Annals of the „Constantin Brâncuşi” University of TârguJiu, Economy Series, Issue 2/2013

„ACADEMICA BRÂNCUŞI” PUBLISHER, ISSN 1844 – 7007

CLASSIFICATION OF COMPANIES FROM THE PERFORMANCE STANDPOINT USING WARD’S METHOD

Bogeanu Alexandru

Candidate for Doctor's Degree in Accounting

Academy of Economic Studies - Bucharest

alexandru.bogeanu@yahoo.com

ABSTRACT

In this paper I will try to apply an algorithm of hierarchic classification of the economic and financial performance for a group of companies in the

chemical field, listed with the New York Stock Exchange (NYSE), a classification which will be performed taking into consideration the Return on Equity

(ROE), Net income, Economic Value Added (EVA), EVA/Equity and Stock Price. The classification will be performed using the cluster analysis.

KEY-WORDS: Return on equity (ROE), Economic Value Added (EVA), cluster analysis, Nearest Neighbor Method, Ward's linkage.

JEL classification codes: M21; M41; M49.

Introduction ˝The financial rate of return” is the result of the percentage ratio of the net income associated to accounting year (Romanian acronym Rn) and the

value of the firm-owned equity (Romanian acronym CP). The Anglo-Saxon equivalent is the “ROE” index - “Return on equity (return of company-owned

equity).˝1

Rrf = CP

Rn × 100˝

„Return on equity (ROE) is one of the major indexes monitored by investors and management. Using this rate, investors can appreciate to what

extent their investment is profitable or not. In the event that the return on equity is higher than the cost of the owned equity, then, by the performed activity,

the company creates an additional value for shareholders.”2

The economic value added (EVA). ˝The economic value added index (EVA) is a privileged index for performance evaluation, which integrates the

assembly of resource consumption (operational, cost of borrowed capital, and the cost of cost of the owned equity).

EVA simply requires the supplementation of calculation by taking into account the cost of the owned equity.3”

˝The recent disturbances in the financial world only increased the distrust in the „commercial” models used as a basis for measuring the performance

and hierarchy of companies.

A positive value of the EVA index signifies achieving wealth for shareholders in addition to the capital remuneration. A negative value shows the

fact that the company fails to cover the cost of capital from the achieved operational result. In other words, the company loses money even if it reports a

positive accounting result.˝4

„Any company has to achieve, following its activity, a mean rate of return on capital markets, a rate determined under comparable risk conditions. If

a company cannot generate a minimum value of return requested by shareholders, then the said shareholders will place their capital in other fields of activity

or other companies5”.

Distances between items. ˝A presentation of the usual methods for calculating the distances between items (elements or already constituted groups)

follows. The selection of a specific distance modifies the groups which are constituted.˝6

The cluster analysis. ˝The cluster analysis plays an important role within the methods of uncontrolled recognition of forms (also known as non-

supervised learning methods). The purpose of the cluster analysis is represented by data classification (observations or forms) in information structures which

are significant, relevant, called classes, groups or clusters.

Therefore, an essential notion used by the cluster analysis is the cluster. A cluster is defined as a subset of the initial aggregate of items (notes) the

property of which is that the degree of dissimilarity between any of two items which belong to the cluster is lower than the degree of dissimilarity between any

other item belonging to the cluster and any other item which does not belong to that cluster. It is necessary to mention a series of technical explanations.

Firstly, to evaluate the distance (dissimilarity) between items (companies listed in category I) or between clusters, the Manhattan distance will be used. The

Manhattan distance, also called the rectangular distance, the “City-Block“ distance or norm of type L1, is calculated as a sum of the absolute values of the

differences of coordinates of the two items or the two analyzed variables.

