THE IMPACT OF THE FINANCIAL CRISIS ON THE ROMANIAN COMPANIES EARNING

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1 THE IMPACT OF THE FINANCIAL CRISIS ON THE ROMANIAN COMPANIES EARNING PERFORMANCE AND FINANCIAL POSITION Ec. Dan Florentin SICHIGEA Ph. D, University of Craiova, Faculty of Economics Craiova, Romania Ec. Mirela Miruna CIOCHIA, Student University of Craiova, Faculty of Economics and Business Administration Craiova, Romania Ec. Cristina BULDUR Student University of Craiova, Faculty of Economics and Business Administration Craiova, Romania Abstract: In this paper, we examined how the current economic crisis affected the profitability and financial position of the Romanian companies. We studied the profitability, financial position and risk for a number of 16 companies listed on Bucharest Stock Exchange, the four branches of activity: pharmaceuticals, construction, oil and food. The analysis covered the period between , which allowed tracking how the economic financial position we found that best results are achieved by the pharmaceutical sector. Calculated rates of return have fluctuated over time and between companies, but generally had a downward trend. At the end of the work we have identified a correlation between financial profitability (the dependent variable) and rate the financial stability function model Z Anghel, general creditworthiness (as independent variables). Model results from the correlation can be used in making predictions and future work orientation of firms. JEL classification: C01, G01 Key words : profitability, financial position, risk, financial stability, financial and economic performance 1. INTRODUCTION The concept of economic and financial performance of a company has had many heterogeneous definitions along time in the specialized literature: among others, it was correlated to net profit, to the creation of value, to the efficiency indicators or the position towards competitors. Despite this diversity of opinions, a close connection is outlined between performances and the company s results or achievements. The final goal of any company participating in the economic activity is to obtain maximum earnings, to detach itself from competitors, to satisfy its shareholders or, otherwise said, to maximize its profitability. In order to ensure such maximization, performances must be, first, quantified, measured, interpreted and analyzed in terms of several indicators.

2 In the study we started from the fact that the profitability of the firms and their financial position has changed due to reality of the financial crisis and how to adapt the Romanian society to its difficulties. Thus it is normal for some areas of activity to be more marked than others, to influence the results and hence the returns and the profitability of firms. Through this article, we proposed to study the correlation between the earning performance and financial position of the Romanian companies, based on a series of relevant indicators. In the study there were included 16 companies listed on Bucharest Stock Exchange, for which we used the data in the annual financial statements. The analysis was conducted for four consecutive years, aiming to identify the differences in corporate and business sectors in 2007 (which preceded the beginning of the financial crisis in our country) and the years that followed, and 2008 (beginning of the crisis ), 2009 and 2010 (years of full crisis). The objective of this review is to present an accurate picture of how firms from this country were able to cope with the crisis, how the activity and the financial results were affected. So, we watched four companies in four major areas of activity, namely the pharmaceutical sector, the constructions sector, the oil industry and the food industry. The choice of these four areas aims to illustrate which of these have best overcome the shocks of the economic crisis. By comparing the results obtained, we emphasized the similarities and differences between the firms analyzed for each studied year. In order to reflect the financial position, in this study we used the following financial ratios: Current Liquidity Ratio, Immediate Liquidity Ratio, overall solvency ratio, solvency ratio and the rate of economic financial stability. Also, to reflect the profitability, we analyzed the return on assets and the return on equity. We also studied the risk of bankruptcy of the analyzed companies by using the Altman and Anghel models that allowed the firms classification in several areas of risk. In the last part of the paper, we tested the correlation between the profitability, the financial position and the risk of bankruptcy, using SPSS statistical package, which was conducted using a mathematical model. It allowed to obtain several useful conclusions on the correlation tested, while allowing, and carrying out projections of profitability. 