Project Report on tata steel shares

7/31/2019 Project Report on tata steel shares

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1.DETERMINANTS OF SHARE PRICES OF STEEL INDUSTRY

FOR 2007 AND 2011- BASED ON PROFITABILITY RATIOSA

FACTOR ANALYSIS APPROACH

2.COMPARISONS OF PERFORMANCE FROM 2007 TO 2011 OF

TOP FIVE PLAYERS IN STEEL INDUSTRY- ANOVA

APPROACH

PLAYERS :

STEEL AUTHORITY OF INDIA LIMITED(SAIL)

TATA STEEL(TISCO)

ELECTROSTEEL CASTING LIMITED

JINDAL STEEL LIMITED

LLOYD STEEL


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ABSTRACT

The following project tries to examine the primary profitability factors responsible for affecting steel industry in India. Further this paper

attempts to investigate the relative influence of the factors affecting share prices of steel industry and thereby categorizing them. i considered

the following determinants gp margin, np margin, operating profit, return on capital employed, return from long term funds, cash margin etc.

.With the help of multiple regression model and applying Factor analysis the primary factors are traced out. Then using anova i have ranked the

companies and tried to evaluate their performance.

In my project, i have estimated the relationship between share prices of steel industry and some other important profitability factors and got

some interesting results related to this. i have taken into consideration the Multicollinearity problem among different independent variables

and attempted to eliminate it. i have used statistical methods to do the analysis based on yearly basis database of different profitability factors.

Finally i got some relationships of those factors with share prices of steel industry. In my analysis i found that return on capital employed along

with Factor 1i.e; operational efficiency and Factor score 2i.e; investors return are significantly affecting share prices of steel industry.

Key words:Share prices, profitability ratios, Multiple Regression analysis, Multicollinearity , Factor Analysis, Anova.

SOFTWARES USED: SPSS, MS EXCEL.


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STUDENTS INVOLVED

1.RONAL MUKHERJEE (11/MBA/64)

UNDER THE GUIDANCE OF

Dr. Gautam Bandyopadhyay

Associate Professor, NIT,

Durgapur, India

[email protected]


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STEPS INVOLVED IN THE RESEARCH

1. CHECKING THE DISTRIBUTION WHETHER NORMAL OR NOT.

2. SHOWING THAT REGRESSION FAILED

3. FACTOR ANALYSIS FOR YEAR 20114. REGRESSION SUCCESSFUL FOR THE FACTORS

5. NAME THE FACTORS

6. FACTOR ANALYSIS FOR YEAR 2007

7. REGRESSION SUCCESSFUL FOR THE FACTORS

8. NAME THE FACTORS

9. RANK THE COMPANIES USING THE FACTORS FOR 2007 USING ANOVA10. RANK THE COMPANIES USING THE FACTORSFOR 2011 USING ANOVA

11. COMPARE THEIR INDIVIDUAL GROWTH OR DECLINE.


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STEP 1

One-Sample Kolmogorov-Smirnov Test

shareprice

operating profit

margin

profit before

interest and

tax gross profit margin cash profit margin

adjusted cash

profit margin

net profit

margin adjusted net margin

return on capital

employed

return on net

worth adjusted return on net worth

N 25 25 25 25 25 25 25 25 25 25

Normal Parametersa

Mean -19.7200 24.8132 18.1760 13.8124 16.5976 16.6052 12.5348 12.5236 21.5336 20.0532 19.8

Std. Deviation 173.35717 18.05262 13.99259 14.84098 10.61080 10.60423 9.86017 9.88793 18.38057 8.55207 9.11

Most Extreme Differences Absolute .205 .121 .137 .162 .129 .129 .168 .160 .123 .145 .

Positive .176 .121 .109 .108 .108 .100 .132 .131 .123 .145 .

Negative -.205 -.101 -.137 -.162 -.129 -.129 -.168 -. 160 -.076 -.070 -.

Kolmogorov-Smirnov Z 1.023 .604 .685 .810 .644 .643 .842 .799 .614 .725 .