1Bogeanu, A., ˝ Relevance of specific tools for an entity’s performance valuation. Study of case: PETROM, a joint stock company ˝ Zigotto Publishing House,

Galaţi, 2010, p. 31 2Vâlceanu, Gh., Robu, V., Georgescu, N., Economic and financial analysis, Economics Publishing House, Bucharest, 2005, p. 281

3Maria Niculescu, Global Strategy Diagnosis, Financial Diagnosis, Economics Publishing House, Bucharest, 2003, p.193

4Bogeanu, A., ˝ Relevance of specific tools for an entity’s performance valuation. Study of case: PETROM, a joint stock company ˝ Zigotto Publishing House,

Galaţi, 2010, p. 36 5Vâlceanu, Gh., Robu, V., Georgescu, N., Economic and financial analysis, Economics Publishing House, Bucharest, 2005, p. 318

6Multi-varied Statistics – Paper No. 12- Classification – SPSS, pp. 7, http://profs.info.uaic.ro/~val/statistica/StatWork_12.pdf; 15.10.2012

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„ACADEMICA BRÂNCUŞI” PUBLISHER, ISSN 1844 – 7007

Secondly, we will use Ward’s method, as a method of hierarchic classification by aggregation. This method is considered the most efficient and the

highest performance method of all the “algorithms” of hierarchic classification as it the only one which explicitly treats the problem of classes

homogenization, that is of minimizing of intra-cluster variability: at every step the two clusters - for which the variability of the resulted cluster is the lowest

of all the possibilities of clusters fusion – are merged. An important premise of Ward’s method is represented by the break-out of the total variance into intra-

cluster variance and inter-cluster variance.˝7

The nearest neighbor method. ˝The distance between two groups is the minimum distance between two elements of the groups (distance between

the nearest elements of different classes). This method uses the calculation of the distance between two groups as the maximum distance between two

elements of the groups (distance between the farthest elements of different classes). The advantage of this method is that it does not agglomerate groups linked

by a chain. Also, the achieved grouping better corresponds to the intuitive grouping (performed by a human operator).˝8

Ward's linkage method. ˝Ward’s linkage is based on the growth of “sum of squares of errors” after the groups are merged into one single group.

Ward’s method selects the groupings which minimize the growth of sum of squares of errors.˝9

Dendrogram. ˝As a result of the algorithm, the classification ranking (dendrogram) is achieved. By the horizontal sectioning of the dendrogram, a

partition of the aggregate of the classified elements is obtained. The components of the partition are the needed classes.˝10

Study of case

To study the companies operating in the field of chemical production, I used the data of a sample of 31 companies, my purpose was to make the

classification of these companies dependant on 5 variables: ROE, Equity, Net income, EVA and Stock Price.

Descriptive Statistics N Range Minimum Maximum Mean Std. Deviation Variance Skewness Kurtosis

ROE 31 9.10 0.0003 9.15 0.50 1.608 2.588 5.439 29.974

Equity 31 84115 92.00 84207.00 5472.06 14990.692 2.247*108 5.148 27.676

Net income 31 23019 7.00 23026.00 1321.65 4109.138 16885016.703 5.239 28.381

EVA 31 2399.84 -68.49 2331.34 337.53 523.317 273861.447 2.383 6.339

Stock Price 31 208.04 8.56 216.60 56.17 48.285 2331.521 2.002 4.657

Valid N 31

Table No.1. My own calculations For the considered 31-company sample, one can find that the mean value of the rate of return is about 50% (0.50), the minimum value being 3%,

reported for FLOTEK INDUSTRIES INC – KPI, and the maximum value is 910%, reported for DOW CHEMICAL – KPI, with a standard deviation of 1,60,

the studied sample displays positive asymmetry, which means that values of the ROE index are in excess of the mean reported value, that is the considered

companies form a heterogeneous group.

Also, the asymmetric distribution of the companies in the chemical industry has a leptokurtosis character, as resulted from the kurtosis, the value of

which is much higher than the same index specific to the perfectly symmetric normal distribution, the value of which is 3.

