MODEL OF PREDICTION OF BANKRUPTCIES

JORGE S. ROSILLO C.

MODEL OF PREDICTION OF BANKRUPTCIES OF COLOMBIAN ENTERPRISES ABSTRACT The objective of the article is to define what financial indicators permit to predict with a major certainty a difficult financial situation or a fact waiting a bankruptcy, it will be used the model proposed by professor Altman applied to Colombian case, the purpose is to have some kind of light for previously indicating us an enterprise with troubles and in this way the entrepreneur may take the correctives of the case.

Financial indicators are a control instrument of management very important in enterprises and of great utility for the banks to analyze applications of new credits for their clients, nevertheless they are objected in the sense that they are used in an isolated way and only under judgment of analyst they are integrate under an analysis as Dupont's. Alternatively financial reasons also may be used with multi-variable technical statistics as "Discriminant Analysis” and serve as instrument for predicting situations of danger in the enterprises. If organizations have not an adequate direction will be subjected to environment influences that every day are major as a consequence of globalization of economy, of new technologies, of competitors, etc., Colombian enterprises are not immune to these external agents, hence. It is of a great importance to provide instruments for permitting the diagnosis and if not predicting a possible bankruptcy, in a country where people speak about economical recession on last years and rates of unemployment superior to 20%, what itself reflects that productive growing is inferior to necessities of work of Colombians. Previous aspects justify this article in a country in development that depends of enterprises as generators of employment. On year 1968 professor Edward Altman designed a model for predicting the bankruptcy of enterprises by using the discriminant analysis, his sample took information of 66 manufacturing enterprises from United States and obtained 22 financial reasons an among these he found that 5 contribute in notable way to predictive model, the model correctly classified the 95% of total sample. METHODOLOGY: Discriminant analysis suppose normality in considered variables therefore they must not be used for small samples, the size must be major than 30 for fulfilling with the requisite of normality explicated in Statistical Theorem of Central Limit. Financial statements were initially taken of 150 enterprises for a lapse of 4 years, not all of them had complete information and finally 106 were selected.

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MODEL OF PREDICTION OF BANKRUPTCIES

JORGE S. ROSILLO C.

Of 106 selected enterprises 80 were taken for designing the model, remainder 26 were used for testing it, financial statements corresponding to 4 years were taken and financial reasons averaged, of 80 enterprises used to create the model 50 are strong and 30 weak, of enterprises used as test 15 are strong and 11 are weak. Criteria for classifying enterprises in strong and weak With base in the reasons for each one of the enterprises it was proceeded to order them in accordance with value obtained in indicator, for example:

ENTERPRISE A B C

Acid Test 0.4 0.7 0.6

Debts 70% 75% 50%

Asset Income-yield 12.5% 11.3% 8.4%

For the acid test the higher value is considered as the best one, because it implies a better situation of liquidity, in debts defined in Colombia as Total Liabilities/Total Assets, this indicator is considered better when lower and finally Income-yield of Asset defined as Net Income /Total Asset, this last indicator is considered better when higher, therefore the following classification will exist in accordance to given parameters:

POSITION 1 2 3

Acid Test B C A

Debts C A B

Asset Income-yield A B C

In accordance with previous table Enterprise B would be in the first place in Acid Test, third in debts and second in Income-yield of Asset, similar methodology was used with the 106 enterprises, these enterprises were classified in each one of the reasons with similar criteria to that previously exposed, at last obtained positions are averaged in each one of the ratios for each one of the enterprises and a final value is obtained classifying in the first place the enterprise presenting minor value and so in ascending order. Classified the enterprises, 80 were selected for the model and was proceeded to make a financial diagnosis of each one of them, the reasons were analyzed and considered the first fifty as financially strong and last thirty as weak, with indicators of these 80 enterprises it was proceed to calculate the Discriminant Figure. 12 indicators were used for calculation of discriminant figure, current ratio, acid test, liquidness ratio, debts, charge period days, inventory days, rotation of assets, net margin, patrimony income-yield, asset income-yield, short term leverage and long term leverage

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MODEL OF PREDICTION OF BANKRUPTCIES

JORGE S. ROSILLO C.

TABLE #1 CURRENT RATIO, ACID TEST, LIQUIDNESS RATIO AND DEBTS OF 106 ENTERPRISES CURRENT RATIO

CIA.CHOCOLATES ESTACION TERM AGUILA UNIDAS CINE COLOMBIA AEROVIAS INTEGR PAVCO S.A. HOTELES ESTELAR SIDERURGICA MED CEMENTOS CARIBE CALES TOLUVIEJO INV AGRICOLAS CARVAJAL S.A. BAVARIA S.A. MAYAGUEZ S.A. EMPAQUES S.A. ETERNIT ARGOS TERPEL SUR S.A. ESTRA NOEL ING.ESPECIALIZADA FDO GAN.ATLANT INVERSORA COLMENA ETERNIT PACIFICO S.A. FDO GAN. HUILA FDO GAN SUCRE ÉXITO GRAN CADENA ALM FDO GAN SANT CLINICA COLSANITAS CARULLA Y CIA S.A. EQUIPOS Y SERVICIOS TEXTIL DE LOS ANDES CIA. AGR SAN FELIPE M.P. COLSANITAS FDO GAN CALDAS COLTABACO CARTON DE COL COLOMBINA S.A. CEMENTOS VALLE FDO GAN TOLIMA INGENIO DEL CAUCA INVERSIONES VENECIA PALMERAS YARIMA INGENIO CASTILLA FDO GAN QUINDIO CEM PAZ DEL RIO CENTRAL TUMACO MANUELITA S.A. FDO GAN BOYACA HOTEL DE PEREIRA MINEROS ANTIOQUIA FDO GAN CAUCA CEMENTOS RIOCLARO ALUMINIO NACIONAL AGROGUACHAL MAN DE CEMENTO UNIV P BOLIVARIANA SIDERURGICA BOYACA INTEGRAL S.A. PAPELES NACIONALES RICA RONDO S.A. PAGUEMENOS S.A. MODERNA IMPRESORES FDO GAN CAQUETA CONCONCRETO S.A. CARBONES CARIBE FDO GAN META

1.52 1.25 3.75 2.40 1.52 1.79 2.09 1.70 1.89 1.89 2.18 3.70 1.78 1.51 1.46 3.01 3.27 1.01 1.22 2.00 1.35 1.42 4.92 1.12 1.68 6.91 5.22 1.05 1.02 8.52 1.79 0.93 2.17 1.78 2.25 1.25 3.63 2.33 1.36 1.13 0.77 6.46 2.10 9.74 19.14 1.47 14.11 1.27 1.78 1.58 13.16 0.74 1.78 6.76 1.18 1.58 0.98 0.87 0.60 1.55 1.09 1.83 1.04 1.23 1.18 5.26 1.33 1.83 3.25

POS.

54 69 13 23 55 41 31 46 36 35 27 14 45 56 58 20 17 89 74 33 64 59 11 79 47 6 10 83 86 5 40 96 28 44 26 70 15 24 63 78 100 8 30 4 1 57 2 66 42 48 3 102 43 7 75 49 92 97 103 52 81 37 85 71 76 9 65 38 18

ACID TEST

0.80 0.73 3.51 1.17 1.37 1.34 1.47 1.57 0.98 1.30 1.38 2.30 1.70 1.14 1.01 2.23 1.85 0.94 0.67 1.26 0.91 1.42 1.01 1.12 1.13 1.38 0.33 0.24 0.34 3.09 1.70 0.42 0.72 1.00 0.41 1.25 0.37 0.78 0.94 0.78 0.58 1.08 1.62 8.27 0.77 0.83 3.01 0.79 0.97 0.91 0.93 0.54 1.42 0.70 0.57 0.82 0.35 0.46 0.58 0.96 1.08 1.12 0.75 1.05 0.78 0.41 1.20 1.42 0.40

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POS.