Asymp. Sig. (2-tailed) .246 .858 .736 .527 .802 .803 .477 .546 .845 .670 .

a. Test distribution is Normal.

Since the sig values are all greater than .05 therefore it represents a normal distribution. Hence the following cases of REGRESSION

and FACTOR ANALYSIS and ANOVA can be done.

STEP 2


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Table showing that regression failed

Variables Entered/Removed

b

Model

Variables

Entered

Variables

Removed Method

1 return on long

term funds,

adjusted return

on net worth,

operating profit

margin, gross

profit margin,

cash profit

margin, profit

before interest

and tax, return

on capital

employed, return

on net worth,

adjusted net

margin, adjusted

cash profit

margina

. Enter

a. Tolerance = .000 limits reached.

b. Dependent Variable: shareprice

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .512a

.263 -.264 194.90958


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Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .512a

.263 -.264 194.90958

a. Predictors: (Constant), return on long term funds, adjusted return

on net worth, operating profit margin, gross profit margin, cash profit

margin, profit before interest and tax, return on capital employed,

return on net worth, adjusted net margin, adjusted cash profit margin

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) 142.384 134.737 1.057 .309

operating profit margin 1.083 5.585 .113 .194 .849 .156 6.421

profit before interest and tax -19.248 24.454 -1.554 -.787 .444 .014 73.967

gross profit margin 1.624 4.382 .172 .371 .716 .244 4.099

cash profit margin -220.856 264.498 -13.518 -.835 .418 .000 4.976E3

adjusted cash profit margin 204.591 261.086 12.515 .784 .446 .000 4.843E3

adjusted net margin 41.308 46.804 2.356 .883 .392 .007 135.310

return on capital employed 4.352 28.008 .373 .155 .879 .009 109.150

return on net worth -44.369 47.137 -2.189 -.941 .363 .010 102.661

adjusted return on net worth 40.967 49.139 2.155 .834 .418 .008 126.825

return on long term funds -7.485 23.856 -.727 -.314 .758 .010 101.845

a. Dependent Variable: shareprice

Since all values of tolerance are less than .5 then we can conclude that multicollinearity occurs. This is also evident from the fact that

all t values lie between -2 to +2 and vif values are greater than 2.So factor analysis can be done.


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STEP 3

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .738

Bartlett's Test of Sphericity Approx. Chi-Square 749.184

df 55

Sig. .000

The KMO Bartlett Test Statistic is equal to 0.738 which exceeds 0.5 and hence, the Null hypothesis of spherical matrix is rejected. This conclusion is

further supported by Bartlett Test of sphericity where the 2 statistic is significant at 5% level. Hence non spherical correlation matrix confirms the

presence of multicollinearity.

Table showing factor analysis for year 2011.

Correlation Matrixa,b,c

operating profit

margin

profit before

interest and tax gross profit margin cash profit margin

adjusted cash profit

margin net profit margin

adjusted net

margin

return on capital

employed return on net worth

adjusted return on

net worth

return on long term

funds

Correlation operating profit margin 1.000 .996 .996 .975 .976 .985 .986 .802 -.126 -.187 .801

profit before interest and tax .996 1.000 1.000 .958 .959 .988 .989 .810 -.190 -.256 .795

gross profit margin .996 1.000 1.000 .960 .961 .990 .991 .818 -.200 -.265 .803

cash profit margin .975 .958 .960 1.000 1.000 .971 .974 .863 -.115 -.155 .884

adjusted cash profit margin .976 .959 .961 1.000 1.000 .972 .974 .862 -.117 -.156 .883

net profit margin .985 .988 .990 .971 .972 1.000 1.000 .879 -.249 -.312 .863

adjusted net margin .986 .989 .991 .974 .974 1.000 1.000 .877 -.241 -.303 .862

return on capital employed .802 .810 .818 .863 .862 .879 .877 1.000 -.550 -.567 .988

return on net worth -.126 -.190 -.200 -.115 -.117 -.249 -.241 -.550 1.000 .989 -.459

adjusted return on net worth -.187 -.256 -.265 -.155 -.156 -.312 -.303 -.567 .989 1.000 -.461


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return on long term funds .801 .795 .803 .884 .883 .863 .862 .988 -.459 -.461 1.000

a. Only cases for which year = 2011 are used in the analysis phase.

b. Determinant = .000

Determinant shows that value is tending to zero which shows factor analysis can be available.