2. METHODOLOGY The financial position of an enterprise is influenced by the economic resources it controls, its financial structure, the liquidity, the solvency and the ability to adapt to changes in the operating environment. The liquidity of a firm refers to cash availability in the near future, after taking into account the financial obligations for this period. The formulas for calculating the current liquidity ratio (L c ) respectively the immediate liquidity ratio (L i ) are as follows: CA CA S Lc 100. (1) Li 100. (2) STD STD CA = current assets, STD = current liabilities, S = stock The solvency of a firm refers to the cash availability of over a longer period in which it has to honor its outstanding financial commitments. Among the solvency ratios, we studied the general solvency ratio (S g ) and the asset solvency ratio which are calculated as follows: 1 Bătrâncea I., Dumbravă P., Bătrâncea L. Bilanţul entităţii economice, Ed. Alma Mater Cluj Napoca, 2007, pg. 98

3 TA Kpr Sg 100. (3) Sp 100. (4) Dt Kt TA = total assets, Dt= total debt, Kpr = own capital, Kt = total capital The ratio of the financial stability reflects the share of the permanent capital (Kper) in the company's total capital (Kt). Kper RSF 100. (5) Kt The earning performance is one of the synthetic forms of expressing the efficiency and it reflects the capacity of the company to release a financial surplus in the form of profit from their activities. The return expresses the efficiency with which a company uses financial and material resources invested in its work, having gone through all the stages of the economic circuit. In the article, we calculated the return on assets and the return on equity: Pe Pn Re 100 (6) Rf 100 (7) TA Kpr Pe = operating profit, TA = total assets, Pn = net profit, Kpr= own capital We analyzed the scores using the risk of bankruptcy. The discriminant analysis method called scores (scoring) defines a new variable "Z", which is a combination of rates that make differ most the two classes, namely healthy and risky business 1. By using the Anghel model, there were retained for the development of the score function, four financial ratios: the return on income, the ratio of debt coverage with cash flow, the asset leverage and the period of obligations payment, which are aggregated into the following function: A = 5, ,3781X 1 + 5,3932X 2-5,1427X 3-0,0105X 4 Depending on the values obtained the firms are classified either in a situation of failure / bankruptcy (A <0) or in the area of uncertainty (0 <A <2.05) or non-bankruptcy situation (A> 2.05). According to the Altman model, the scoring function has the following form: Z =1,2X 1 +1,4X 2 +3,3X 3 +0,6X 4 + X 5 where: X1 = Net Working capital / total assets; X2 = Reserves / Total Assets; X3 = Gross operating surplus / total assets; X4 = equity / total liabilities; X5 = Turnover (excl. VAT) / total assets. Altman characteristic values of the model are: - If Z < the company is insolvent, - If 1.81 <z 2.90, the firm is in difficulty, - If Z 2.90-organization may be considered economically healthy. The analysis of the correlation between the profitability and the financial position can be made both separately,through the correlation coefficient, analyzing the correlations between the dependent variable and independent variable selected from the studied group variables, or overall, through the linear regression. The intensityof the correlation between 1 Siminică Marian Diagnosticul financiar al firmei, ED. Sitech, Craiova, 2010, p. 244

