF 10 1618.114 161.8114 29840.63
Sintex 9 1937.106 215.234 15242.85
Nilkamal 10 363.8414 36.38414 629.1384
INEOS ABS 10 1125.408 112.5408 1937.828
Essel Propack 10 4370.259 437.0259 17423.73
Plastiblend 9 609.558 67.72867 415.0934
Gopala 10 -151.479 -15.1479 586.3143
Shaily 6 74.5008 12.4168 410.5448
Acrysil 10 175.6976 17.56976 198.2484
Jagdamba 6 21.34 3.556667 1.779336
Gujarat Craft 10 42.5137 4.25137 19.8549
Polylink 10 -363.483 -36.3483 21344.65
Promact 9 -666.898 -74.0998 114086.2
Ashish 10 60.18 6.018 26.74111
Table no. - 7.3.3(A).3 (ANOVA)
Source of Variation SS df MS F P-value F crit
Between Groups 2180906 13 167762 11.42875 0 1.806181
Within Groups 1688079 115 14678.95
Total 3868985 128
Above table no. – 7.3.3(A).1 shows descriptive statistics related to the ANOVA. Table
no. -7.3.3(A).2 gives sum of square, degree of freedom and mean sum of square for
between companies and within companies. For testing the hypothesis by ANOVA
procedure, F – test is applied. In ANOVA table calculated value of F – test with
corresponding p – value is given. F value is 11.43 and p – value is 0.00. Here p –
124
value is less than 0.05. Hence the given hypothesis is rejected i.e. there is significant
difference in Composite Net Profit margin Ratios among the selected companies.
Conclusion
Composite net profit margin ratio was (-3.13) during the decade for the
industry in the company wise comparison which is unhealthy.
The highest composite net profit margin ratio was 13.29 for Essel Propack and
the lowest was -84 for Shree Ram Multi-tech.
Out of selected companies the composite net profit margin ratio of 11
companies was negative.
Due to huge loss of Shree Ram Multi-tech, the whole ratio of composite net
profit margin of the industry became negative. It shows the poor picture of the
industry in terms of performance in net profit margin.
Individual performance of the selected companies was very poor in terms of
net profit margin except Essel Propack during the decade.
In comparison to operating profit margin ratio, the net profit margin ratio was
very poor, it indicates that the operating expenses were rising.
The companies having very poor performance, in net profit belong to small
and mid-cap segment.
From revised table we conclude that
The composite net profit margin ratio for revised table was 2.65 during the
decade for the industry.
The highest composite net profit margin ratio was 9.87 for Plastiblends.
Out of selected companies the composite net profit margin ratio of 8
companies was above 2.65.
7.3.4 Return on Capital Employed: ANOVA for Composite Return on Capital Employed ratios among the companies
under study (for the decade).
In this sub section ANOVA for Composite Return on Capital Employed ratios of 15
companies under study (for the decade) has been carried out on the basis of data on
Return on Capital Employed Ratios given from following table no. - 7.3.4.1
125
Table no. - 7.3.4.1 (Composite ratios of Return on Capital Employed) Composite ratios of Return on Capital Employed based on weighted mean where weights (Wi) are paid up capital & Ri ratios
WiRi Company 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 ∑(wiRi) ∑w wei R W
The summary of ANOVA based on the data given in 7.3.4.1 is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Return on Capital Employed of 15
companies.
H1 = There is significant difference in Return on Capital Employed of 15 companies.
Table no. - 7.3.4.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance JBF 10 6481.7392 648.1739 141575.5
Sintex 9 1965.916 218.4351 6277.363
Nilkamal 10 1100.6993 110.0699 4187.871
INEOS ABS 3 1331.7389 443.913 17763.44
Essel Propack 10 3550.3182 355.0318 9134.195
Plastiblend 9 1387.62 154.18 2030.897
Gopala 10 205.0239 20.50239 4652.865
Shaily 6 350.955 58.4925 508.4298
Shree Ram 10 -859.5612 -85.9561 155779.7
Acrysil 10 510.5727 51.05727 817.1973
Jagdamba 6 67.3464 11.2244 2.298442
Gujarat Craft 10 324.7964 32.47964 25.90814
Polylink 10 515.8191 51.58191 1331.37
Promact 9 239.7165 26.63517 3506.999
Ashish 10 105.706 10.5706 23.06591
Table no. - 7.3.4.3 (ANOVA)
Source of Variation SS df MS F P-value F crit
Between Groups 4725875.85 14 337562.6 13.20742 0.0000 1.77719014
Within Groups 2990351.64 117 25558.56
Total 7716227.5 131 Above table no. – 7.3.4.2 shows descriptive statistics related to the ANOVA. Table
no.-7.3.4.3 gives sum of square, degree of freedom and mean sum of square for
between companies and within companies. For testing the hypothesis by ANOVA
procedure, F – test is applied. In the ANOVA table the calculated value of F – test
with corresponding p – value is given. F value is 13.207 and p – value is 0.000. Here
127
p – value is less than 0.05. Hence the given hypothesis is rejected i.e. there is
significant difference in Composite Return on Capital Employed among selected
companies.