From the Equity variable standpoint, the analyzed companies report a mean of 5472,06 million $, having a value range from 92.00 million $ -

reported for company CHASE CORP- KPI and the maximum value of 84207.00 million $ - for company FLOTEK INDUSTRIES INC - KPI. The sample of

considered companies is very heterogeneous because the mean square deviation is very high, amounting to 14990.692 million $, the distribution being

asymmetric, and it advances to values higher than the mean liabilities, thus it has a leptokurtosis character, too.

Analyzing the Net income variable, the 31-company sample in the field of chemical industry reported a mean Net income of 1321.65 million $, with

a mean square deviation of 4109,13 million $, the minimum Net income being reported for company LANDEC CORP - KPI, and the maximum Net income

being reported by company DOW CHEMICAL - KPI, the distribution of values being asymmetric towards values higher than the mean Net income, having a

skewness of de 5.23, thus it has a leptokurtosis character with a kurtosis of 28.38.

For the EVA variable, the analyzed companies report a mean value of 337.53 million $, the minimum value being -68.49 million $, reported by

company ASHLAND INC – KPI, and the maximum value is 2331.34 million $, reported for company DU PONT (E I) DE NEMOURS – KPI. The value of

the mean square deviation is 523.317 million $, the value of skewness is 2.383 million $, and the value of kurtosis is 6.339 million $.

As the value of kurtosis is low, we can state that, from the EVA index standpoint, the sample is approximately symmetric, the form of distribution

having a mezzo-kurtosis character.

For the Stock Price variable, the analyzed companies report a mean value of 56.17 $, the value of the minimum Stock Price is 8.56 $ - being reported

by company LANDEC CORP – KPI, and the value of the maximum Stock Price maxim is 216.60 $, bei9ng reported by company NEWMARKET CORP –

KPI. The value of the mean square deviation is 48.285 $, the value of skewness is 2.002 $, and the value of kurtosis is 4.657 $.

From the Stock Price variable standpoint, the considered companies form a homogenous group.

For the sample of analyzed companies, the graphs below show that they have distributions different from the normal traditional distribution

considered in the classical econometrics theory.

7Armeanu, Ş. D., Vintilă, G., Moscalu, M., Filipescu, M. O., Lazăr, P., (2012), ´ Use of techniques of quantitative data analysis for the estimation of corporate

bankruptcy risk´ Theoretical and applied economics, Volume XIX (2012), No. 1(566), pp. 96 8 Multi-varied Statistics – Paper No. 12- Classification – SPSS, pp. 7-8, http://profs.info.uaic.ro/~val/statistica/StatWork_12.pdf; 15.10.2012 9 Multi-varied Statistics – Paper No. 12- Classification – SPSS, pp. 8, http://profs.info.uaic.ro/~val/statistica/StatWork_12.pdf; 15.10.2012

10 Multi-varied Statistics – Paper No. 12- Classification – SPSS, pp. 9, http://profs.info.uaic.ro/~val/statistica/StatWork_12.pdf; 15.10.2012

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Graphs 1-5: Presentation of selection distributions for the analyzed sample.

Elimination of incongruous data

The intended purpose is to identify the classes of companies comprised of companies which are similar from the standpoint of the five tracked indexes,

which are different from the companied in the other classes. To perform a classification by classes, I have used the cluster analysis, the first stage being the

elimination of the dissimilar companies in the analyzed group which report high performance as compared to the rest of the companies. The first stage of the

scientific approach is to perform the classification of companies taking into account the single linkage method to detect the incongruous data in the initial data

matrix. As the variables initially analyzed are measured on different ranges as order of measure, to provide the comparability of information in the company area

(the 31 companies can be considered to form an area named as a rule area of individuals, the classification being done for its elements), I have performed the

standardization of the initial values.

Therefore, the classification process is performed for the standardized values, thus providing the comparability of companies dependant on the analyzed

variables.