Total Variance Explaineda

Compon

ent

Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %

1 8.628 78.438 78.438 8.628 78.438 78.438 8.170 74.269 74.269

2 2.026 18.414 96.852 2.026 18.414 96.852 2.484 22.584 96.852

3 .326 2.968 99.820

4 .020 .180 100.000

5 7.575E-16 6.887E-15 100.000

6 2.607E-16 2.370E-15 100.000

7 2.138E-16 1.943E-15 100.000

8 1.563E-16 1.421E-15 100.000

9 4.128E-18 3.752E-17 100.000

10 -2.574E-16 -2.340E-15 100.000

11 -3.780E-16 -3.437E-15 100.000

Extraction Method: Principal Component Analysis.



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Rotated Component Matrixa,b

Component

1 2

operating profit margin .989

profit before interest and tax .975

gross profit margin .976

cash profit margin .994

adjusted cash profit margin .994

net profit margin .978

adjusted net margin .980

return on capital employed .822 -.512

return on net worth .994

adjusted return on net worth .980

return on long term funds .836


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Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 3 iterations.

b. Only cases for which year = 2011 are used in the

analysis phase.

STEP 4

Table showing that regression model can be fitted after factor analysis.

Variables Entered/Removedb,c

Model

Variables

Entered

Variables

Removed Method

1 return on capital

employed,

REGR factor

score 2 for

analysis 1,

REGR factor

score 1 for

analysis 1a

. Enter

a. All requested variables entered.


c. Models are based only on cases for which year =

2011

Model Summary

Model

R

R Square

Adjusted R

Square

Std. Error of the

Estimate

year = 2011

(Selected)

1 .999a

.997 .988 4.76754

a. Predictors: (Constant), return on capital employed, REGR factor score 2

for analysis 1, REGR factor score 1 for analysis 1


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Coefficientsa,b

Model


Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 6.010 7.676 .783 .577

REGR factor score 1 for

analysis 1 .748 8.162 .017 .092 .942


analysis 1-16.885 5.418 -.387 -3.116 .198

return on capital employed 3.062 .911 .732 3.362 .184


b. Selecting only cases for which year = 2011

STEP 5

Name of the first factor operational

efficiency.

Name of the second factor - investorsreturn

STEP 6

Table showing factor analysis for the year 2007

Correlation Matrixa,b,c

operating profitmargin

profit beforeinterest and tax gross profit margin cash profit margin

adjusted cash profitmargin net profit margin

adjusted netmargin

return on capitalemployed return on net worth

adjusted return onnet worth

return on long termfunds

Correlation operating profit margin 1.000 .989 .644 .998 1.000 .966 .970 .958 .725 .737 .680

profit before interest and tax .989 1.000 .713 .991 .991 .993 .995 .986 .728 .740 .746

gross profit margin .644 .713 1.000 .653 .649 .756 .746 .771 .854 .838 .996

cash profit margin .998 .991 .653 1.000 .999 .974 .976 .957 .709 .718 .692

adjusted cash profit margin 1.000 .991 .649 .999 1.000 .970 .973 .959 .720 .730 .687


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net profit margin .966 .993 .756 .974 .970 1.000 1.000 .986 .707 .716 .788

adjusted net margin .970 .995 .746 .976 .973 1.000 1.000 .989 .709 .720 .777

return on capital employed .958 .986 .771 .957 .959 .986 .989 1.000 .764 .782 .791

return on net worth .725 .728 .854 .709 .720 .707 .709 .764 1.000 .997 .843

adjusted return on net worth .737 .740 .838 .718 .730 .716 .720 .782 .997 1.000 .825

return on long term funds .680 .746 .996 .692 .687 .788 .777 .791 .843 .825 1.000