Conclusion
It is found that the composite ratio of return on capital employed for the
industry during the decade was 10.6.
The highest composite ratio of return on capital employed was 25.24 for
INEOS ABS, followed by Plastiblend 23.72, Acrysil 19.27.
The lowest composite ratio of return on capital employed was -3 for Shree
Ram Multi-tech.
The companies among the poor performance in terms of return on capital
employed were Gopala 2.4, Ashish 3.11, Polylink 3.61, Promact 4.5 belong to
small and mid-cap group except Polylink.
Acrysil even though in small cap group maintained consistency in profitability
ratios.
Out of selected companies the composite ratio of return on capital employed, 8
were higher than 10.6 and 9 were lower than 10.6.
Composite ratio of return on capital employed of selected companies were in
the range of (-2 to 25).
7.3.5 Return on Net worth: ANOVA for composite Return on Net Worth Ratios among the companies under
study (for the decade).
In this sub section ANOVA for Composite Return on Net Worth ratios of 15
companies under study (for the decade) has been carried out on the basis of data on
Return on Net Worth given from the following table no. 7.3.5.1
128
Table no. - 7.3.5.1 (Composite ratios of Return on Net Worth) Composite ratios of return on net worth based on weighted mean where weights (Wi) are paid up capital & Ri are ratios
W 14.019 13.076 13.078 13.085 12.249 13.897 14.337 15.743 15.872 15.882 where, weighted wiwiRiR / nwiW / n = no. of years
129
The summary of ANOVA based on the data given in 7.3.5.1 is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Return on Net worth of 15 companies.
H1 = There is significant difference in Return on Net worth of 15 companies.
Table no. - 7.3.5.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance
JBF 10 5498.9216 549.8922 327676.5
Sintex 9 2591.69993 287.9667 24623.76
Nilkamal 10 1194.5208 119.4521 10095.82
INEOS 6 1599.1069 266.5178 10238.03
Essel Pro. 10 2449.0902 244.909 12204.91
Plastiblend 9 1317.94 146.4378 1323.604
Gopala 10 -6009.9882 -600.999 1641930
Shaily 6 316.4778 52.7463 4047.781
Shree Ram 10 46838.1442 4683.814 1.77E+08
Acrysil 10 522.2591 52.22591 1776.215
Jagdamba 6 57.3232 9.553867 16.68376
Guj. Craft 10 206.5662 20.65662 482.869
Polylink 10 17600.2612 1760.026 18604447
Promact 9 21906.5412 2434.06 35846367
Ashish 10 57.052 5.7052 19.34882
Table no. - 7.3.5.3 (ANOVA)
Source of Variation SS df MS F P-value F crit
Between Groups 2.44E+08 14 17428465 1.014264 0.443906201 1.775030638
Within Groups 2.06E+09 120 17183355
Total 2.31E+09 134 Above table no. – 7.3.5.2 shows descriptive statistics related to the ANOVA. Table
no.-7.3.5.3 gives sum of square, degree of freedom and mean sum of square for
between companies and within companies. For testing the hypothesis by ANOVA
procedure, F – test is applied. In the ANOVA table the calculated value of F – test
with corresponding p – value is given. F value is 1.042 and p – value is 0.4439. Here
p – value is greater than 0.05. Hence the given hypothesis is not rejected i.e. there is
130
no significant difference in Composite Return on Net Worth among selected
companies.
Conclusion
It is found that composite return on net worth ratio for the industry was 49.84.