Detection of incongruous data is done by applying the superior hierarchical classification, using the single linkage method, taking the square Euclidian

distance as a measure of the dissimilarity among companies.

Based on the classification table and dendogram in Annex No.1, one can find that, of the 31 analyzed companies, the prominent companies are DOW

CHEMICAL – KPI and FLOTEK INDUSTRIES INC – KPI, which are the highest performance ones of the initially analyzed aggregate. The research progress

continued by the elimination of these entities – as shown in the classification dendogram, using the single linkage method, each time the two companies will be

located in a different class, which, though allowed by the theoretical results obtained in the field of classification techniques, is not just from the interpretation

standpoint, as at the limit, each company can be included in a distinct class. In this way one will obtain a subset of the aggregate of the parts of the initial

company list, that is 31 subsets having each an element, however, the consideration of each company as being part of a specific class does not bring any

informational gain.

The classification of the 29 companies left in the initially analyzed 31-company sample is performed by using the classification method proposed by

Ward, taking the square Euclidian distance as the measure of the dissimilarities among the classified items, as this classification method is the best fit for

performing the distribution of companies by classes because it takes into account the variability inside classes, a company being allocated to the class toward

which the space density of companies is minimal .

Annex No.1 Stages of classification using the single linkage method.

Agglomeration Schedule

Stage Cluster Combined Coefficients Stage Cluster First Appears Next Stage

Cluster 1 Cluster 2 Cluster 1 Cluster 2 1 4 5 .030 0 0 2 2 4 30 .034 1 0 4 3 19 31 .043 0 0 4

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4 4 19 .099 2 3 8 5 23 24 .102 0 0 7 6 14 28 .123 0 0 7 7 14 23 .134 6 5 8 8 4 14 .135 4 7 14 9 1 12 .160 0 0 11 10 17 18 .190 0 0 11 11 1 17 .200 9 10 12 12 1 27 .218 11 0 13 13 1 11 .256 12 0 15 14 4 16 .261 8 0 15 15 1 4 .288 13 14 16 16 1 29 .302 15 0 17 17 1 10 .322 16 0 18 18 1 6 .342 17 0 19 19 1 2 .444 18 0 20 20 1 3 .450 19 0 21 21 1 15 .515 20 0 24 22 20 21 .624 0 0 25 23 25 26 .679 0 0 24 24 1 25 .681 21 23 25 25 1 20 1.156 24 22 26 26 1 8 2.198 25 0 27 27 1 7 2.216 26 0 28 28 1 22 2.263 27 0 29 29 1 13 5.388 28 0 30 30 1 9 7.550 29 0 0 Source: My own calculations

Figure No.2 Classification dendogram by the single linkage method

Source: My own analysis

The classification using Ward’s method, as a procedure for class determination leads to the formation of two classes (as shown in Annex No. 2, based on

the table containing the stages of classification and the dendogram obtained for the 29 companies considered this time for analysis):

- The companies in Table No. 2 are allocated to the first class, and the variables ROE, EVA/Equity 2012, Net income 2012, EVA 2012 and Stock Price

2012, have their evolutions presented in graphs 6-13:

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Company Class I TIC Class I ROE Class I EVA/Equity 2012 Class I Equity 2012 Class I Net income 2012 Class I EVA 2012 Class IStock Price 6/30/12 Class I