b. Determinant = .000

Total Variance Explaineda

Compon

ent

Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %

1 9.445 85.862 85.862 9.445 85.862 85.862 6.290 57.185 57.185

2 1.144 10.402 96.263 1.144 10.402 96.263 4.299 39.078 96.263

3 .366 3.332 99.595

4 .045 .405 100.000

5 4.386E-16 3.987E-15 100.000

6 2.920E-16 2.655E-15 100.000

7 1.069E-17 9.719E-17 100.000

8 -7.4 74E-17 -6.795E-16 100.000

9 -1.7 26E-16 -1.569E-15 100.000

10 -2.664E-16 -2.422E-15 100.000

11 -7.791E-16 -7.083E-15 100.000




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Rotated Component Matrixa,b

Component

1 2

operating profit margin .919

profit before interest and tax .904

gross profit margin .897

cash profit margin .923

adjusted cash profit margin .921

net profit margin .883

adjusted net margin .889

return on capital employed .849 .506


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return on net worth .872

adjusted return on net worth .852

return on long term funds .866


Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 3 iterations.

b. Only cases for which year = 2007 are used in the

analysis phase.

STEP 7

Table showing that regression can be done

Variables Entered/Removedb,c

Model

Variables

Entered

Variables

Removed Method

1 REGR factor

score 2 for

analysis 2,

REGR factor

score 1 for

analysis 2, return

on capital

employeda

. Enter

a. All requested variables entered.


c. Models are based only on cases for which year =

2007

Model Summary

Model

R

R Square

Adjusted R

Square

Std. Error of the

Estimate

year = 2007

(Selected)

1 .997a

.993 .973 57.60850

a. Predictors: (Constant), REGR factor score 2 for analysis 2, REGR factor

score 1 for analysis 2, return on capital employed


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Coefficientsa,b

Model


Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) -2193.668 318.228 -6.893 .092

return on capital employed 87.685 13.217 3.543 6.634 .095


analysis 2-1318.124 161.024 -3.771 -8.186 .077


analysis 2-742.661 98.723 -2.125 -7.523 .084


b. Selecting only cases for which year = 2007

STEP 8

Name of the first factor operational efficiency.

Name of the second factor- investors

return

STEP 9

Now we will compare the performance of the companies within the five year period and rank them using ANOVA.

For 2007

ANOVA

Sum of Squares df Mean Square F Sig.


analysis 2

Between Groups 24.848 4 6.212 93.382 .000

Within Groups 1.330 20 .067

Total 26.179 24


analysis 2

Between Groups 8.134 4 2.034 4.463 .010


Total 17.247 24


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return on capital employed Between Groups 5849.219 4 1462.305 12.946 .000

Within Groups 2259.066 20 112.953

Total 8108.285 24

Multiple Comparisons

Tukey HSD

Dependent Variable (I) companyname (J) companyname

Mean Difference

(I-J) Std. Error Sig.