The highest composite return on net worth ratio was 412.24 for Promact. It was
due to the exceptionally high i.e. 1975.27, return on net worth ratio during
2008-09.
The composite return on net worth ratio for Shree Ram was 163.34. It was also
due to the exceptionally high return on net worth ratio i.e. 1601.74 during
2004-05.
The lowest composite return on net worth ratio was -70.48 for Gopala followed
by Ashish 1.68, Gujarat Craft 6.64 considered very low reward to the owners
capital. These companies belong to small and mid-cap group.
Out of the selected companies 3 companies have the composite return on net
worth ratio higher than 49.84 and 12 companies have lower than 49.84.
Three companies achieved higher performance in terms of return on net worth
belong to large cap segment.
7.3.6 Earning per Share ANOVA for Composite Earning per Share Ratios among the companies under
study (for the decade).
In this sub section ANOVA for Earning per Share ratios of 15 companies under study
(for the decade) has been carried out on the basis of data on Earning per Share given
from the following table no. 7.3.6.1.
131
Table no. - 7.3.6.1 (Composite Earning per Share Ratios) Composite Earning per Share ratios based on Weighted mean where weight (Wi) are Paid-up capital & Ri are ratios
WiRi
Company 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 ∑(wiRi) ∑w wei R W
The summary of ANOVA based on the data given in 7.3.6.1 is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Earning per Share Ratio of 15 companies.
H1 = There is significant difference in Earning per Share Ratio of 15 companies.
Table no. - 7.3.6.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance
JBF 10 5132.8034 513.2803 284436.7
Sintex 9 3189.2005 354.3556 24042.82
Nilkamal 10 1831.6845 183.1685 33568.88
INEOS 10 3100.4136 310.0414 33127.72
Essel Pro. 10 2844.17 284.417 38227.84
Plastiblend 9 985.27 109.4744 918.65
Gopala 10 -55.6265 -5.56265 697.8254
Shaily 6 55.3602 9.2267 295.2068
Shree Ram 10 -2381.187 -238.119 231649.9
Acrysil 10 206.6653 20.66653 695.806
Jagdamba 6 38.165 6.360833 15.06303
Guj. Craft 10 30.1984 3.01984 10.81845
Polylink 10 -53.5913 -5.35913 1991.241
Promact 10 -41.8291 -4.18291 992.7068
Ashish 10 7.425 0.7425 0.240746
Table no. - 7.3.6.3 (ANOVA)
Source of Variation SS df MS F P-value F crit
Between Groups 4967661 14 354832.9 7.608118 0.000000 1.771664374
Within Groups 5829840 125 46638.72
Total 10797501 139 Above table no. – 7.3.6.2 shows descriptive statistics related to the ANOVA. Table
no.-7.3.6.3 gives sum of square, degree of freedom and mean sum of square for
between companies and within companies. For testing the hypothesis by ANOVA
procedure, F – test is applied. In the ANOVA table the calculated value of F – test
with corresponding p – value is given. F value is 7.60 and p – value is 0.000. Here p –
133
value is less than 0.05. Hence the given hypothesis is rejected i.e. there is significant
difference in Composite Earning per Share ratios among selected companies.
Conclusion
It is found that the composite ratio of earning per share for the industry for
company wise comparison was 6.57.
The highest composite earning per share ratio was 18.63 for Nilkamal,
followed by INEOS ABS 17.63, Sintex 17.20, Plastiblends 16.84. These
companies belong to large size group while Plastiblends belong to mid size
group.
Out of the selected companies the composite earning per share ratio 8 higher
than 6.57 and 7 companies have lower than 6.57.
Companies among the lowest composite earning per ratio was Shree Ram -8.3,
followed by Promact -0.79, Gopala -0.65, Polylink -0.38, Ashish 0.22 were
poor performers in terms of earning per share ratio. Out of these companies
Ashish belong to small cap segment and the rest belong to large size group.
The composite ratio of earning per share was in the range of (-8.3 to 18.63).
7.4 Activity Ratios The following activity ratios have been studied:
1. Inventory Turnover Ratio
2. Debtors Turnover Ratio
3. Fixed Assets Turnover Ratio
4. Investment Turnover Ratio
7.4.1 Inventory Turnover Ratio: ANOVA for Composite Inventory Turnover Ratios among the companies under
study (for the decade).