61 69 2 30 20 21 14 12 45 25 18 6 10 31 41 7 8 52 73 27 55 17 40 34 32 19 101 105 99 3 9 89 70 42 90 28 96 65 51 64 76 36 11 1 66 59 4 62 46 54 53 80 15 71 77 60 97 86 75 47 35 33 68 38 63 92 29 16 93

LIQUIDNES S RATIO

0.08 0.16 0.02 0.04 0.08 0.07 0.04 0.12 0.07 0.06 0.08 0.03 0.04 0.09 0.02 0.04 0.01 0.03 0.20 0.07 0.06 0.09 0.09 0.08 0.03 0.02 0.02 0.05 0.08 0.05 0.01 0.18 0.05 0.09 0.07 0.07 0.02 0.03 0.03 0.06 0.02 -0.01 0.02 0.03 0.01 0.03 0.09 0.06 0.05 0.02 0.04 0.20 0.03 0.01 0.03 0.02 0.06 0.06 0.25 0.04 0.07 0.02 0.06 0.21 0.02 0.01 0.11 0.03 0.03

POS.

20 7 74 45 21 25 47 8 24 35 17 54 43 16 76 42 96 56 4 29 37 14 15 18 53 72 71 38 19 41 98 5 39 12 26 28 68 60 63 33 85 106 75 58 102 59 13 31 40 80 49 3 62 93 57 70 30 36 1 46 22 79 34 2 82 103 10 51 61

DEBTS

0.11 0.33 0.17 0.23 0.21 0.44 0.20 0.16 0.20 0.10 0.26 0.25 0.20 0.24 0.26 0.18 0.20 0.05 0.47 0.21 0.28 0.57 0.14 0.27 0.28 0.07 0.05 0.31 0.30 0.08 0.36 0.30 0.04 0.33 0.02 0.73 0.18 0.15 0.19 0.35 0.19 0.11 0.29 0.14 0.24 0.24 0.07 0.18 0.36 0.39 0.09 0.11 0.43 0.13 0.35 0.30 0.07 0.37 0.29 0.25 0.70 0.35 0.58 0.75 0.33 0.13 0.63 0.41 0.14

POS.

13 56 23 36 34 76 31 22 29 10 44 41 32 38 43 24 30 3 79 33 46 92 17 45 48 7 4 54 51 8 62 52 2 55 1 103 25 21 27 60 28 12 50 20 37 39 6 26 63 70 9 11 75 15 59 53 5 67 49 42 101 61 93 104 57 16 98 74 18

MODEL OF PREDICTION OF BANKRUPTCIES

CURRENT RATIO

VARELA S.A. CIA. NAC VIDRIOS CONFEC COLOMBIA COOMEVA FDO GAN RISARALDA LISTER ALGOD VILLAVICENCIO EDITORIAL EL GLOBO S.A. EL PAIS S.A CEMENTOS BOYACA S.A. INDUSTRIA COL LLANTAS ENKA DE COLOMBIA S.A. INGENIO RIOPAILA S.A. CEMENTOS DIAMANTE FDO GAN CUNDINAMARCA LACORONA SOFASA COMPLEJO TUR. ESPINAL TEXTILES ESPINAL S.A. ESTRUCTURAS CENO CIA. COL TEJIDOS S.A. FDO GAN CESAR CARIBU INTERNACIONAL SIDERURG. PACIFICO FDO GAN BOLIVAR PAÑOS VICUÑA SANTA FE TEJIDOS EL CONDOR S.A. ACEITES DELSINU DISTRAL S.A. HILANDERIAS MEDELLIN COLOMSAT S.A. FIBRATOLIMA S.A. FABRICATO INDUSTRIAS LEHNER S.A. SETAS COLOMBIANAS TABLEROS DE CALDAS ACERIAS PAZ DEL RIO

POS.

JORGE S. ROSILLO C.

ACID TEST

POS.

LIQUIDNES S RATIO

POS.

DEBTS

POS.

1.23 1.27 2.16 2.50 4.44 1.36 1.08 1.10

72 68 29 22 12 62 82 80

0.95 0.86 1.33 2.50 0.30 0.99 1.01 0.94

48 57 23 5 103 44 39 50

0.06 0.01 0.03 0.11 0.01 0.01 0.01 0.03

32 100 64 9 88 91 104 65

0.47 0.48 0.37 0.50 0.11 0.64 0.81 0.60

80 82 66 84 14 99 105 97

0.86 0.96 2.06

98 93 32

0.56 0.55 1.28

78 79 26

0.02 0.03 0.02

66 50 81

0.41 0.52 0.40

73 85 72

1.57 1.27 0.95 3.02

50 67 95 19

1.07 0.67 0.91 0.32

37 72 56 102

0.02 0.01 0.07 0.01

69 87 23 99

0.36 0.35 0.36 0.14

64 58 65 19

1.01 1.15 0.22

90 77 106

0.46 0.46 0.18

87 85 106

0.02 0.02 0.11

83 77 11

0.52 0.48 0.55

88 83 91

1.02 1.81 0.99 3.42 1.56 1.05 2.25 2.67

88 39 91 16 51 84 25 21

0.86 0.38 0.53 0.34 1.52 0.51 0.38 1.33

58 94 81 98 13 83 95 24

0.01 0.01 0.03 0.01 0.01 0.01 0.04 0.01

101 94 55 105 97 90 48 86

0.39 0.52 0.38 0.22 0.45 0.39 0.25 0.54

69 86 68 35 77 71 40 90

1.96

34

1.33

22

0.02

73

0.48

81

1.39 1.53 1.38 0.50 1.22 0.86 0.77

60 53 61 105 73 99 101

0.41 0.95 0.99 0.50 0.75 0.52 0.45

91 49 43 84 67 82 88

0.01 0.16 0.03 0.07 0.01 0.01 0.02

95 6 52 27 92 89 84

0.60 1.01 0.28 0.58 0.47 0.52 0.72

96 106 47 95 78 87 102

0.58 1.02 0.95

104 87 94

0.27 0.62 0.34

104 74 100

0.02 0.04 0.02

67 44 78

0.53 0.58 0.68

89 94 100

TABLE #2 CHARGE PERIOD DAYS, INVENTORY DAYS, ROTATION OF ASSETS AND NET MARGIN OF 106 ENTERPRISES CPD

CIA.CHOCOLATES ESTACION TERM AGUILA UNIDAS CINE COLOMBIA AEROVIAS INTEGR PAVCO S.A. HOTELES ESTELAR SIDERURGICA MED CEMENTOS CARIBE CALES TOLUVIEJO INV AGRICOLAS CARVAJAL S.A. BAVARIA S.A. MAYAGUEZ S.A. EMPAQUES S.A. ETERNIT ARGOS TERPEL SUR S.A. ESTRA NOEL ING.ESPECIALIZADA

42.16 17.75 115.14 55.59 25.80 27.49 77.83 66.47 46.75 131.82 70.31 141.30 237.57 118.38 60.83 112.58 71.87 222.64 10.52 79.95 57.74 83.58

POS

INVENTORY DAYS

POS

24 6 80 34 12 16 61 49 27 90 53 92 100 83 47 79 54 99 4 62 40 64

62.94 21.08 67.92 106.07 3,242.56 31.57 62.09 89.66 77.76 125.37 128.65 233.84 29.32 82.96 42.59 60.11 104.25 47.85 15.88 77.52 46.56 -

32 11 35 64 106 13 31 50 42 71 73 85 12 45 17 29 62 21 9 41 20 1

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ROT. ASSETS.