CALGON CARBON CORP - KPI CCC 10.08% 1.50% 387 39 5.7882 14.22

CHASE CORP - KPI CCF 10.87% 4.21% 92 10 3.8752 13.2

TREDEGAR CORP - KPI TG 5.42% -0.67% 406 22 -2.7049 14.56

LANDEC CORP - KPI LNDC 4.73% 4.45% 148 7 6.5839 8.56

ZOLTEK COS INC - KPI ZOLT 5.84% -4.94% 291 17 -14.3888 9.03

OLIN CORP - KPI OLN 14.47% 5.67% 1016 147 57.6034 20.89

OM GROUP INC - KPI OMG 1.88% 2.93% 1277 24 37.4567 19

GEORGIA GULF CORP - KPI GGC 15.34% 2.05% 528 81 10.8243 25.67

RPM INTERNATIONAL INC - KPI RPM 16.09% 5.16% 1268 204 65.4141 27.2

HAWKINS INC - KPI HWKN 15.29% 8.92% 157 24 14.0067 38.18

ALBEMARLE CORP - KPI ALB 25.36% 16.24% 1723 437 279.8664 59.64

FMC CORP - KPI FMC 31.58% 19.19% 1238 391 237.5689 53.48

INTL FLAVORS & FRAGRANCES - KPI IFF 21.97% 11.71% 1197 263 140.1986 54.8

INNOPHOS HOLDINGS INC - KPI IPHS 21.39% 11.78% 416 89 49.0048 56.46

ROCKWOOD HOLDINGS INC - KPI ROC 20.57% 8.88% 1507 310 133.8666 44.35

EASTMAN CHEMICAL CO - KPI EMN 31.31% 17.87% 2025 634 361.8507 50.37

SIGMA-ALDRICH CORP - KPI SIAL 19.65% 12.74% 2316 455 295.1491 73.93

ECOLAB INC - KPI ECL 7.31% 3.48% 5733 419 199.4035 68.53

CELANESE CORP - KPI CE 42.05% 25.87% 1541 648 398.6072 34.62

AIR PRODUCTS & CHEMICALS INC - KPI APD 20.79% 0.91% 6514 1354 59.5021 80.73

ASHLAND INC - KPI ASH 2.85% -1.58% 4323 123 -68.4913 69.31

GRACE (W R) & CO - KPI GRA 109.96% 123.38% 251 276 309.6766 50.45

PPG INDUSTRIES INC - KPI PPG 26.72% 8.10% 3293 880 266.7016 106.12

PRAXAIR INC - KPI PX 28.50% 9.97% 5940 1693 592.3501 108.73

Table No. 2. Indexes (ROE, EVA/Equity 2012, Equity 2012, Net income 2012, EVA 2012, Stock Price 6/30/12) for the companies of the first class, according to Ward’s method. Graphs 6-13 corresponding to indexes ROE, EVA/Equity 2012, Equity 2012, Net income 2012, EVA 2012, Stock Price 6/30/12, for the companies of

the first class, according to Ward’s method.