95% Confidence Interval

Lower Bound Upper Bound


analysis 2

sail tisco -1.61467646*

.16312347 .000 -2.1028030 -1.1265499

jindal -1.27227978*

.16312347 .000 -1.7604063 -.7841533

lloyd 1.17571199*

.16312347 .000 .6875855 1.6638385

electrosteel casting -.08577095 .16312347 .984 -.5738975 .4023556

tisco sail 1.61467646*

.16312347 .000 1.1265499 2.1028030

jindal .34239667 .16312347 .259 -.1457298 .8305232

lloyd 2.79038844*

.16312347 .000 2.3022619 3.2785150

electrosteel casting 1.52890550*

.16312347 .000 1.0407790 2.0170320

jindal sail 1.27227978*

.16312347 .000 .7841533 1.7604063

tisco -.34239667 .16312347 .259 -.8305232 .1457298

lloyd 2.44799177*

.16312347 .000 1.9598652 2.9361183


.16312347 .000 .6983823 1.6746354

lloyd sail -1.17571199*

.16312347 .000 -1.6638385 -.6875855

tisco -2.79038844*

.16312347 .000 -3.2785150 -2.3022619

jindal -2.44799177*

.16312347 .000 -2.9361183 -1.9598652

electrosteel casting -1.26148294*

.16312347 .000 -1.7496095 -.7733564

electrosteel casting sail .08577095 .16312347 .984 -.4023556 .5738975

tisco -1.52890550*

.16312347 .000 -2.0170320 -1.0407790

jindal -1.18650883*

.16312347 .000 -1.6746354 -.6983823

lloyd 1.26148294*

.16312347 .000 .7733564 1.7496095


analysis 2

sail tisco 1.45905167*

.42691390 .020 .1815653 2.7365380

jindal .70403294 .42691390 .485 -.5734534 1.9815193

lloyd 1.18775419 .42691390 .076 -.0897321 2.4652405


.42691390 .013 .2661201 2.8210928

tisco sail -1.45905167*

.42691390 .020 -2.7365380 -.1815653

jindal -.75501873 .42691390 .418 -2.0325051 .5224676


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lloyd -.27129748 .42691390 .967 -1.5487838 1.0061888

electrosteel casting .08455478 .42691390 1.000 -1.1929315 1.3620411

jindal sail -.70403294 .42691390 .485 -1.9815193 .5734534

tisco .75501873 .42691390 .418 -.5224676 2.0325051

lloyd .48372125 .42691390 .787 -.7937651 1.7612076

electrosteel casting .83957351 .42691390 .317 -.4379128 2.1170598

lloyd sail -1.18775419 .42691390 .076 -2.4652405 .0897321

tisco .27129748 .42691390 .967 -1.0061888 1.5487838

jindal -.48372125 .42691390 .787 -1.7612076 .7937651

electrosteel casting .35585226 .42691390 .917 -.9216341 1.6333386

electrosteel casting sail -1.54360645*

.42691390 .013 -2.8210928 -.2661201

tisco -.08455478 .42691390 1.000 -1.3620411 1.1929315

jindal -.83957351 .42691390 .317 -2.1170598 .4379128

lloyd -.35585226 .42691390 .917 -1.6333386 .9216341

return on capital employed sail tisco -14.45600 6.72171 .238 -34.5699 5.6579

jindal -19.42800 6.72171 .061 -39.5419 .6859

lloyd 22.89200*

6.72171 .021 2.7781 43.0059

electrosteel casting 7.83400 6.72171 .770 -12.2799 27.9479

tisco sail 14.45600 6.72171 .238 -5.6579 34.5699

jindal -4.97200 6.72171 .944 -25.0859 15.1419

lloyd 37.34800*

6.72171 .000 17.2341 57.4619


6.72171 .025 2.1761 42.4039

jindal sail 19.42800 6.72171 .061 -.6859 39.5419

tisco 4.97200 6.72171 .944 -15.1419 25.0859

lloyd 42.32000*

6.72171 .000 22.2061 62.4339


6.72171 .005 7.1481 47.3759

lloyd sail -22.89200*

6.72171 .021 -43.0059 -2.7781

tisco -37.34800*

6.72171 .000 -57.4619 -17.2341

jindal -42.32000*

6.72171 .000 -62.4339 -22.2061

electrosteel casting -15.05800 6.72171 .206 -35.1719 5.0559

electrosteel casting sail -7.83400 6.72171 .770 -27.9479 12.2799

tisco -22.29000*

6.72171 .025 -42.4039 -2.1761

jindal -27.26200*

6.72171 .005 -47.3759 -7.1481

lloyd 15.05800 6.72171 .206 -5.0559 35.1719


19/28

The mean difference is significant at the 0.05 level.

Homogeneous Subsets

REGR factor score 1 for analysis 2

Tukey HSD

companyname N

Subset for alpha = 0.05

1 2 3

lloyd

5

-

1.3669562

E0

sail

5

-

1.9124418

E-1

electrosteel casting

5

-

1.0547323

E-1

jindal5

1.0810356

E0

tisco5

1.4234323

E0

Sig. 1.000 .984 .259

Means for groups in homogeneous subsets are displayed.