0.43 2.01 0.37 0.88 0.53 2.83 0.89 0.33 0.62 0.09 0.49 1.14 0.31 0.25 0.58 0.69 0.52 0.03 3.82 0.86 0.86 2.45

POS

60 7 67 23 50 2 22 72 39 101 53 14 76 85 43 33 52 106 1 26 27 4

NET MARGIN

0.21 0.05 0.21 0.07 0.13 0.04 0.06 0.06 0.05 0.68 0.12 0.09 0.20 0.26 0.11 0.02 0.08 2.75 0.03 0.03 0.06 0.06

POS

9 35 8 23 15 45 28 26 37 2 17 19 10 5 18 60 21 1 58 50 29 27

MODEL OF PREDICTION OF BANKRUPTCIES

POS

INVENTORY DAYS

POS

22.90 88.04 72.51 45.46 26.96 1.76 5.01 67.45 101.88 7.28 47.14 70.10 25.63 43.30 29.82 72.01 90.29 60.56 73.23 26.38 116.21 89.14 33.24 56.32 126.14 50.09 57.07 60.66 36.23 21.67 107.73 36.80 54.86 75.11 12.15 59.88 47.14 87.81 207.41 87.99 55.89 72.68 102.31 31.11 456.85 118.26 39.00 82.33 93.46 122.94 168.29 22.57 93.15 243.23 59.40

9 67 56 26 15 1 2 50 75 3 29 52 11 25 18 55 71 45 58 14 81 68 20 36 87 31 38 46 21 7 78 22 33 59 5 43 28 65 98 66 35 57 76 19 103 82 23 63 74 86 96 8 73 101 41

1,147.25 65.64 567.45 679.58 52.50 55.27 331.65 12.73 35.73 197.27 92.51 188.17 560.62 328.43 54.15 50.90 70.29 867.89 44.37 86.47 748.73 71.14 803.96 84.59 86.39 61.27 1,295.46 176.59 140.76 480.25 130.52 92.33 107.09 95.22 222.81 83.19 1.11 105.15 39.93 107.72 79.98 680.65 471.97 96.22 689.49 55.69 68.66 119.23 587.46 59.99 18.38 33.95

102 1 34 93 95 24 26 87 7 15 82 54 81 1 92 86 25 22 38 100 19 49 98 39 99 47 48 30 104 80 75 90 74 53 66 55 84 46 5 63 16 67 44 96 89 56 97 27 36 69 1 94 28 10 14

0.18 0.14 1.07 0.31 0.13 1.81 1.42 0.58 1.04 1.90 0.07 1.33 0.07 2.59 0.20 0.15 0.43 1.08 0.22 0.37 0.41 0.06 0.30 0.39 0.28 0.21 0.62 0.72 0.21 0.29 0.52 0.60 0.33 0.85 0.16 0.44 0.29 0.58 0.95 0.46 1.85 1.01 0.56 0.37 0.37 0.56 0.29 0.87 0.74 0.64 2.16 0.22 2.01 0.93 1.05

92 97 16 75 98 11 12 45 18 8 102 13 103 3 91 95 59 15 87 68 61 105 77 62 81 89 38 32 90 80 51 40 73 28 94 57 78 44 20 55 9 19 47 65 69 49 79 24 31 37 5 88 6 21 17

0.06 0.36 0.05 0.03 0.25 0.04 0.04 -0.07 0.07 0.02 0.05 0.03 0.03 0.03 0.16 0.16 0.05 0.04 0.42 0.02 0.04 -0.08 0.08 0.04 -0.16 0.05 0.03 0.05 -0.11 0.00 0.12 -0.03 0.15 0.03 -0.03 0.21 0.06 0.00 0.03 0.03 0.01 0.03 0.05 -0.12 0.16 0.02 -0.22 0.00 0.05 -0.00 -0.42 -0.27 0.01 0.05 0.00

25 4 31 53 6 44 46 81 24 61 34 56 55 59 12 11 32 41 3 62 47 83 20 42 91 39 48 38 85 68 16 77 14 51 76 7 30 67 49 54 65 52 40 86 13 63 97 66 36 71 101 99 64 33 70

69.64 56.59 91.50

51 37 72

73.09 106.18 96.40

40 65 57

0.59 0.38 0.68

42 63 35

0.03 0.04 -0.06

57 43 80

151.08 57.10 338.60 48.17

94 39 102 30

102.24 101.62 14.55 482.42

60 59 8 91

0.56 0.35 0.11 0.25

48 70 100 84

-0.03 -0.02 -0.17 -0.37

75 74 92 100

119.19 29.69

84 17

221.88 63.72

83 33

0.60 1.83

41 10

0.08 -0.02

22 73

CPD

FDO GAN.ATLANT INVERSORA COLMENA ETERNIT PACIFICO S.A. FDO GAN. HUILA FDO GAN SUCRE ÉXITO GRAN CADENA ALM FDO GAN SANT CLINICA COLSANITAS CARULLA Y CIA S.A. EQUIPOS Y SERVICIOS TEXTIL DE LOS ANDES CIA. AGR SAN FELIPE M.P. COLSANITAS FDO GAN CALDAS COLTABACO CARTON DE COL COLOMBINA S.A. CEMENTOS VALLE FDO GAN TOLIMA INGENIO DEL CAUCA INVERSIONES VENECIA PALMERAS YARIMA INGENIO CASTILLA FDO GAN QUINDIO CEM PAZ DEL RIO CENTRAL TUMACO MANUELITA S.A. FDO GAN BOYACA HOTEL DE PEREIRA MINEROS ANTIOQUIA FDO GAN CAUCA CEMENTOS RIOCLARO ALUMINIO NACIONAL AGROGUACHAL MAN DE CEMENTO UNIV P BOLIVARIANA SIDERURGICA BOYACA INTEGRAL S.A. PAPELES NACIONALES RICA RONDO S.A. PAGUEMENOS S.A. MODERNA IMPRESORES FDO GAN CAQUETA CONCONCRETO S.A. CARBONES CARIBE FDO GAN META VARELA S.A. CIA. NAC VIDRIOS CONFEC COLOMBIA COOMEVA FDO GAN RISARALDA LISTER ALGOD VILLAVICENCIO EDITORIAL EL GLOBO S.A. EL PAIS S.A CEMENTOS BOYACA S.A. INDUSTRIA COL LLANTAS ENKA DE COLOMBIA S.A. INGENIO RIOPAILA S.A. CEMENTOS DIAMANTE FDO GAN CUNDINAMARCA LACORONA SOFASA

JORGE S. ROSILLO C.

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ROT. ASSETS.