38792

406148 291

10161277

528

1268

157

17231238 1197

416

1507

20252316

5733

1541

6514

4323

251

3293

5940

0

1000

2000

3000

4000

5000

6000

7000

CCCCCF TG

LNDC

ZOLT OLNOMG

GGCRPM

HWKNALB FMC IFF

IPHSROC

EMNSIAL

ECL CEAPD

ASHGRA

PPG PX

Equity 2012 Class I

10.08%10.87%5.42%4.73%5.84%

14.47%

1.88%

15.34%16.09%15.29%

25.36%31.58%

21.97%21.39%20.57%

31.31%

19.65%

7.31%

42.05%

20.79%

2.85%

109.96%

26.72%28.50%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

CCCCCF TG

LNDC

ZOLT OLNOMG

GGCRPM

HWKN

ALBFMC IFF

IPHS

ROCEMN

SIAL

ECL CEAPD

ASHGRA

PPG PX

ROE Class I

39 10 22 7 17147

24 81204

24

437 391263

89

310

634

455 419

648

1354

123

276

880

1693

0

200

400

600

800

1000

1200

1400

1600

1800

CCCCCF TG

LNDC

ZOLTOLN

OMGGGC

RPMHW

KNALB FMC

IFF IPHS

ROCEMN

SIAL

ECL CEAPD

ASHGRA

PPG PX

Net income 2012 Class I

1.50%4.21%-0.67%

4.45%-4.94%

5.67%2.93%2.05%5.16%8.92%16.24%19.19%

11.71%11.78%8.88%17.87%

12.74%3.48%

25.87%

0.91%-1.58%

123.38%

8.10%9.97%

-20.00%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

140.00%

CCCCCF TG

LNDC

ZOLT

OLNOMG

GGCRPM

HWKN

ALB FMC IFF IP

HSROC

EMNSIA

LECL CE

APDASH

GRAPPG PX

EVA/Equity 2012 Class I

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- The companies in Table No. 3 are allocated to the second class, and variables ROE, EVA/Equity 2012, Net income 2012, EVA 2012 and Stock Price

2012, have their evolutions presented in graphs 14:

- Table No.3. Indexes (ROE, EVA/Equity 2012, Equity 2012, Net income 2012, EVA 2012, Stock Price 6/30/12) for the companies of the second class,

according to Ward’s method.

39 10 22 7 17

14724

81204

24

437 391

263

89

310

634

455 419

648

1354

123

276

880

1693

5.78823.8752-2.70496.5839-14.388857.603437.456710.8243

65.414114.0067

279.8664237.5689140.1986

49.0048133.8666

361.8507295.1491

199.4035

398.6072

59.5021

-68.4913

309.6766266.7016

592.3501

-200

0

200

400

600

800

1000

1200

1400

1600

1800

CCCCCF TG

LNDC

ZOLT OLNOMG

GGCRPM

HWKN

ALB FMC IFFIP

HSROC

EMNSIA

LECL CE

APDASH

GRAPPG PX

Net income 2012 Class I EVA 2012 Class I

14.2213.2 14.568.56 9.03

20.8919

25.6727.2

38.18

59.6453.4854.8 56.46

44.3550.37

73.9368.53

34.62

80.73

69.31

50.45

106.12108.73

0

20

40

60

80

100

120

CCCCCF TG

LNDCZOLT

OLNOMG

GGCRPM

HWKNALB

FMC IFFIPHS

ROCEMN

SIALECL CE

APDASH

GRAPPG PX

Stock Price 6/30/12 Class I

0.10%

1.00%

10.00%

100.00%

1000.00%

10000.00%

100000.00%

1000000.00%

CCCCCF TG

LNDC

ZOLT OLNOMG

GGCRPM

HWKN

ALBFMC IFF

IPHSROC

EMNSIAL

ECL CEAPD

ASHGRA

PPG PX

ROE Class I EVA/Equity 2012 Class I Equity 2012 Class I Net income 2012 Class I EVA 2012 Class I Stock Price 6/30/12 Class I

-100000.00%

0.00%

100000.00%

200000.00%

300000.00%

400000.00%

500000.00%

600000.00%

700000.00%

ROE Class I EVA/Equity 2012 Class I Equity 2012 Class I Net income 2012 Class I EVA 2012 Class I Stock Price 6/30/12 Class I

CCC CCF TG LNDC ZOLT OLN OMG GGC RPM HWKN ALB FMC IFF

IPHS ROC EMN SIAL ECL CE APD ASH GRA PPG PX

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Company Class II TIC ROE Class II EVA/Equity 2012 Class II Equity 2012 Class II Net income 2012 Class II EVA 2012 Class II Stock Price 6/30/12 Class II

CF INDUSTRIES HOLDINGS INC - KPI CF 32.95% 26.27% 4932 1625 1295.5325 193.74

DU PONT (E I) DE NEMOURS - KPI DD 35.45% 23.41% 9960 3531 2331.3475 50.57

MOSAIC CO - KPI MOS 17.54% 10.16% 11811 2072 1200.4577 54.76

MONSANTO CO - KPI MON 16.02% 9.02% 11994 1921 1081.6338 82.78

NEWMARKET CORP - KPI NEU 36.48% 26.30% 614 224 161.4898 216.6

Graph 14. Corresponds to indexes ROE, EVA/Equity 2012, Equity 2012, Net income 2012, EVA 2012, Stock Price 6/30/12, for the companies of the

second class, according to Ward’s method.