Ranking based on operational efficiency- 1.Tisco

2. Jindal

3 Electrosteel casting

4. Sail5. Lloyd


20/28


Tukey HSD

companyname N


1 2


5

-

1.1619264E

0

tisco

5

-

1.0773716E

0

lloyd 5 -.8060741 -.8060741

jindal 5 -.3223529 -.3223529

sail 5 .3816801

Sig. .317 .076


Ranking based on investor return 1 Sail

2. Jindal

3. Lloyd

4. Tisco5. Electrosteel casting

return on capital employed

Tukey HSD

companyname N


1 2 3

lloyd 5 -1.9900

electrosteel casting 5 13.0680 13.0680

sail 5 20.9020 20.9020

tisco 5 35.3580


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jindal 5 40.3300

Sig. .206 .770 .061


Ranking based on capital employed 1. Jindal

2. Tisco

3. Sail

4 Electrosteel casting

5. lloyd

Step 10

For 2011

ANOVA

Sum of Squares df Mean Square F Sig.


analysis 1

Between Groups 28.249 4 7.062 42.285 .000


Total 31.590 24


analysis 1

Between Groups 14.805 4 3.701 6.065 .002


Total 27.011 24

return on capital employed Between Groups 3888.273 4 972.068 13.908 .000

Within Groups 1397.838 20 69.892

Total 5286.111 24

Multiple Comparisons


22/28

Tukey HSD

Dependent Variable (I) companyname (J) companyname

Mean Difference

(I-J) Std. Error Sig.