POS

NET MARGIN

POS

MODEL OF PREDICTION OF BANKRUPTCIES

POS

INVENTORY DAYS

POS

26.15

13

52.01

23

0.46

56

-0.06

79

130.92 59.50 75.47 89.16 756.26 64.96 501.50 122.01

89 42 60 69 105 48 104 85

43.05 352.92 103.02 1,292.39 69.94 97.49 3,011.79 159.67

18 88 61 103 37 58 105 79

0.65 0.84 0.32 0.27 0.17 0.57 0.12 0.43

36 29 74 83 93 46 99 58

-0.02 0.00 -0.13 -0.21 -0.16 -0.07 -1.34 -0.20

72 69 87 96 90 82 105 95

194.95

97

146.54

76

0.38

64

-0.19

94

23.69 134.97 4,114.26 128.41 145.82 106.08 89.49

10 91 106 88 93 77 70

79.30 127.93 926.57 1.71 112.21 90.89 119.79

43 72 101 6 68 51 70

0.68 0.87 0.07 0.35 0.37 0.47 0.79

34 25 104 71 66 54 30

-0.17 -0.58 -26.03 -0.13 -0.11 -0.14 -0.03

93 103 106 88 84 89 78

51.34 162.97 60.18

32 95 44

91.51 158.03 159.01

52 77 78

0.15 0.23 0.28

96 86 82

-0.68 -0.27 -0.55

104 98 102

CPD

COMPLEJO TUR. ESPINAL TEXTILES ESPINAL S.A. ESTRUCTURAS CENO CIA. COL TEJIDOS S.A. FDO GAN CESAR CARIBU INTERNACIONAL SIDERURG. PACIFICO FDO GAN BOLIVAR PAÑOS VICUÑA SANTA FE TEJIDOS EL CONDOR S.A. ACEITES DELSINU DISTRAL S.A. HILANDERIAS MEDELLIN COLOMSAT S.A. FIBRATOLIMA S.A. FABRICATO INDUSTRIAS LEHNER S.A. SETAS COLOMBIANAS TABLEROS DE CALDAS ACERIAS PAZ DEL RIO

JORGE S. ROSILLO C.

ROT. ASSETS.

POS

NET MARGIN

POS

TABLE # 3 PATRIMONY INCOME-YIELD, ASSET INCOME-YIELD, SHORT TERM LEVERAGE, LONG TERM LEVERAGE OF 106 ENTERPRISES

CIA.CHOCOLATES ESTACION TERM AGUILA UNIDAS CINE COLOMBIA AEROVIAS INTEGR PAVCO S.A. HOTELES ESTELAR SIDERURGICA MED CEMENTOS CARIBE CALES TOLUVIEJO INV AGRICOLAS CARVAJAL S.A. BAVARIA S.A. MAYAGUEZ S.A. EMPAQUES S.A. ETERNIT ARGOS TERPEL SUR S.A. ESTRA NOEL CARULLA Y CIA S.A. EQUIPOS Y SERVICIOS TEXTIL DE LOS ANDES CIA. AGR SA FELIPE M.P. COLSANITAS FDO GAN CALDAS COLTABACO CARTON DE COL COLOMBINA S.A. CEMENTOS VALLE FDO GAN TOLIMA INGENIO DEL CAUCA INVERSIONES VENECIA PALMERAS YARIMA INGENIO CASTILLA FDO GAN QUINDIO

PATRIM. INCOMEYIELD 0.10 0.15 0.09 0.08 0.09 0.18 0.05 0.03 0.04 0.07 0.08 0.15 0.06 0.09 0.09 0.02 0.05 0.08 0.20 0.04 0.07 0.05 0.00 0.07 0.00 0.26 0.04 0.03 0.03 0.07 0.12 0.01 0.02 -0.01 0.03 0.02 -0.05

POS

15 7 17 21 18 5 40 54 44 31 22 9 35 19 16 58 39 23 4 45 32 38 67 33 69 2 42 52 51 29 12 61 56 75 46 57 82

ASSET INCOMEYIELD 0.09 0.10 0.07 0.06 0.07 0.10 0.04 0.02 0.03 0.06 0.06 0.11 0.05 0.06 0.06 0.02 0.04 0.08 0.11 0.03 0.05 0.04 0.00 0.04 0.00 0.07 0.03 0.02 0.02 0.05 0.09 0.01 0.02 -0.01 0.03 0.02 -0.04

-6-

POS

8 4 10 16 13 5 33 50 41 19 21 2 26 17 18 58 31 9 3 43 27 35 66 32 70 11 40 48 49 30 6 61 57 76 46 54 90

SHORT TERM LEVERAGE 0.09 0.32 0.18 0.21 0.13 0.80 0.26 0.07 0.16 0.05 0.26 0.34 0.15 0.13 0.17 0.14 0.12 0.03 0.55 0.23 0.25 0.41 0.03 0.51 0.02 2.46 0.08 0.06 0.16 0.48 0.17 0.11 0.13 0.03 0.07 0.13 0.06

POS

17 57 39 42 22 90 50 12 33 6 49 59 29 24 36 27 21 3 79 47 48 69 2 78 1 104 14 9 34 76 38 19 25 4 11 23 7

LONG TERM LEVERAGE 0.13 0.50 0.21 0.31 0.28 0.80 0.26 0.19 0.25 0.11 0.36 0.35 0.25 0.32 0.36 0.22 0.25 0.05 0.89 0.26 0.39 0.44 0.04 0.51 0.02 2.69 0.22 0.17 0.23 0.54 0.24 0.12 0.42 0.17 0.33 0.33 0.08

POS

13 55 23 36 35 75 32 22 29 10 43 42 31 37 44 24 30 3 80 33 46 52 2 56 1 104 25 21 26 59 28 12 49 20 39 38 6

MODEL OF PREDICTION OF BANKRUPTCIES

CEM PAZ DEL RIO CENTRAL TUMACO MANUELITA S.A. FDO GAN BOYACA HOTEL DE PEREIRA MINEROS ANTIOQUIA FDO GAN CAUCA CEMENTOS RIOCLARO ALUMINIO NACIONAL AGROGUACHAL MAN DE CEMENTO UNIV P BOLIVARIANA SIDERURGICA BOYACA INTEGRAL S.A. PAPELES NACIONALES RICA RONDO S.A. PAGUEMENOS S.A. MODERNA IMPRESORES FDO GAN CAQUETA CONCONCRETO S.A. CARBONES CARIBE FDO GAN META VARELA S.A. CIA. NAC VIDRIOS CONFEC COLOMBIA COOMEVA FDO GAN RISARALDA LISTER ALGOD VILLAVICENCIO EDITORIAL EL GLOBO S.A. EL PAIS S.A CEMENTOS BOYACA S.A. INDUSTRIA COL LLANTAS ENKA DE COLOMBIA S.A. INGENIO RIOPAILA S.A. CEMENTOS DIAMANTE FDO GAN CUNDINAMARCA LACORONA SOFASA COMPLEJO TUR. ESPINAL TEXTILES ESPINAL S.A. ESTRUCTURAS CENO CIA. COL TEJIDOS S.A. FDO GAN CESAR CARIBU INTERNACIONAL SIDERURG. PACIFICO FDO GAN BOLIVAR PAÑOS VICUÑA SANTA FE TEJIDOS EL CONDOR S.A. ACEITES DELSINU DISTRAL S.A. HILANDERIAS MEDELLIN COLOMSAT S.A. FIBRATOLIMA S.A. FABRICATO INDUSTRIAS LEHNER S.A. SETAS COLOMBIANAS TABLEROS DE CALDAS ACERIAS PAZ DEL RIO

PATRIM. INCOMEYIELD 0.01 0.03 0.06 -0.02 0.00 0.12 -0.02 0.08 0.04 -0.00 0.15 0.03 -0.00 0.13 0.02 0.06 0.08 0.04 -0.04 0.16 0.02 -0.06 0.01 0.07 -0.00 -0.18 -0.07 0.08 0.26 0.01

JORGE S. ROSILLO C.