Annex No.2. Stages of classification using Ward’s method

Agglomeration Schedule

Stage Cluster Combined Coefficients Stage Cluster First Appears Next Stage

Cluster 1 Cluster 2 Cluster 1 Cluster 2 1 4 5 .000 0 0 3 2 17 29 .001 0 0 7 3 4 28 .002 1 0 7 4 21 22 .008 0 0 9 5 12 26 .015 0 0 9 6 1 11 .028 0 0 10 7 4 17 .043 3 2 15 8 15 16 .061 0 0 13 9 12 21 .082 5 4 15 10 1 10 .122 6 0 16 11 14 25 .163 0 0 13 12 9 27 .215 0 0 20 13 14 15 .306 11 8 21 14 2 3 .425 0 0 20 15 4 12 .570 7 9 26 16 1 6 .733 10 0 18 17 18 19 .928 0 0 25 18 1 13 1.124 16 0 21 19 23 24 1.354 0 0 23 20 2 9 1.606 14 12 22 21 1 14 2.133 18 13 22 22 1 2 3.128 21 20 23 23 1 23 5.553 22 19 26 24 7 20 8.112 0 0 27

1.00%

10.00%

100.00%

1000.00%

10000.00%

100000.00%

1000000.00%

10000000.00%

NEU MON MOS CF DD

ROE Class II EVA/Equity 2012 Class II Equity 2012 Class II Net income 2012 Class II EVA 2012 Class II Stock Price 6/30/12 Class II

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25 8 18 11.769 0 17 27 26 1 4 18.021 23 15 28 27 7 8 31.906 24 25 28 28 1 7 60.134 26 27 0

Figure No3 Classification dendogram using Ward’s method

Graph No. 15. Distribution by classes of mean performance of the companiea of the two classes

21.25%12.40%

1816.12

356.12143.32

45.92

27.68% 19.00%

7862.2

1874.61214.09

119.69

Class I 21.25% 12.40% 1816.12 356.12 143.32 45.92

Class II 27.68% 19.00% 7862.2 1874.6 1214.09 119.69

Media ROE Media EVA/Equity 2012 Media Equity 2012 Media Net income 2012 Media EVA 2012 Media Stock Price 6/30/12

Conclusions: For the companies of the first class we observe the following aspects:

ROE ranging from 1,88%, corresponding to company OM GROUP INC – KPI to 109,96%, corresponding to company GRACE (W R) & CO – KPI;

ROE mean is 21,25%;

EVA/Equity 2012 ranging from -4,94%, corresponding to company ZOLTEK COS INC – KPI to 123,38%, corresponding to company GRACE (W R)

& CO – KPI; EVA/Equity 2012 mean is 12,40%;

Equity 2012 ranging from 92 million $, corresponding to company CHASE CORP – KPI to 6514 million $, corresponding to company AIR

PRODUCTS & CHEMICALS INC – KPI; Equity 2012 mean is 1816,12 million $;

Net income 2012 ranging from 7 million $, corresponding to company LANDEC CORP – KPI to 1693 million $, corresponding to company PRAXAIR

INC – KPI; Net income 2012 mean is 356,12 million $;

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EVA 2012 ranging from -68,4813 million $, corresponding to company ASHLAND INC – KPI to 592,35 million $, corresponding to company

PRAXAIR INC – KPI; EVA 2012 mean is 143,32 million $; at this economic index we note the fact that, by considering the cost of owned equity, three

companies destroy economic value, according to the following situation:

StocK Price 6/30/2012 ranging from 8,56 $, corresponding to company LANDEC CORP – KPI to 108,73 $, corresponding to company PRAXAIR INC

– KPI; Stock Price mean 6/30/2012 is 45,92 $.