4 the studied variables is estimated using the Pearson correlation coefficient. It takes values between -1 and 1 theoretical, positive values indicating direct correlations and inverse correlations negative. The linear regression consists of calculating the correlation coefficient for the group of variables, analyzing the correlation between a dependent variable and a number of independent variables. As with the applied correlation coefficient, the calculated value should be as close as possible to estimate a value that there is a very strong correlation. Thus, to capture the correlation between variable outcome (Y), on the one hand, and factorial variables (X1... Xn) on the other hand, using a multiple linear regression model of the form: Y 1 X1 2 X2... n Xn (10) where: α, β1... βn - regression coefficients. 3. ANALYSIS 3.1. ANALYSIS OF FINANCIAL POSITION RATES Current liquidity levels for companies in the study, the period, are shown in Table no.1 Table no. 1 BIO % % % 550,39% SNP % % % * SCD % % % 698,97% DAFR % % % 120,40% SINT % % % 362,85% TGN % % % 156,49% ATB % % % 202,38% RRC % 71.30% 40.24% 41,35% PRAE % % 79.84% 56,73% COTR % % 148,41% 123,93% ALBZ % % 88.74% 85,35% CFES % 62.71% 53.36% 80,88% INEM 93.38% 67.91% 92.13% 90,12% SCTB % % % 117,82% LACT % % % 95,08% UTBT 31.45% 64.85% % 288,36% Given that this rate should record values greater than 100% (to have a positive working capital), it appears that the pharmaceutical sector exceeds this threshold in all four years, fact which can be considered as favorable. Lactate Giurgiu (INEM) has a value less than unity in all the analyzed years, and this can be a problem for timely payment of shortterm obligations. In the oil sector, the only company with a precarious financial ratios is Rompetrol (RRC), where we notice a downward trend due to the rising of short-term debt and the declining value of current assets. The level drops below the normal level since 2008, so that in 2010 it reached 41.35% in value, fact that can reflect a declining activity and and can worry the suppliers regarding the granting of new loans and commercial banking.an opposie trend was noticed in Bega Construction (UTBT), which in 2010 reached a value higher than one, although he had a very low level in 2007 and This change is due to the decreasing of short term debt and the increasing of current assets in the last analyzed year. The second indicator of the financial position which we analized is the immediate liquidity. Its values are illustrated in the following table:

5 Table no. 2 BIO % % % % SNP % 78.05% 65.03% * SCD % % % % DAFR 82.11% 82.45% 78.80% 80.42% SINT % % % % TGN % % % % ATB 188,67% 149,55% % % RRC 74.74% 51.93% 24.28% 25.08% PRAE % 69.03% 43.27% 33.92% COTR % % % 36.73% ALBZ % 60.59% 52.66% 61.03% CFES 85.79% 55.72% 48.88% 74.40% INEM 51.62% 45.81% 51.99% 59.12% SCTB 105,41% 65,02% % 79.89% LACT % 47.17% 54.51% 47.22% UTBT 29.08% 55.72% % % So that the analized companies can have the capacity to meet their short term obligations it is indicated that tha immediate liquidity ratio fall between a level of 80% - 100%. We noticed that in the oil sector, the situation is favorable because the all four firms exceeded the normal level throughout the analyzed period. At the opposite stand the dairy companies that, although, in 2007 did not face difficulties (PRAE, ALBZ, lactate), starting with 2008 they failed to achieve any level between 80% - 100%, which implies that the situation is a delicate one. If we refer to the other two areas there is one company of each (RRC and CFES), which in 2010 recorded values which placed them in the category of companies with difficulties regarding the payment of the current debt. The third is the overall solvency rate. The illustrated values are in the following table: Table no.3 BIO % % % 880,58% SNP % % % * SCD % % % 858,14% DAFR % % % 156,89% SINT % % % 707,13% TGN % % % 416,27% ATB % % % 354,94% RRC % % % 116,50% PRAE % % % 161,05% COTR % % % 626,66% ALBZ % % % 185,46% CFES % % % 192,51% INEM % % % 211,36% SCTB % % % 338,38% LACT % % % 107,36% UTBT % % % 1440,3% If we analyze the results of the 16 firms, we see that in the first year only 12 of these values are above the normal range of 200%, and for companies Lactag (LACT), Dafora (DAFR), Rompetrol (RRC), (UTBT), the rate is below the limit. Of the four sectors, the pharmaceutical is the one in which all the firms have a favorable situation (the maximum is reached by Biofarm, who has exceeded 1,000% in 2007 and 2009, the amount considered to be atypical) and the lower values are obtained in