63 48 37 79 68 13 78 26 41 71 8 47 70 11 55 36 24 43 81 6 59 86 66 28 73 102 88 25 3 64

ASSET INCOMEYIELD 0.01 0.02 0.04 -0.02 0.00 0.07 -0.02 0.05 0.03 -0.00 0.09 0.02 -0.00 0.04 0.02 0.03 0.03 0.03 -0.04 0.07 0.01 -0.06 0.00 0.04 -0.00 -0.09 -0.06 0.03 0.05 0.01

64 52 36 79 68 14 78 28 45 73 7 51 71 37 55 44 38 47 84 15 63 95 67 34 72 100 94 42 29 65

SHORT TERM LEVERAGE 0.16 0.26 0.23 0.05 0.10 0.76 0.12 0.16 0.34 0.06 0.70 0.22 0.26 2.30 0.23 1.14 3.20 0.35 0.15 1.47 0.59 0.14 0.68 0.67 0.35 1.38 0.08 1.51 4.18 0.56

32 52 46 5 18 88 20 35 58 10 87 43 51 103 45 96 105 61 28 99 81 26 86 85 60 97 15 101 106 80

LONG TERM LEVERAGE 0.24 0.56 0.65 0.10 0.12 0.76 0.15 0.54 0.44 0.08 0.81 0.43 0.34 2.35 0.55 1.40 3.22 0.51 0.15 1.81 0.71 0.16 0.89 0.93 0.59 1.40 0.13 1.79 5.14 1.54

0.03 0.03 -0.06

53 50 85

0.02 0.02 -0.04

53 56 86

0.42 0.31 0.36

71 56 64

0.69 1.08 0.67

72 83 70

-0.01 -0.01 -0.00 -0.10

74 76 72 94

-0.00 -0.01 0.01 -0.09

74 75 59 102

0.39 0.21 0.17 0.15

67 41 37 30

0.56 0.53 0.67 0.17

62 58 69 19

0.14 -0.12 -0.06

10 96 84

0.05 -0.03 -0.03

22 83 81

1.11 0.98 0.88

95 94 93

1.11 1.11 1.23

86 87 90

-0.02 0.01 -0.07 -0.07 -0.05 -0.08 -0.06 -0.20

77 65 89 90 83 91 87 103

-0.01 0.00 -0.04 -0.06 -0.03 -0.04 -0.05 -0.09

77 69 87 93 82 89 91 101

0.64 0.82 0.29 0.27 0.60 0.46 0.28 0.36

84 92 55 53 82 75 54 62

0.64 1.08 0.64 0.27 0.83 0.69 0.34 1.21

67 84 66 34 77 71 40 89

-0.14

100

-0.07

98

0.45

73

0.94

82

-0.26 -0.08 -0.12 -0.11 -0.08 -0.14 -0.12

105 93 98 95 92 99 97

-0.11 -0.43 -0.09 -0.05 -0.04 -0.06 -0.02

104 106 99 92 88 97 80

0.41 1.48 0.22 0.81 0.42 0.63 1.69

70 100 44 91 72 83 102

1.50 1.57 0.39 1.42 0.89 1.10 2.68

96 98 47 95 78 85 103

-0.22 -0.16 -0.44

104 101 106

-0.10 -0.06 -0.14

103 96 105

0.36 0.49 0.78

63 77 89

1.15 1.41 2.24

88 93 101

POS

POS

POS

POS

27 63 68 9 11 74 15 60 53 5 76 50 41 102 61 91 105 57 16 100 73 17 79 81 64 92 14 99 106 97

With base in information of tables 1, 2 and 3 the average of positions was determined for each one of the enterprises, the one with the best results was Compañía Nacional de Chocolates and the one with poorest was Acerías Paz del Río, general classification may be observed in the following table ( # 4)

-7-

MODEL OF PREDICTION OF BANKRUPTCIES

JORGE S. ROSILLO C.

TABLE # 4 AVERAGE POSITION OF EACH ENTERPRISE IN ACCORDANCE WITH 12 CONSIDERED INDICATORS AVERAGE POSITION CIA. NACIONAL DE CHOCOLATES S.A. ESTACION TERM.DE DIST. DE PROD. DE PETR. CERVECERIA AGUILA S.A. INDUSTRIAS METALURGICAS UNIDAS S.A. CINE COLOMBIA S.A. AEROVIAS DE INTEGRACION REGIONAL S.A. PAVCO S.A. HOTELES ESTELAR S.A. SIDERURGICA DE MEDELLIN S.A. CEMENTOS DEL CARIBE S.A. CALES Y CEMENTOS DE TOLUVIEJO S.A. CIA. COLOMBIANA DE INVERSIONES AGRICOLAS CARVAJAL S.A. BAVARIA S.A. MAYAGUEZ S.A. CIA. DE EMPAQUES S.A. ETERNIT COLOMBIANA S.A. CIA. DE CEMENTO ARGOS S.A. TERPEL SUR S.A. INDUSTRIAS ESTRA S.A. INDUSTRIAS ALIMENTICIAS NOEL S.A. INGENIERIA ESPECIALIZADA S.A. FDO GANADERO DEL ATLANTICO S.A. CIA. INVERSORA COLMENA S.A. ETERNIT PACIFICO S.A. FDO GANADERO DEL HUILA S.A. FDO GANADERO DE SUCRE S.A - INTERVENIDO ALMACENES EXITO S.A. GRAN CADENA DE ALMACENES COLOMBIANOS S.A FDO GANADERO DE SANTANDER S.A. CLINICA COLSANITAS S.A. CARULLA Y CIA S.A. INVERSIONES EQUIPOS Y SERVICIOS S.A. FABRICA TEXTIL DE LOS ANDESS.A. CIA. AGRICOLA SAN FELIPE S.A. CIA. DE MEDICINA PREPAGADA COLSANITAS S. FDO GANADERO DE CALDAS S.A. CIA. COLOMBIANA DE TABACO S.A. CARTON DE COLOMBIA S.A. COLOMBINA S.A. CEMENTOS DEL VALLE S.A. FDO GANADERO DEL TOLIMA S.A. INGENIO DEL CAUCA S.A. INVERSIONES VENECIA S.A. PALMERAS DEL YARIMA S.A. INGENIO CENTRAL CASTILLA S.A FDO GANADERO DEL QUINDIO S.A. CEMENTOS PAZ DEL RIO S.A. CENTRAL TUMACO S.A. MANUELITA S.A. FDO GANADERO DE BOYACA S.A. HOTEL DE PEREIRA S.A. MINEROS DE ANTIOQUIA S.A. FDO GANADERO DEL CAUCA S.A. CEMENTOS RIOCLARO S.A. ALUMINIO NACIONAL S.A. AGROGUACHAL S.A. MANUFACTURAS DE CEMENTO S.A. UNIVERSIDAD PONTIFICIA BOLIVARIANA SIDERURGICA DE BOYACA S.A. INTEGRAL S.A. PAPELES NACIONALES S.A. RICA RONDO S.A. INDUSTRIA NACIONAL DE AL ALMACENES PAGUEMENOS S.A. PRENSA MODERNA IMPRESORES S.A. FDO GANADERO DEL CAQUETA S.A.

-8-

27.17 31.92 32.58 32.75 33.42 34.50 35.00 35.25 35.50 36.25 36.42 36.42 37.42 38.00 38.08 38.42 38.42 38.75 39.00 39.08 39.25 39.33 40.00 40.25 41.00 41.25 41.67 42.17 42.33 42.42 42.67 43.58 43.58 43.92 44.50 44.83 44.83 45.58 45.92 46.00 46.58 46.58 46.75 46.92 46.92 47.08 47.33 48.08 48.17 48.75 48.83 49.67 50.33 50.50 50.92 51.67 52.00 52.17 53.25 53.50 55.33 55.33 56.00 56.83 57.75 57.92

MODEL OF PREDICTION OF BANKRUPTCIES

JORGE S. ROSILLO C.