The companies of the first class have the lowest economic performance.

For the companies of the second class we note the following aspects:

ROE ranging from 16,02%, corresponding to company MONSANTO CO – KPI to 36,48%, corresponding to company NEWMARKET CORP - KPI;

ROE mean is 27,68%;

EVA/Equity 2012 ranging from 9,02%, corresponding to company MONSANTO CO – KPI to 26,30%, corresponding to company NEWMARKET

CORP - KPI; EVA/Equity 2012 mean is 19,00%;

Equity 2012 ranging from 614 million $, corresponding to company NEWMARKET CORP - KPI to 11994 million $, corresponding to company

MONSANTO CO – KPI; Equity 2012 mean is 7862,2 million $;

Net income 2012 ranging from 224 million $, corresponding to company NEWMARKET CORP - KPI to 3531 million $, corresponding to company

DU PONT (E I) DE NEMOURS - KPI; Net income 2012 mean is 1874,6 million $;

EVA 2012 ranging from 161,49 million $, corresponding to company NEWMARKET CORP - KPI to 2331,35 million $, corresponding to company DU PONT

(E I) DE NEMOURS - KPI; EVA 2012 mean is 1214,09 million $;

Stock Price 6/30/2012 ranging from 50,57 $, corresponding to company DU PONT (E I) DE NEMOURS - KPI to 216,6 $, corresponding to company

NEWMARKET CORP - KPI; Stock Price mean 6/30/2012 is 119,69 $.

The companies of this class have the highest economic performance.

The poorest company from the standpoint of the analyzed indexes is CALGON CARBON CORP – KPI, and the highest performance company is DU

PONT (E I) DE NEMOURS – KPI.

Graph No.16. Sequence of classification of analyzed companies from the standpoint of the analyzed performance

0

5

10

15

20

25

30

35

CCCCCF TG

LNDC

ZOLT OLNOMG

GGCRPM

PPG PXECL

SIAL

APDASH IFF

IPHS

HWKNROC

ALBFMC

EMN CEGRA CF

NEUMON

MOS DD

Rank

Acknowledgments:

˝This work was co-financed from the European Social Fund through Sectorial Operational Program Human Resources Development 2007-2013,

project number POSDRU/107/1.5/S/77213 „Ph.D. for a career in interdisciplinary economic research at the European standards”

BIBLIOGRAPHY:

Armeanu, Ş. D., Vintilă, G., Moscalu, M., Filipescu, M. O., Lazăr, P., (2012), ´Use of techniques of quantitative data analysis for the estimation of

corporate bankruptcy risk´ Theoretical and applied economics, Volume XIX (2012), No. 1(566), pp. 86-102

Niculescu M. - Global Strategy Diagnosis, Financial Diagnosis, Economics Publishing House, Bucharest, 2005

Parkinson, J. (2004), 'Economic Value Added: Does it Add Value?', International Accountant, May 2004, pp. 36-8. (B)

Vâlceanu Gh., Robu V., Georgescu N. - Economic and financial analysis, “Economics” Publishing House, Bucharest, 2005

Multi-varied Statistics – Paper No. 12 — Classification - SPSS http://profs.info.uaic.ro/~val/statistica/StatWork_12.pdf; 15.10.2012

http://eresearch.fidelity.com/eresearch/evaluate/fundamentals/keyStatistics.jhtml?

http://www.evanomics.com/evastudy.shtml

http://www.gurufocus.com/

www.investopedia.com

Company Class I EVA 2012 Class I

ASHLAND INC - KPI -68.4913

ZOLTEK COS INC - KPI -14.3888

TREDEGAR CORP - KPI -2.7049

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Annals of the „Constantin Brâncuşi” University of TârguJiu, Economy Series, Issue 2/2013

„ACADEMICA BRÂNCUŞI” PUBLISHER, ISSN 1844 – 7007

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