6 the oil sector, where Dafora and Rompetrol fail in all the four years to record values above the normal range. From this analysis, we noted that Lactag (LACT), although it had a slight increase from one year to another, the situation of the solvency remains delicate. In 2010, we see that, this time, the number of the firms that do not reach the normal value (Prodlacta- (PRAE) Lactag, Dafora, Rompetrol, (CFES), Albalact) has increased, so that, in addition to the three that still retain their 2007 level below 200%, are added CFES, Prodlacta and Albalact. The most spectacular evolution was registered by Bega Construction, which gets in 2010 to have a value of eleven times higher in 2007, which is due to an increase in total assets and significant decrease in total liabilities. Regarding the solvency rate, the data obtained are as follows: Table no.4 BIO 90.82% 88.29% 88.30% 86.64% SNP 62.30% 54.43% 52.62% * SCD 81.31% 82.69% 85.46% 85.63% DAFR 36.15% 32.40% 34.24% 35.51% SINT 72.14% 70.40% 75.10% 81.43% TGN 60.03% 66.71% 68.80% 67.43% ATB 71.32% 67.06% 64.25% 66.86% RRC 46.44% 36.58% 22.25% 9.39% PRAE 44.43% 39.46% 35.96% 27.87% COTR 42.96% 78.64% 82.22% 83.67% ALBZ 67.22% 56.16% 45.75% 43.28% CFES 58.85% 26.20% 41.62% 44.99% INEM 47.87% 45.94% 47.64% 44.31% SCTB 58.51% 72.73% 67.57% 68.19% LACT 2.71% 6.27% 6.62% 6.82% UTBT 22.39% 68.49% 90.32% 92.79% In terms of patrimonial solvency, the best results are in the pharmaceutical sector, where the recorded values are above the normal limit of 50%. The dairy companies recorded a downward trend from one to another so that in 2010 two companies (PRAE and lactate) are below the minimum acceptable limit, which means that they can not cope with the maturities on their own sources, they being forced to resort to loans.the same situation is found in the case of RRC which also records the decreasing values from one year to another (9.39% in 2010). A spectacular evolution had UTBT from the construction sector, which although in 2007 was below the limit value in 2010 it reached 92.79%, favorable situation. The fourth rate that reflects the calculated financial position is the rate of financial stability whose values are presented in the table below: Table no.5 BIO 91,73% 88,99% 88,85% 87,14% SNP 62,44% 60,47% 63,18% * SCD 81,38% 82,69% 85,46% 85,63% DAFR 62,08% 75,14% 69,30% 71,33% SINT 78,54% 73,68% 76,06% 81,43% TGN 83,35% 84,54% 84,16% 82,14% ATB 72,42% 67,45% 64,26% 66,86% RRC 50,91% 38,72% 22,26% 9,39% PRAE 52,74% 58,86% 49,91% 44,80% COTR 73,36% 91,20% 95,58% 88,75% ALBZ 70,32% 64,31% 59,34% 57,92% CFES 59,10% 26,61% 41,85% 59,98%

7 INEM 49,50% 48,53% 49,11% 44,71% SCTB 62,66% 74,53% 68,48% 69,15% LACT 83,34% 84,94% 77,49% 80,29% UTBT 81,34% 93,21% 94,69% 94,32% Seen only in dynamic level of this rate decreases from year to year 7 of the 16 companies and this decline is due to the increased short-term debt whereas a higher rate than capital growth and emergence of permanent economic crisis since It can be seen that the areas showing the highest rates is pharmaceutical where work is done mostly funding permanent capital and less short-term loans, something that means a more stable funding sources.at the opposite end where the two companies are dairy (and dairy Prodlacta Giurgiu) had values below normal stability rate of 67%. This means that more funds than normal short-term loans, something that can be extremely risky. In construction and oil company is one which all four years below the normal values (Rompetrol and railroads Timişoara). The Rompetrol in 2009 and 2010 the situation is alarming (especially in 2010) as the value recorded is very low, something that is due to accelerated growth of short-term debt ANALYSIS OF RATES OF RETURN Economic rate of return for the firms analyzed as following: Table no.6 BIO 9.22% 9.90% 8.90% SNP 9.28% 5.25% 4.48% * SCD 2.88% 6.60% -3.11% DAFR 7.21% 5.56% 4.72% 5.27% SINT -4.21% -3.20% 3.14% 4.85% TGN 10.39% 8.57% 10.03% 11.57% ATB 12.17% 6.88% 6.95% 7.78% RRC -0.86% 0.40% -6.63% -2.52% PRAE 2.71% 6.20% 0.20% -8.83% COTR 14.77% 5.44% 1.52% 0.62% ALBZ 6.11% 4.33% 5.58% 2.25% CFES 8.04% 27.07% -3.71% -6.11% INEM 4.45% -3.66% 5.51% -2.59% SCTB 6.30% 4.62% 2.39% 1.80% LACT 4.63% 4.80% 4.41% 2.99% UTBT % 20.85% -0.78% 4.40% In the pharmaceutical field there is a decrease in value of the value in 2009 compared to the first, the only exception being represented by Sintofarm. Negative values are obtained by Sintofarm in 2009 and Zentiva in 2007 and This is due to the fact that these companies have had in those years operating loss rates with negative consequences for their performance. Analyzing the dairy sector we note that the values obtained in 2010 compared to 2007, recorded a downward trend (even negative-prae and INEM), which is obtained due to operating losses in the financial year. The petroleum sector noted that all firms had a lower value of the indicator in 2009 compared with the first year of reference.