95% Confidence Interval

Lower Bound Upper Bound


analysis 1

sail tisco -.50430049 .25847083 .324 -1.2777420 .2691410

jindal -.72893562 .25847083 .071 -1.5023772 .0445059

lloyd 2.10874521*

.25847083 .000 1.3353037 2.8821867

electrosteel casting 1.09136464

*

.25847083 .003 .3179231 1.8648062

tisco sail .50430049 .25847083 .324 -.2691410 1.2777420

jindal -.22463514 .25847083 .905 -.9980767 .5488064

lloyd 2.61304570*

.25847083 .000 1.8396042 3.3864872


.25847083 .000 .8222236 2.3691067

jindal sail .72893562 .25847083 .071 -.0445059 1.5023772

tisco .22463514 .25847083 .905 -.5488064 .9980767

lloyd 2.83768083*

.25847083 .000 2.0642393 3.6111224


.25847083 .000 1.0468587 2.5937418

lloyd sail -2.10874521*

.25847083 .000 -2.8821867 -1.3353037

tisco -2.61304570

*

.25847083 .000 -3.3864872 -1.8396042

jindal -2.83768083*

.25847083 .000 -3.6111224 -2.0642393


.25847083 .007 -1.7908221 -.2439390


.25847083 .003 -1.8648062 -.3179231

tisco -1.59566512*

.25847083 .000 -2.3691067 -.8222236

jindal -1.82030026*

.25847083 .000 -2.5937418 -1.0468587

lloyd 1.01738057*

.25847083 .007 .2439390 1.7908221


analysis 1

sail tisco -.01160045 .49408122 1.000 -1.4900766 1.4668757

jindal -.94308569 .49408122 .345 -2.4215618 .5353904

lloyd .28782533 .49408122 .976 -1.1906508 1.7663014

electrosteel casting 1.45337608 .49408122 .055 -.0251000 2.9318522

tisco sail .01160045 .49408122 1.000 -1.4668757 1.4900766

jindal -.93148524 .49408122 .356 -2.4099613 .5469909

lloyd .29942578 .49408122 .972 -1.1790503 1.7779019


jindal sail .94308569 .49408122 .345 -.5353904 2.4215618

tisco .93148524 .49408122 .356 -.5469909 2.4099613


23/28

lloyd 1.23091102 .49408122 .132 -.2475651 2.7093871


.49408122 .001 .9179857 3.8749379

lloyd sail -.28782533 .49408122 .976 -1.7663014 1.1906508

tisco -.29942578 .49408122 .972 -1.7779019 1.1790503

jindal -1.23091102 .49408122 .132 -2.7093871 .2475651


electrosteel casting sail -1.45337608 .49408122 .055 -2.9318522 .0251000

tisco -1.46497653 .49408122 .053 -2.9434526 .0134996

jindal -2.39646177*

.49408122 .001 -3.8749379 -.9179857

lloyd -1.16555076 .49408122 .168 -2.6440269 .3129254

return on capital employed sail tisco 12.77600 5.28742 .152 -3.0459 28.5979

jindal 10.85400 5.28742 .278 -4.9679 26.6759

lloyd 37.68000*

5.28742 .000 21.8581 53.5019


5.28742 .010 4.0561 35.6999

tisco sail -12.77600 5.28742 .152 -28.5979 3.0459

jindal -1.92200 5.28742 .996 -17.7439 13.8999

lloyd 24.90400*

5.28742 .001 9.0821 40.7259


jindal sail -10.85400 5.28742 .278 -26.6759 4.9679

tisco 1.92200 5.28742 .996 -13.8999 17.7439

lloyd 26.82600*

5.28742 .000 11.0041 42.6479


lloyd sail -37.68000*

5.28742 .000 -53.5019 -21.8581

tisco -24.90400*

5.28742 .001 -40.7259 -9.0821

jindal -26.82600*

5.28742 .000 -42.6479 -11.0041


5.28742 .023 -33.6239 -1.9801


5.28742 .010 -35.6999 -4.0561

tisco -7.10200 5.28742 .669 -22.9239 8.7199

jindal -9.02400 5.28742 .452 -24.8459 6.7979

lloyd 17.80200*

5.28742 .023 1.9801 33.6239

*. The mean difference is significant at the 0.05 level.


24/28

Homogeneous Subsets


Tukey HSD

companyname N


1 2 3

lloyd

5

-

1.4828676

E0


5

-

4.6548698

E-1

sail5

6.2587766

E-1

tisco5

1.1301781

E0

jindal 5 1.3548133

E0

Sig. 1.000 1.000 .071


Ranking based on operational efficiency- 1. Jindal

2. Tisco

3. Sail

4. Electrosteel casting

5. Lloyd


25/28


Tukey HSD

companyname N


1 2


5

-

1.0351938E

0

lloyd 5 .1303570 .1303570

sail 5 .4181823 .4181823

tisco 5 .4297827 .4297827

jindal5

1.3612680E

0

Sig. .053 .132


Ranking based on investor return 1. Jindal

2. Tisco

3. Sail

4. Lloyd


return on capital employed

Tukey HSD

companyname N


1 2 3

lloyd 5 -7.6300

electrosteel casting 5 10.1720

tisco 5 17.2740 17.2740

jindal 5 19.1960 19.1960

sail 5 30.0500

Sig. 1.000 .452 .152



26/28

Ranking based on capital employed 1. Jindal

2. Tisco

3. Sail


5. Lloyd

Step 11

Comparison from 2007 to 2011

BASED ON OPERATIONAL EFFICIENCY

YEAR/COMPANY

NAME

TISCO SAIL JINDAL LLOYD ELECTROSTEEL

2007 1 4 2 5 3

2011 2 3 1 5 4


27/28

BASED ON INVESTORS RETURN

YEAR/COMPANY

NAME


2007 4 1 2 3 5

2011 2 3 1 4 5

BASED ON CAPITAL EMPLOYED

YEAR/COMPANY

NAME


2007 2 3 1 5 4

2011 2 3 1 5 4


28/28

CONCLUSION

In the context of Indian economy the appreciation of return on capital employed will bring in more funds which will act as

stimulant to foster growth and in this process the injection of capital flows will affect share prices. It is evident from thecoefficient table that the rise in the return of capital employed has a positive impact on share prices of steel industry.

Due to the constraint on data base we have not considered the impact of political factors and economical factors and

turbulence on share prices of steel industry. Here we have analyzed eleven independent variables but more quantitative

factors can be included in further research.

References:1.Research paper of Dr. Gautam Bandyopadhyay.

2.Spss notes of Dr. Gautam Bandyopadhyay

3.Research methodologyNaresh and Malhotra

Date post:	05-Apr-2018
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Project Report on tata steel shares

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