In this sub section ANOVA for Composite Inventory Turnover ratios of 15 companies
under study (for the decade) has been carried out on the basis of data on Inventory
Turnover ratios given from following table no. - 7.4.1.1
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Table no. - 7.4.1.1 (Composite Ratios Inventory Turnover) Composite Inventory Turnover ratio based on Weighted Mean where weight (Wi) are Paid-up capital and Ri are ratios
WiRi Company 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 ∑(wiRi) ∑w wei R W
W 14.025 13.076 13.078 13.085 12.249 13.897 14.337 15.743 15.872 15.882 where, weighted wiwiRiR / nwiW / n = no. of years
135
The summary of ANOVA based on the data given in 7.4.1.1 is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Inventory Turnover Ratio of 15 companies.
H1 = There is significant difference in Inventory Turnover Ratio of 15 companies.
Table no. - 7.4.1.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance
JBF 10 18745.8392 1874.584 8357193
Sintex 9 1761.2115 195.6902 12221.61
Nilkamal 10 771.0337 77.10337 407.4342
INEOS 6 838.8671 139.8112 568.8829
Essel Pro. 10 2722.6068 272.2607 11703.86
Plastiblend 9 458.9 50.98889 162.6837
Gopala 10 1275.1548 127.5155 1845.944
Shaily 6 377.1936 62.8656 121.8744
Shree Ram 10 3051.3896 305.139 98448.15
Acrysil 10 142.5778 14.25778 10.60801
Jagdamba 6 57.8072 9.634533 1.02284
Guj. Craft 10 181.6297 18.16297 102.5967
Polylink 10 1794.5073 179.4507 4869.928
Promact 9 404.8101 44.9789 780.896
Ashish 10 148.138 14.8138 28.61769
Table no. - 7.4.1.3 (ANOVA)
Source of Variation SS df MS F P-value F crit
Between Groups 29956404.77 14 2139743 3.361721 0.000142219 1.775030638
Within Groups 76380270.98 120 636502.3
Total 106336675.7 134 Above table no. – 7.4.1.2 shows descriptive statistics related to the ANOVA. Table no.
-7.4.1.3 gives sum of square, degree of freedom and mean sum of square for between
companies and within companies. For testing the hypothesis by ANOVA procedure, F
136
– test is applied. In the ANOVA table the calculated value of F – test with
corresponding p – value is given. F value is 3.361 and p – value is 0.000. Here p –
value is less than 0.05. Hence the given hypothesis is rejected i.e. there is significant
difference in Composite Inventory Turnover ratios among the selected companies.
Conclusion
It is found that the composite inventory turnover ratio for the industry was
11.08.
The highest composite inventory turnover ratio was 42.12 for JBF, followed by
Gopala 14.95, Jagdamba 10.94 and Shree Ram 10.64. These companies belong
to large size group while Jagdamba in a small size group.
The lowest composite inventory turnover ratio was 4.36 for Ashish Polyplast
followed by Acrysil 5.38, Gujarat Craft 5.84, were the poor performers in
inventory turnover ratio. These companies belong to small cap segment.
Out of the selected companies only two companies have the higher inventory
turnover ratio than 11.08 and 13 have lower than 11.08.
The composite inventory turnover ratios were in the range of (4.36 to 42.12).
7.4.2 Debtors Turnover Ratio: ANOVA for Composite Debtors Turnover Ratios among the companies under
study (for the decade).
In this sub section ANOVA for Composite Debtors Turnover ratios of 15 companies
under study (for the decade) has been carried out on the basis of data on Debtors
Turnover ratios given from following table no. - 7.4.2.1
137
Table no. - 7.4.2.1 (Composite Debtors Turnover Ratios) Composite Debtors Turnover Ratios based on Weighted Mean Where weights(wi) are paid-up capital & Ri are Debt Turnover Ratios
WiRi
Company 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 ∑(wiRi) ∑wi wei R W
The summary of ANOVA based on the data given in 7.4.2.1 is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Debtors Turnover Ratio of 15 companies.
H1 = There is significant difference in Debtors Turnover Ratio of 15 companies.