în 2010 the highest rate values were recorded by Transgaz, and the opposite stands Rompetrol with losses in three of the four analyzed years, which contributed to negative values. The construction sector has been obtained very different results in calculating the economic profitability, so that 3 of the companies recorded a decrease in 2010 compared to

8 2007, except for UTBT which, although in 2007 registered a very low level of this indicator, it recorded in 2010 a positive value of 4.40%. Regarding the rate of financial stability, the obtained data are as follows: Table No. 7 BIO 8.95% % 14.43% 9,89% SNP 13.49% 7.53% 9.73% * SCD 1.64% 8.11% 1.02% 16,91% DAFR 11.53% 0.64% 0.89% 5,08% SINT -7.38% % 1.66% 4,75% TGN 14.30% 10.92% 12.61% 14,55% ATB 13.18% 4.28% 4.92% 4,77% RRC % % % -115,16% PRAE 1.82% 7.03% -9.67% -52,60% COT 25.67% 4.50% 0.25% 0,27% ALBZ 3.81% 0.71% 3.04% 0,68% CFES R % % % -16,74% INEM 5.97% % 4.13% 8,59% SCTB 5.18% 5.85% 1.47% 0,02% LACT 17.35% 3.67% 3.95% 1,18% UTBT % 26.76% 0.06% 4,85% The pharmaceutical companies had a drastic decrease in financial return in 2008 (except Zentiva), after which it recovers its financial profitability in As an observation, the only companies that had positive values throughout the studied period are antibiotics and Zentiva the maximum being reached in By analyzing the companies in the dairy sector it is noted that two of them had the highest value of the indicator in 2007, the first being Lactag. But this level is not maintained in the coming years because, firstly the profit falls at its half in 2008, and secondly there is a doubling of equity. The minimum values are recorded by Giurgiu lactate in 2008 and Prodlacta in 2009 and 2010, and it is due to the obtained net losses. Of the four companies in the oil industry it is noted that the highest rates of financial return is registered by Transgaz whose values a are above 10% across the four analyzed years. Rompetrol is opposed which has negative and increasingly smaller values during the analized period.this is due to the increase in net loss from one to another, seriously affecting the return on equity, especially since the economic profitability is negative and quite significant in the year In the construction sector are observed the largest variations, UTBT reaching the minimum value and the maximum value (26.76% in 2008) of all the analyzed companies. 3.2.THE ANALYSIS OF BANKRUPTCY RISK By calculating the Anghel score, the studied firms have obtained the following values: Table no.8 Firm Firm BIO 1,78 23,04 7,81 SNP 15,05 12,40 * SCD 12,44 8,48 10,47 DAFR 5,67 2,17 4,95 SINT 1,74 7,72 13,69 TGN 7,51 8,62 9,93 ATB 6,21 8,85 15,56 RRC 0,63-1,49 1,16 PRAE 4,58 2,87 2,26 COTR 8,18 8,55 9,94 ALBZ 6,20 5,53 4,37 CFES 4,98-1,16-0,97 INEM 1,98 6,20 2,50 SCTB 9,41 4,90 7,68 LACT 0,68 1,47 1,35 UTBT 10,03 10,48 17,30

9 If we consider the three intervals for the risk assessment, we see that for 2008 no company falls under the bankrupty risk, however, the uncertainty is within five of these, 11 companies representing a low risk of bankruptcy. In 2009, the situation changes so that the two companies go into bankruptcy, which means they have a poor financial situation and they are threatened by high bankruptcy risk. In the area of uncertainty it remains a single company (Lactag) and the remaining 13 companies are in non-bankruptcy.in the last analyzed year remains in the bankruptcy only CFES, Lactagl and Rompetrol being placed in areas of uncertainty, and all other firms are not threatened by bankruptcy. Analyzing the dynamics it is observed that the only company that remains in the area of uncertainty is Lactag in all analized years and CFES had a negative function score in both 2009 and In addition, there are 