AVERAGE POSITION CONCONCRETO S.A. CARBONES DEL CARIBE S.A. FDO GANADERO DEL META S.A. VARELA S.A. CIA. NACIONAL DE VIDRIOS S.A. CONFECCIONES COLOMBIA S.A. COOMEVA ENTIDAD PROMOTORA DE SALUD S.A. FDO GANADERO DE RISARALDA S.A. LABORATORIOS LISTER S.A. ALGODONEROS DE VILLAVICENCIO S.A. EDITORIAL EL GLOBO S.A. EL PAIS S.A CEMENTOS BOYACA S.A. INDUSTRIA COLOMBIANA DE LLANTAS S.A. ENKA DE COLOMBIA S.A. INGENIO RIOPAILA S.A. CEMENTOS DIAMANTE S.A. FDO GANADERO DE CUNDINAMARCA S.A. MANUFACTURAS DE CUERO LA CORONA S.A. SOC. DE FABRICACION DE AUTOMOTORES S.A. COMPLEJO TURISTICO DEL ESPINAL S.A - EN TEXTILES ESPINAL S.A. ESTRUCTURAS CENO DE ANTIOQUIA S.A. CIA. COLOMBIANA DE TEJIDOS S.A. FDO GANADERO DEL CESAR S.A. CARIBU INTERNACIONAL S.A. SIDERURGICA DEL PACIFICO S.A. FDO GANADERO DE BOLIVAR S.A. PAÑOS VICUÑA SANTA FE S.A. -EN CONCORDAT TEJIDOS EL CONDOR S.A. ACEITES COMESTIBLES DEL SINU S.A. DISTRAL S.A. –EN CONCORDATO HILANDERIAS MEDELLIN S.A. COLOMSAT S.A. FIBRATOLIMA S.A. FABRICA DE HILADOS Y TEJIDOS DEL HATO S INDUSTRIAS LEHNER S.A. SETAS COLOMBIANAS S.A TABLEROS Y MADERAS DE CALDAS S.A. ACERIAS PAZ DEL RIO S.A -EN CONCORDATO

58.00 58.75 59.17 59.17 59.33 59.50 59.50 59.75 61.17 61.58 61.67 62.83 63.33 63.33 64.50 64.67 64.83 65.75 65.92 67.92 69.42 69.67 70.92 72.83 72.92 73.92 74.00 74.42 74.42 74.50 74.75 75.17 75.67 78.08 79.25 82.67 83.75 83.83 85.17 89.92

CALCULATION OF DISCRIMINANT FUNCTION Results of table # 4 are the Input for calculating the discriminant function, which is a multivariable system of analysis permitting to make predictions for defining if an enterprise is strong or weak, for its calculation statistical package SPSS was used. At the beginning 12 ratios were assigned for calculating discriminant function, system step by step reduced them to three, which are the real ones for establishing the difference between strong and weak enterprises, these ratios are: Debts, Patrimony income-yield long term Leverage, results obtained for coefficients of discriminant function are: Debts = -7,165 Patrimony Income-yield = 9,852 Long term Leverage = 1,097 Constant =1,563 Z = DISCRIMINANT FUNCTION Z = -7,165Xdebts+ 9,852Xpatrim.income-yield+1,097Xlong term leverage+ 1,563

-9-

MODEL OF PREDICTION OF BANKRUPTCIES

JORGE S. ROSILLO C.

Previous function is going to serve for determining when an enterprise is strong or weak, at the beginning the results of financial indicators were analyzed for 106 enterprises and in accordance with parameters considered in the present chapter about when an indicator is good or bad it was defined that of the 106 enterprises object of analysis, first 65 may be considered as financially strong and weak the remainder ones, reminding that classification made in tables #s 1, 2, 3 and 4 was in descendent order. From 106 enterprises of the sample 80 were taken ( 50 strong and 30 weak ) for calculating the average of discriminant ratios, remainder 26 (15 strong and 11 weak) are for testing the model (test), that is to say for determining if correctly classifying strong or weak enterprises which were not considered for calculating averages of discriminant financial indicators calculated as follows: AVERAGES OF DISCRIMINANT FINANCIAL INDICATORS OF STRONG ENTERPRISES Of first 65 enterprises classified as strong 50 were taken and it was proceeded to average their indicators so obtaining the following results ( See Table #5): Debts = 0,26017006 Patrimony Income-yield = 0,06113952 Long term Leverage = 0,50273351 Constant =1,563 With base on previous results it was proceeded to calculate discriminant function of financially strong enterprises. Zstrong = -7,165(0,26017006)+9,852(0,06113952)+1,097(0,50273351)+1,563

Zstrong = 0,85272677 AVERAGES OF DISCRIMINANT FINANCIAL INDICATORS OF WEAK ENTERPRISES From remainder 41 enterprises of the106 considered as weak 30 were taken and average financial indicators were calculated of discriminant function for these enterprises (See Table #6). Debts = 0,46342418 Patrimony Income-yield = -0,07814256 Long Term Leverage = 1,00787766 Constant =1,563 Zweak = -7,165(0,46342418)+9,852(-0,07814256)+1,097(1,00787766)+1,563

Zweak = - 1.42165289

- 10 -

MODEL OF PREDICTION OF BANKRUPTCIES

JORGE S. ROSILLO C.

POINT OF CUTTING (ZOC) With base on results of Z for strong and weak enterprises previously obtained it is proceeded to determine the ZOC that is the point of cutting or Z in which a strong enterprise becomes weak. ZOC = ((Zstrong)(Number of Strong Enterprises) + Zweak(Númber of Weak Enterprises))/total of enterprises

Zoc = (50(0.85272677) + 30(-1.42165289))/80 = - 0.0001656

ALL ENTERPRISES HAVING A DISCRIMINANT FUNCTION MAJOR THAN Zoc ARE STRONG, IN CONTRARY CASE ARE WEAK. CONCLUSIONS

In accordance with aforementioned the classification of enterprises of sample was tested (80 enterprises) and a 94% successes for the strong ones and a 87% for weak ones were obtained. ( See Tables #s 5 y 6) Finally the model with 26 enterprises was tested (15 strong and 11 weak) which were not part of the sample for calculation of discriminant ZOC and a 100% of successes for strong ones and 82% for weak were obtained (See Tables #s 7 and 8). THEREFORE IT IS CONCLUDED THAT THE MODEL REALLY SERVES FOR PREDICTING IF AN ENTERPRISE IS STRONG OR WEAK WITH FINANCIAL INDICATORS OBTAINED THROUGH DISCRIMINANT ANALYSIS. Multivariable analysis provides this technique very useful for banks and credit entities for analyzing enterprises when a credit is going to be granted or for directive personnel itself of organizations whishing to have a control instrument about how their management has been and taking correctives of the case if necessary. ZOC previously calculated would have usefulness for predicting if an enterprise is strong or weak even not considered among the 106 enterprises used in investigation, it would have some limitations if the business name does not seems like the enterprises of the sample. The 3 indicators obtained as fundamental for diagnosis of debts, patrimony income-yield and leverage, for strong enterprises they present an average debts value of 26% which really is low, because 75% is the maximum figure exacted to credit applicants by financial entities, what locates them in a very advantageous situation and a patrimony income-yield of 6.11% and a covered debt by 50% of the patrimony, to the contrary of weak enterprises they have debts close to 50%, a negative income-yield and liabilities with backup of the whole of patrimony that is to say a major risk, that is why we can conclude that results obtained by model are a good predictor due opposite results between weak and strong therefore discriminant function can be used as an instrument of forecast.

- 11 -

MODEL OF PREDICTION OF BANKRUPTCIES

JORGE S. ROSILLO C.