Table no. - 7.4.2.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance
JBF 10 4913.8622 491.3862 47777.65
Sintex 9 865.1984 96.13316 778.9319
Nilkamal 10 711.63 71.163 569.9061
INEOS ABS 10 1062.9637 106.2964 391.9516
Essel Pro. 10 2213.7742 221.3774 2559.432
Plastiblend 9 424.71 47.19 72.40488
Gopala 10 494.2708 49.42708 465.4551
Shaily 6 149.8554 24.9759 39.6601
Shree Ram 10 1580.8786 158.0879 59208.52
Acrysil 10 76.5778 7.65778 9.895523
Jagdamba 6 42.0376 7.006267 1.262626
Gujarat Craft 10 202.0908 20.20908 6.617014
Polylink 4 540.2025 135.0506 4861.754
Promact 7 159.8454 22.83506 318.3225
Ashish 10 1.87 0.187 0.003404
Table no. - 7.4.2.3 (ANOVA)
Source of Variation SS df MS F P-value F crit
Between Groups 2152357.28 14 153739.8 17.44283 0.0000 1.777935098
Within Groups 1022415.37 116 8813.926
Total 3174772.65 130 Above table no. – 7.4.2.2 shows descriptive statistics related to the ANOVA. Table-
7.4.2.3 gives sum of square, degree of freedom and mean sum of square for between
companies and within companies. For testing the hypothesis by ANOVA procedure, F
– test is applied. In the ANOVA table the calculated value of F – test with
corresponding p – value is given. F value is 17.44 and p – value is 0.000. Here p –
139
value is less than 0.05. Hence the given hypothesis is rejected i.e. there is significant
difference in Composite Debtors Turnover among the selected companies.
Conclusion
It is found that the composite debtors turnover ratio for the industry for
company wise comparison was 5.94.
The highest composite debtors turnover ratio was 11.04 for JBF followed by
Polylink 9.07, Jagdamba 7.96 were comparatively good performers.
The lowest composite debtors turnover ratio was 0.055 for Ashish Polymers,
followed by Acrysil 2.89, Promact 3.97 were the poor performers in terms of
debtors turnover ratio.
Out of the selected companies 8 companies have the composite debtors
turnover higher than 5.94 and 7 companies were lower than 5.94.
Companies among poor performers Ashish and Acrysil belong to small size
group while Shaily Engineering and Promact belong to mid-cap group.
The composite debtors turnover ratio of the companies were in the range of
(0.055 to 11.04).
7.4.3 Fixed Assets Turnover Ratio:
ANOVA for Composite Fixed Assets Turnover Ratios among the companies
under study (for the decade).
In this sub section ANOVA for Composite Fixed Assets Turnover ratios of 15
companies under study (for the decade) has been carried out on the basis of data on
Fixed Assets Turnover ratios given from following table no. - 7.4.3.1
140
Table no. - 7.4.3.1 (Composite Fixed Assets Turnover Ratios) Composite Fixed Assets Turnover Ratio based on Weighted Mean where weight (Wi) are Paid-up capital & Ri are ratios
The summary of ANOVA based on the data given in 7.4.3.1 is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Fixed Assets Turnover Ratio of 15
companies.
H1 = There is significant difference in Fixed Assets Turnover Ratio of 15 companies.
Table no. - 7.4.3.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance
JBF 10 1233.5778 123.3578 22257.68
Sintex 9 288.0606 32.00673 76.14929
Nilkamal 10 267.9095 26.79095 39.80682
INEOS 6 247.3154 41.21923 76.69195
Essel Pro. 10 480.7364 48.07364 226.9954
Plastiblend 9 225.285 25.03167 47.82529
Gopala 10 238.7185 23.87185 48.08959
Shaily 6 40.7556 6.7926 5.659611
Shree Ram 10 139.2158 13.92158 243.3728
Acrysil 10 68.2127 6.82127 3.868047
Jagdamba 6 6.1512 1.0252 0.167572
Guj. Craft 10 151.2059 15.12059 61.39014
Polylink 10 250.674 25.0674 120.9508
Promact 9 72.0933 8.010367 19.08216
Ashish 10 61.812 6.1812 19.04492
Table no. - 7.4.3.3 (ANOVA)
Source of Variation SS df MS F P-value F crit
Between Groups 120051 14 8575.057 4.929425 0.000000 1.775030638
Within Groups 208748 120 1739.565
Total 328799 134 Above table no. – 7.4.3.2 shows descriptive statistics related to the ANOVA. Table
no.-7.4.3.3 gives sum of square, degree of freedom and mean sum of square for
between and within companies. For testing the hypothesis by ANOVA procedure, F –
test is applied. In the ANOVA table the calculated value of F – test with corresponding
p – value is given. F value is 4.92 and p – value is 0.000. Here p – value is less than
142
0.05. Hence the given hypothesis is rejected i.e. there is significant difference in
Composite Fixed Assets Turnover among the selected companies.