10 of the 16 studied companies which are placed in non- bankruptcy area. The values obtained by applying the Altman model (for studied companies) are: Table no. 9 BIO SNP * SCD DAFR SINT TGN ATB RRC PRAE COT ALBZ CFES INEM SCTB LACT UTBT From the obtained data we notice companies that face difficulties (during the four years analyzed) in terms of solvency, and companies that are considered economically healthy.we noticed that CFES from the construction sector registers for the entire analyzed period values below 1.81, followed by PRAE and RRC (in 2009 and 2010), which means that these companies are being forced to face problems, to take action to improvethe activity.in terms of risk, the sector pharmaceutical presents the best situation, so that in 2010 all four companies offer a favorable situation. If we analyze the dynamics, we observe that although in 2007 SCTB and ALBZ firms were considered economically healthy in 2010 they recorded values that placed them in an action area of decline factors. 3.3.THE CORRELATION BETWEEN THE RETURN ON EQUITY, THE RATE OF FINANCIAL STABILITY THE OVERALL SOLVENCY AND THE ANGHEL SCORE To analyze the correlation between profitability, financial position and risk, we selected as dependent variable, the return on equity, and as independent variables: the current liquidity, s the overall olvency the rate of global financial stability and the value of the Z score calculated with the Anghel model. We used the data processed by SPSS's softaware and obtained the following situation: The correlations between the dependent variable and the independent variables:

10 Table no. 10. Lc Sg Rsfg Z_Anghel Pearson Correlation Rrf 0,351 0,378-0,917 0,515 Sig. (1-tailed) Rrf 0,091 0,075 0,000 0,021 N Rrf As seen from Table 10, for the 16 companies (the value of N in the table representing the 16 studied companies), the highest value for Pearson's coefficient (-0.917) is registered for the correlation between the return on equity and the rate of financial stability, which means strong inverse correlation between the existence of the two variables. Materiality (Sig) shows a null value (0.000), indicating that the value obtained is significant.the following variables that influence the value of financial profitability, in order of intensity the dependence are: the Anghel Z score (0.515) and the overall solvency (0.378). It is noted that these two variables are directly correlated to the return on equity. The first independent variable entered in the model is " the rate of financial stability", which, as previously shown, has a greater influence on the return on equity. In the second stage, the second independent variable introduced was the " Z_Anghel score", the last entered variable being the "overall solvency". It is noted that the fourth independent variable under study, the "Liquidity" is introduced in the model and the effect on net asset value is insignificant. In table no.11 are presented for a multiple linear regression model, the correlation coefficient (R), the determinative relationship (R Square) and the standard error. Table no. 11 Model R R Square Std. Error of the Estimate 1 0,917 a 0,840 0, ,940 b 0,883 0, ,962 c 0,926 0, Interpretation of the three models of correlation results is as follows: The model 1 shows the dependence of return on equity and the rate of financial stability in order to produce a correlation coefficient of and a determinative ratio of These values indicate the existence of an inverse correlation between the two variables, strong enough; In model 2 an independent variable is added, the Z_Anghel score in order to produce a correlation coefficient of and a determinative ratio of This means that 88.3% of the variance of return on equity is explained by changes in financial profitability and the value of the Z_Anghel score. Furthermore, by introducing in the regression model of the two independent variables, the estimated standard error decreases significantly from to ; In model 3 the last independent variable is introduced, the overall solvency, giving a highest value of correlation coefficient (0.962) and determinative relationship (0.926). This model explained 92.6% of the change in return on equity and it is considered the most comprehensive. The calculated regression coefficients for each of three model are shown in Table. 12.