TABLE # 5 CLASSIFICATION STRONG ENTERPRISES (SAMPLE OF 50 COMPANIES) ENTERPRISE CIA. NACIONAL DE CHOCOLATES S.A. CERVECERIA AGUILA S.A. INDUSTRIAS METALURGICAS UNIDAS S.A. HOTELES ESTELAR S.A. SIDERURGICA DE MEDELLIN S.A. CEMENTOS DEL CARIBE S.A. CARVAJAL S.A. BAVARIA S.A. MAYAGUEZ S.A. CIA. DE EMPAQUES S.A. ETERNIT COLOMBIANA S.A. CIA. DE CEMENTO ARGOS S.A. TERPEL SUR S.A. INDUSTRIAS ESTRA S.A. INGENIERIA ESPECIALIZADA S.A. FDO GANADERO DEL ATLANTICO S.A. ETERNIT PACIFICO S.A. FDO GANADERO DEL HUILA S.A. FDO GANADERO DE SUCRE S.A – INTERVENIDO ALMACENES EXITO S.A. GRAN CADENA DE ALMACENES COLOMBIANOS S.A FDO GANADERO DE SANTANDER S.A. CLINICA COLSANITAS S.A. CARULLA Y CIA S.A. INVERSIONES EQUIPOS Y SERVICIOS S.A. CIA. AGRICOLA SAN FELIPE S.A. CIA. DE MEDICINA PREPAGADA COLSANITAS S. FDO GANADERO DE CALDAS S.A. CIA. COLOMBIANA DE TABACO S.A. CARTÓN DE COLOMBIA S.A. COLOMBINA S.A. FDO GANADERO DEL TOLIMA S.A. INVERSIONES VENECIA S.A. PALMERAS DEL YARIMA S.A. INGENIO CENTRAL CASTILLA S.A CEMENTOS PAZ DEL RIO S.A. CENTRAL TUMACO S.A. MANUELITA S.A. FDO GANADERO DE BOYACA S.A. MINEROS DE ANTIOQUIA S.A. FDO GANADERO DEL CAUCA S.A. CEMENTOS RIOCLARO S.A. ALUMINIO NACIONAL S.A. AGROGUACHAL S.A. MANUFACTURAS DE CEMENTO S.A. INTEGRAL S.A. PAPELES NACIONALES S.A. RICA RONDO S.A. INDUSTRIA NACIONAL DE ALMACENES PAGUEMENOS PRENSA MODERNA IMPRESORES AVERAGE

DEBTS

PATRIM. INCOMEYIELD

LONG TERM LEVERAG

DISCRIMI NANT FUNCTIO

CLASSIFI CATION

SUCCESS

0.11050

0.09753

0.12530

1.86959

STRONG

YES

0.16960

0.08914

0.20597

1.45198

STRONG

YES

0.23489

0.08404

0.30750

1.04531

STRONG

YES

0.15645 0.19627 0.09789 0.20074 0.24262 0.25720 0.17946 0.19707 0.04663 0.46935 0.20717 0.56826

0.02538 0.03696 0.07049 0.06462 0.08505 0.09042 0.01885 0.05385 0.08210 0.20027 0.03646 0.35509

0.19102 0.24642 0.11462 0.25286 0.32100 0.36143 0.21923 0.25072 0.04954 0.89380 0.26336 1.41417

0.90170 0.79117 1.68185 1.03873 1.01466 1.00751 0.70337 0.95652 2.09213 1.15366 0.72678 2.54108

STRONG STRONG STRONG STRONG STRONG STRONG STRONG STRONG STRONG STRONG STRONG STRONG

YES YES YES YES YES YES YES YES YES YES YES YES

0.13747

0.01322

0.16400

0.88818

STRONG

YES

0.27784 0.07420

0.06655 0.01197

0.39462 0.08032

0.66084 1.23743

STRONG STRONG

YES YES YES

0.05214

0.03215

0.05646

1.56810

STRONG

0.30625

0.10052

0.44194

0.84384

STRONG

YES

0.30085

0.07491

0.43102

0.61825

STRONG

YES

0.07835

-0.03893

0.08502

0.71132

STRONG

YES

0.35702 0.30458

0.08458 0.05468

0.60198 0.43901

0.49858 0.40100

STRONG STRONG

YES YES

0.04101

0.00447

0.04293

1.36034

STRONG

YES

0.02395

0.00176

0.02455

1.43572

STRONG

YES

0.72785

0.26379

2.68866

1.89634

STRONG

YES

0.18111

0.03873

0.22251

0.89105

STRONG

YES

0.14631

0.02872

0.17177

0.98608

STRONG

YES

0.18705 0.35126 0.10601 0.14330 0.24090 0.24493 0.18486 0.35785 0.39309 0.09312 0.42991 0.12723 0.34687 0.30489 0.07166

0.02915 0.07276 0.01211 -0.00870 0.03439 0.02124 0.01108 0.03320 0.05942 -0.02314 0.11620 -0.02296 0.07633 0.04118 -0.00178

0.23025 0.54303 0.11948 0.16940 0.32599 0.32530 0.23561 0.56447 0.64957 0.10284 0.75584 0.14638 0.54401 0.44006 0.07741

0.76257 0.35880 1.05382 0.63634 0.53339 0.37423 0.60605 -0.05463 0.04451 0.78057 0.45665 0.58577 0.42643 0.26690 1.11692

STRONG STRONG STRONG STRONG STRONG STRONG STRONG WEAK STRONG STRONG STRONG STRONG STRONG STRONG STRONG

YES YES YES YES YES YES YES NO YES YES YES YES YES YES YES

0.37061

0.15146

0.81109

1.28954

STRONG

YES

0.69851 0.35260

0.12558 0.02213

2.35447 0.55247

0.37832 -0.13931

STRONG WEAK

YES NO

0.58003

0.06094

1.39512

-0.46210

WEAK

NO

0.74879 0.33202 0.26017

0.08173 0.03727 0.06114

3.21943 0.51271 0.50273

0.53479 0.11367 0.85273

STRONG STRONG SUCCESS ES

YES YES 94%

- 12 -

MODEL OF PREDICTION OF BANKRUPTCIES

JORGE S. ROSILLO C.

TABLE # 6 CLASSIFICATION WEAK ENTERPRISES (SAMPLE OF 30 COMPANIES)