Conclusion
It is found that the composite fixed assets turnover ratio for the industry was
2.18.
The highest composite fixed assets turnover ratio was 4.86 for Gujarat Craft,
followed by Plastiblends 3.85.
The lowest composite fixed assets turnover ratio was 0.49 for Shree Ram. It
indicate inefficient use of fixed assets.
Out of the selected companies 7 have the ratios higher than 2.18 and 8 have
lower than 2.18.
The composite fixed assets turnover ratios of the selected companies were in
the range of (0.49 to 4.86).
Shree Ram, Shaily and Jagdamba were among the poor performers.
7.4.4 Investment Turnover Ratio:
ANOVA for Composite Investment Turnover Ratios among the companies under
study (for the decade).
In this sub section ANOVA for Composite Investment Turnover ratios of 15
companies under study (for the decade) has been carried out on the basis of data on
Investment Turnover ratios given from following table no. - 7.4.4.1
143
Table no. - 7.4.4.1(Composite Investments Turnover Ratios) Composite Investments Turnover Ratios based on weighted mean where weights (Wi) are paid up capital & Ri are ratios
WiRi Company 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 ∑(wiRi) ∑w wei R W
W 14.025 13.076 13.078 13.085 12.249 13.897 14.554 15.866 15.987 15.996 where, weighted wiwiRiR / nwiW / n = no. of years
144
The summary of ANOVA based on the data given in 7.4.4.1is as follows. For this
ANOVA the H0 and H1 are as follows.
H0 = There is no significant difference in Investment Turnover Ratio among 15
companies.
H1 = There is significant difference in Investment Turnover Ratio among 15
companies.
Table no. - 7.4.4.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance JBF 10 12927.7728 1292.777 279542.1
Sintex 9 1862.0776 206.8975 10791.52
Nilkamal 10 829.7183 82.97183 196.0384
INEOS 10 1864.2533 186.4253 983.2627
Essel Pro. 10 7991.736 799.1736 1774332
Plastiblend 9 500.435 55.60389 255.1627
Gopala 10 1309.6705 130.9671 1716.373
Shaily 6 377.1936 62.8656 121.8744
Shree Ram 10 3474.7934 347.4793 96949.96
Acrysil 10 149.4911 14.94911 8.510929
Jagdamba 6 58.3704 9.7284 1.290824
Guj. Craft 10 183.1733 18.31733 124.8861
Polylink 10 2088.5111 208.8511 3365.35
Promact 9 431.1627 47.90697 723.1206
Ashish 10 128.656 12.8656 51.95403
Table no.-7.4.4.3
Source of Variation SS df MS F P-value F crit Between Groups 17392930.2686 14 1242352 7.895954 0.0000 1.772315666
Within Groups 19510204.5740 124 157340.4
Total 36903134.8426 138
Above table no. – 7.4.4.2 shows descriptive statistics related to the ANOVA. Table
no.-7.4.4.3 gives sum of square, degree of freedom and mean sum of square for
between companies and within companies. For testing the hypothesis by ANOVA
procedure, F – test is applied. In the ANOVA table the calculated value of F – test
145
with corresponding p – value is given. F value is 7.89 and p – value is 0.000. Here p –
value is less than 0.05. Hence the given hypothesis is rejected i.e. there is significant
difference in Composite Investment Turnover among the selected companies.
Conclusion
It is observed that the composite investment turnover ratio for the industry was
11.92.
The highest composite investment turnover ratio was 29.05 for JBF followed
by Essel Propack 25.54, Gopala Polyplast 15.36 and Polylink 14.65 were the
good performers.
The high performers in composite investment turnover ratio belong to large
cap segment.
The lowest composite investment turnover ratio was 3.78 for Ashish Polyplast,
followed by Acrysil 5.64 and Gujarat Craft 5.89. These companies belong to
small cap group.