11 Model B Table no. 12 Unstandardized Coefficients Std. Error T Sig. (Constant) 0,070 0,023 3,036 0,010 Rsfg -0,140 0,014-10,279 0,000 Z_Anghel 0,008 0,002 3,625 0,003 Sg -0,010 0,004-2,640 0,022 The T test and the value Sig. are used to test the regression coefficients, ie the assumption that between the dependent variable and the independent variables there is no significant connection. In the study, the elevated t-test for each variable, and Sig has very small values (below 0.05), which allows us to reject the hypothesis that between the analyzed variables there is no significant connection, meaning that small errors might occur due to the random measurement. Based on the calculated coefficients, which are found in column B of Table no. 10, the linear multiple regression model identified for the studied variables is presented below: Y 0,070 0,140 X1 0,008 X 2 0,010 X3 Where: Y - Return on equity; X1 - rate financial stability; X2 - Z_Anghel score; X3 - the overall solvency. This model illustrates the correlation between the return on equity and three factors of influence the rate of financial stability, the overall solvency, the Anghel score. This model can be further used in making predictions, which may allow determining the rate of success and the accuracy of predictions. 4. CONCLUSIONS Following the analysis, we drew the following conclusions: - the pharmaceutical industry has a very good liquidity, all companies showing very high rate of current liquidity.in other sectors, the situation is quite volatile, the level of this rate recorded high fluctuations; - the solvency situation is pretty good for the companies included in the study, except for few companies LACT, DAFR, RRC. This means that the firms have sufficient assets to pay the total debt if they would get in bankruptcy; - the financial stability rate indicates, in general, a high percentage of long-term funding sources in the total capital for most of the studied companies. They meet a few exceptions (PRAE, INEM, RRC and CFES), which have a very high dependence on short-term funding sources, which seriously affect their financial stability. - the return on assets is very volatile, in both years, as well as for the analized companies. Except for a few companies (BIO, ALBZ, lactate, DAFR, TGN), where this rate is roughly stable, the others alternate negative and positive changes, including obtaining negative values of the return on assets. - the return on equity has values that fluctuate within each firm and each sector. There are two companies that record negative values of the rates in all four analyzed years (RRC, CFES), but also companies that suffer significant declines in the rate in 2008

12 (SINT, INEM, CFES) or 2009 (PRAE, RRC). In addition can be highlighted a booming for UTBT. - the Anghel score places 10 companies in the non-bankruptcy in all the analyzed years (2008,2009,2010) and from the other six firms one has a poor financial situation and is at risk of bankruptcy (RRC) and the other 5 are located in area of uncertainty in all studied years.in terms of Altman score there are companies facing solvency problems and firms were the probability of a risk of bankruptcy is low. - using the statistical software SPPS we have identified a strong correlation (92%) between the return on equity(dependent variable) and the return on assets, the Anghel score (independent variable), the overall solvability this correlation is extremely important in achieving forecasts and projections. - in terms of the structure rate, the pharmaceutical sector recorded the best values, but this was not observed for the rates of return, as their negative values occur due to obtaining of operating losses or net losses. The companies that have defied the crisis with very good results in all analyzed indicators include: Antibiotics, Petrom, Transgaz, Transylvania Construction. REFERENCES 1. Anghel Ion Falimentul. Radiografie şi predicţie, Ed. Economică, Bucureşti, 2002, 2. Bătrâncea I., Dumbravă P., Bătrâncea L. Bilanţul entităţii economice, Ed. Alma Mater Cluj Napoca, 2007, 3. Buse L., Siminică M., Cîrciumaru D., Marcu N. Analiza economico-financiară,ed. Sitech, Craiova, Radu C., Ionascu I., Murărita I. Statistică teoretică Ed. Universitaria, Craiova, 2009, 5. Siminică Marian Diagnosticul financiar al firmei, ed. Sitech, Craiova, 2010, Annex no.1 List of names of firms under study and their symbols: In the pharmaceutical sector: Antibiotice S.A. - (ATB) Biofarm S.A. - (BIO) Sintofarm S.A. Bucharest - (SINT) Zentiva S.A. - (SCD) In dairy products: Albalact S.A.- (ALBZ) Lacta S.A. Giurgiu - (INEM) Lactag S.A. Costesti - (LACT) Prodlacta S.A. Brasov - (PRAE) In the oil sector: Dafora S.A. - (DAFR) Omv Petrom S.A. - (SNP) Refining Rompetrom S.A. - (RRC) S.N.T.G.N. Transgaz S.A. - (TGN) In construction: Advantageous equipment Bega S.A. Bucharest - (UTBT) Railway Construction Timisoara S.A. - (CFES) Transylvania Construction S.A. - (COTRA) SCT S.A. Bucharest - (SCTB)