0.12898

PATRIM. INCOMEYIELD -0.0404

LONG TERM LEVERAG 0.14813

DISCRIMI NANT FUNCTIO 0.40345

0.62898 0.41067 0.13782 0.47092 0.48041 0.50131

0.1611 0.0182 -0.0637 0.0068 0.0742 -0.1786

1.80823 0.71300 0.16397 0.89072 0.93202 1.39668

0.11410

-0.0672

0.40682 0.51788 0.35950 0.34532 0.36291 0.48373

CLASSIFI CATION

SUCCESS

STRONG

NO

0.62758 -0.41824 0.12759 -0.76673 -0.12597 -2.25655

STRONG WEAK STRONG WEAK WEAK WEAK

NO YES NO YES YES YES

0.12907

0.22532

STRONG

NO

0.0284 0.0317 -0.0056 -0.0120 -0.0023 -0.1177

0.68996 1.07565 0.56438 0.53219 0.67235 1.10944

-0.31516 -0.65509 -0.44934 -0.44566 -0.32282 -1.84542

WEAK WEAK WEAK WEAK WEAK WEAK

YES YES YES YES YES YES

0.54764

-0.0606

1.23455

-1.60352

WEAK

YES

0.51830

0.0069

1.08223

-0.89545

WEAK

YES

0.37863

-0.0743

0.63694

-1.18336

WEAK

YES

0.21516 0.45027 0.39367

-0.0746 -0.0513 -0.0751

0.27463 0.83348 0.68801

-0.41229 -1.25446 -1.24297

WEAK WEAK WEAK

YES YES YES

0.54317

-0.2016

1.20933

-2.98807

WEAK

YES

0.59847

-0.2554

1.50441

-3.59097

WEAK

YES

1.01119 0.27680 0.58394 0.52005

-0.0827 -0.1196 -0.1137 -0.1362

1.56860 0.38617 1.41617 1.10499

-4.77601 -1.17458 -2.18794 -2.29260

WEAK WEAK WEAK WEAK

YES YES YES YES

0.72116 0.53138 0.58215

-0.1186 -0.2218 -0.1613

2.67759 1.14994 1.40590

-1.83475 -3.16795 -2.65479

WEAK WEAK WEAK

YES YES YES

0.68141

-0.4373

2.23760

-5.17284

WEAK

YES

0.46342

-0.0781

1.00788

-1.42165

SUCCESS ES

87%

ENTERPRISE

DEBTS

FDO GANADERO DEL CAQUETA S.A. CONCONCRETO S.A. CARBONES DEL CARIBE. FDO GANADERO DEL META S.A. VARELA S.A. CIA. NACIONAL DE VIDRIOS S.A. COOMEVA ENTIDAD PROMOTORA DE SALUD S.A. FDO GANADERO DE RISARALDA S.A. EL PAIS S.A CEMENTOS BOYACA S.A. ENKA DE COLOMBIA S.A. INGENIO RIOPAILA S.A. CEMENTOS DIAMANTE S.A. SOC. DE FABRICACION DE AUTOMOTORES S.A. COMPLEJO TURISTICO DEL ESPINAL S.A - EN ESTRUCTURAS CENO DE ANTIOQUIA S.A. CIA. COLOMBIANA DE TEJIDOS S.A. FDO GANADERO DEL CESAR S.A. CARIBU INTERNACIONAL S.A. SIDERURGICA DEL PACIFICO S.A. PAÑOS VICUÑA SANTA FE S.A. – EN CONCORDAT ACEITES COMESTIBLES DEL SINU S.A. DISTRAL S.A. –EN CONCORDATO HILANDERIAS MEDELLIN S.A. COLOMSAT S.A. FABRICA DE HILADOS Y TEJIDOS DEL HATO S INDUSTRIAS LEHNER S.A. SETAS COLOMBIANAS S.A TABLEROS Y MADERAS DE CALDAS S.A. ACERIAS PAZ DEL RIO S.A -EN CONCORDATO AVERAGE

TABLE # 7 STRONG ENTERPRISES FOR THE TEST (TEST) (SAMPLE OF 15 COMPANIES) ENTERPRISE ESTACION TERM.DE DIST. DE PROD. DE PETR. CINE COLOMBIA S.A. AEROVIAS DE INTEGRACION REGIONAL S.A. PAVCO S.A. CALES Y CEMENTOS DE TOLUVIEJO S.A. CIA. COLOMBIANA INV AGRICOL

0.33116

PATRIM. INCOMEYIELD 0.15151

LONG TERM LEVERAG 0.49644

0.21337 0.44219

0.08726 0.17554

0.27746 0.79635

0.19845 0.26333

0.04718 0.08335

0.25376

0.14524

DEBTS

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DISCRIMI NANT FUNCTIO 1.22752

CLASSIFI CATION

SUCCESS

STRONG

YES

1.19822 0.99776

STRONG STRONG

YES YES

0.25741 0.35816

0.88829 0.89034

STRONG STRONG

YES YES

0.35211

1.56195

STRONG

YES

MODEL OF PREDICTION OF BANKRUPTCIES

ENTERPRISE INDUSTRIAS ALIMENTICIAS NOEL S.A. CIA. INVERSORA COLMENA S.A. FABRICA TEXTIL DE LOS ANDESS.A. CEMENTOS DEL VALLE S.A. INGENIO DEL CAUCA S.A. FDO GANADERO DEL QUINDIO S.A. HOTEL DE PEREIRA S.A. UNIVERSIDAD PONTIFICIA BOLIVARIANA SIDERURGICA DE BOYACA S.A. AVERAGE RATIOS STRONG ENTERPRISES (TEST)

JORGE S. ROSILLO C.

0.27621

PATRIM. INCOMEYIELD 0.06890

LONG TERM LEVERAG 0.38550

0.27049 0.32586

0.07234 0.06716

0.38536 0.50975

0.18976 0.29394 0.07365

0.11855 0.02181 -0.04807

0.10522 0.29296

DISCRIMI NANT FUNCTIO 0.68566

CLASSIFI CATION

SUCCESS

STRONG

YES

0.76038 0.44907

STRONG STRONG

YES YES

0.23798 0.41784 0.07961

1.63241 0.13013 0.64908

STRONG STRONG STRONG

YES YES YES

0.00316 0.03390

0.11816 0.42633

0.96987 0.26554

STRONG STRONG

YES YES

0.25434

-0.00035

0.34370

0.11425

STRONG

YES

0.25231

0.06850

0.36281

DEBTS

0.82803

SUCCESS ES

100%

TABLE # 8 WEAK ENTERPRISES FOR THE TEST (TEST) (SAMPLE OF 11 COMPANIES)

0.3695 0.6385 0.8065

PATRIM. INCOMEYIELD -0.0043 0.0811 0.2604

LONG TERM LEVERAG 0.5933 1.7878 5.1402

DISCRIMI NANT FUNCTIO -0.4760 -0.2516 3.9887

0.5986 0.3959

0.0093 -0.0620

1.5351 0.6728

0.1417

-0.1043

0.5202

CLASSIFI CATION

SUCCESS

WEAK WEAK STRONG

YES YES NO

-0.9504 -1.1467

WEAK WEAK

YES YES

0.1685

-0.2947

WEAK

YES

0.1410

1.1073

0.4396

STRONG

NO

0.3908 0.2492 0.4768 0.4665

-0.0162 -0.0645 -0.1370 -0.0772

0.6443 0.3351 0.9384 0.8903

-0.6903 -0.4902 -2.1742 -1.5636

WEAK WEAK WEAK WEAK

YES YES YES YES

0.4595

0.0024

1.2557

-0.3281

SUCCESS ES

82%

ENTERPRISE

DEBTS

CONFECCIONES COLOMBIA S.A. LABORATORIOS LISTER S.A. ALGODONEROS DE VILLAVICENCIO S.A. EDITORIAL EL GLOBO S.A. INDUSTRIA COLOMBIANA DE LLANTAS S.A. FDO GANADERO DE CUNDINAMARCA S.A. MANUFACTURAS DE CUERO LA CORONA S.A. TEXTILES ESPINAL S.A. FDO GANADERO DE BOLIVAR S.A. TEJIDOS EL CONDOR S.A. FIBRATOLIMA S.A. AVERAGE RATIOS WEAK ENTERPRISES (TEST)

BIBLIOGRAPHY: Altman, Edward, “Examining Moyer’ s Reexamination of Forecasting Financial Failfure” Financial Management 7 Invierno de 1978 Altman, Edward; Robert G. y Narayanan P. “ Zeta Analisis: A New Model to Identify BankRuptcy Risk” Journal of Banking and Finance junio de 1977 Joy Maurice y Tollefson John “ On the Financial Applications of Discriminant Analysis”, Journal of Financial and Quantitative Analysis 10 Diciembre 1975 Altman Edward, “ Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy” Journal of Finance 23, Septiembre de 1968 Eisenbeis Robert “ Pitfallls in the Aplication of Discriminant Analysis in Business Finance, and Economics”, Journal of Finance 32, junio 1977 Moyer Charles “ Reply to Examining Moyer’s Re- Examination of Forecasting Failure” Financial Management 7, Winter 1978

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MODEL OF PREDICTION OF BANKRUPTCIES

JORGE S. ROSILLO C.

Tollefson John and Joy Maurice “ Some Clarifying Comments on Discriminant Analysis” Journal of Financial and Quantitative Analysis,13 marzo 1978

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