Out of selected companies 5 of them have composite investment turnover
ratios higher than 11.92 and 10 of them have composite investment turnover
ratios lower than 11.92.
The composite investment turnover ratios were in the range of (3.78 to 29).
7.5 Solvency Ratios The following solvency ratios have been studied:
1. Debt-Equity Ratio
2. Interest Coverage Ratio
7.5.1 Debt-Equity Ratio ANOVA for Composite Debt-Equity Ratios among the companies under study
(for a decade).
In this sub section ANOVA for Composite Debt-Equity ratios of 15 companies under
study (for the decade) has been carried out on the basis of data on Debt-Equity ratios
given from following table no. - 7.5.1.1
146
Table no. - 7.5.1.1 (Composite Debt-Equity Ratios) Composite Debt Equity Ratios based on Weighted Mean where weights (Wi) are Paid-up capital and Ri are ratios
WiRi Company 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 ∑(wiRi) ∑w wei R W
The summary of ANOVA based on the data given in 7.5.1.2 is as follows. For this
ANOVA the H0 and H1 are as follows. H0 = There is no significant difference in Debt-equity Ratios among 15 companies.
H1 = There is significant difference in Debt-equity Ratios among 15 companies.
Table No. - 7.5.1.2 (Summary of statistics for ANOVA)
Groups Count Sum Average Variance
JBF 10 506.794 50.6794 398.6181
Sintex 9 186.8798 20.764422 84.53373
Nilkamal 10 102.8828 10.28828 26.57331
INEOS 2 11.7853 5.89265 11.27793
Essel Pro. 10 145.2 14.52 73.00074
Plastiblend 9 14.235 1.5816667 0.704519
Gopala 10 766.0455 76.60455 18245.55
Shaily 6 79.3536 13.2256 19.83295
Shree Ram 4 128.79 32.1975 219.9681
Acrysil 10 32.9112 3.29112 0.980876
Jagdamba 6 6.0016 1.0002667 0.299032
Guj. Craft 10 46.5567 4.65567 2.652316
Polylink 4 540.2025 135.05063 4861.754
Promact 7 159.8454 22.835057 318.3225
Ashish 10 1.87 0.187 0.003404
Table no. - 7.5.1.3 (ANOVA)
Source of Variation SS df MS F P-value F crit Between Groups 109968 14 7854.8829 4.291933 0.0000 1.789919
Within Groups 186675 102 1830.1504
Total 296644 116 Above table no. - 7.5.1.3 shows descriptive statistics related to the ANOVA. The next
table gives sum of square, degree of freedom and mean sum of square for between
companies and within companies. For testing the hypothesis by ANOVA procedure, F
– test is applied. In the ANOVA table the calculated value of F – test with
corresponding p – value is given. F value is 4.29 and p – value is 0.00. Here p – value
148
is less than 0.05. Hence the given hypothesis is rejected i.e. there is significant
difference in Composite Debt -Equity Ratio among the selected companies.
Conclusion
It is observed that the composite debt-equity ratio for the industry was 2.14
which considered moderate.
The highest composite debt-equity ratio was 9.07 for Polylink followed by
Gopala 8.98.
It indicate high level of borrowed capital.
The lowest composite debt-equity ratio was 0.05 for Ashish Polyplast,
followed by Plastiblends 0.22 and INEOS ABS 0.34. It indicate the owners
capital was more than the borrowed capital and shows less burden of paying
interest and there is scope for trading on equity.
Out of the selected companies 3 have the ratios higher than 2.14 and 12 of
them have the ratios lower than 2.14.
The range of composite debt-equity ratio was (0.05 to 9.07).
7.5.2 Interest Coverage Ratio: ANOVA for Composite Interest Coverage Ratios among the companies under
study (for the decade).
In this sub section ANOVA for Composite Interest Coverage ratios of 15 companies
under study (for the decade) has been carried out on the basis of data on Interest
Coverage ratios given from following table no. 7.5.2.1. The summary of ANOVA
based on the data given in 7.5.2.1 is as follows.
149
Table no. - 7.5.2.1(Composite Ratios of Interest Coverage) Composite Ratios of Interest Coverage based on Weighted Mean where weights (Wi) are Paid-up capital & Ri are ratios
WiRi Company 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 ∑(wiRi) ∑w wei R W