Research on the Influence Factors of Financial Risk for Small and Mediumsized

Research on the Influence Factors of Financial Risk for Small and Mediumsized Enterprise An Empirical Analysis from 216 Companies of Small Plates, ShenZhen Stock Exchange, China 4 Fu Gang Associate professor, College of Economics and Management, Sichuan Agricultural Universy, Chengdu, China.(611130). Liu Dan Master, College of Economics and Management, Sichuan Agricultural Universy,Chengdu, China (611130). Un: Economics & Management School of Sichuan Agricultural Universy Add: No. 211, Huiming Road, Gongping Town, Wenjiang Area, Chengdu Branch Campus of Sichuan Agricultural Universy, Chengdu Cy, Sichuan Province Post Code: 611130 Abstract Based on previous research on financial risk, this article attempts to analyze financial risk factors of China's Small and medium-sized enterprises(smes) by using Alexander Bathory model and currently available data on small and medium enterprise board, ShenZhen stock exchange. Using regression analysis,financial risk was measured by Alexander Bathory model, was found: the financial risk was significantly negative-correlated wh current ratio, net prof margin, net assets ratio, the ratio of fixed assets,weakly correlated wh fixed asset turnover, total asset turnover, while no significant correlation wh debt structure, inventory turnover, accounts receivable turnover. Key Words: Small and medium-sized enterprises, financial risk, regression analysis, Empirical 1.Introduction As we know, small and medium-sized enterprises are playing an increasingly important role in the national economy in China. According to the related data shows, at present, small and medium-size enterprises take a rate of 99% among the registered enterprises from Chinese industry and commerce, and provide over 75% of the urban employment opportunies. After the outbreak of financial crisis in 2008, China is facing huge inflationary pressures in early and liquidy pressure. In 2010, the central bank had to choose to raise interest rates after several fails of being forced to raise the depos reserve rate. As a result, the largest group affected is small and medium-size enterprises. Weak in China s banking system, small and medium-sized enterprise will be more difficult to loan after the bank tighten monetary policy. Severe challenges small and medium-sized enterprises facing now are: the rise of production material and labor force, appreciation of the RMB, rise in loan interest rates, increasing of financing costs. Paying attention to the small and medium enterprises financial risk is not only of theoretical meaning, but also a realistic significance. 2. Lerature Review In recently years, many scholars devote themselves to the research of enterprise financial risks from different angles. Zhou Chunsheng and Zhao Duanduan (2006) did a empirical research to the financial 4 Liu Dan and Fu Gang are both the corresponding authors. 380

risks of listed private enterprise wh Z value, found that average level of private listed companies financial risk is significantly higher than that of state-owned holding listed companies. And in 2004 Andes Barbro, together wh MiguelJ.Bagajewicz put forward a new two-stage random management pattern to reduce financial risk from enterprise management of view. To the study of small and mediumsized enterprises financial risk, Wang Yining and Chen Zhichao(2010) found that financial risk of financing constrainted Company is higher than that of unconstrained, basing on the unbalanced panel data. And Hu Meihui mainly do the research through questionnaire, analyzing the small and mediumsized enterprises in central Taiwan wh multivariable analysis and Log regression analysis. And s financial prewarning model has four conclusion: First, the company leader has multiple professional knowledge. Second, significant environmental change will cause poor management of small and mediumsized enterprise (such as the change of government policy). Third, a sound financial system is needed. Forth, the company needs a good monoring system. The foundation of above 4 ems is useful to lower the genesis probabily of company financial crisis. In 2006, Liao Weiyan take the small and mediumsized enterprise material, which is offered by a financial instutions, to study the characteristics of these kinds of enterprises, using the Logistic regression and factor analysis, and the variable contains financial variables and the non-financial variables. The research conclusions are as below: first, when model considers the financial and non-financial variables, predictive abily of model will be superior to the model that uses financial variables only. Second, is more difficult for some young small and mediumsized companies (less than 7 years) to predict about the company financial than the older one. Once in 2005, Cao Defang and Zeng Murong used enterprises financial leverage coefficient as the dependent variable, did a general empirical research to large enterprises financial risk. They thought that the financial risks of enterprise are related wh enterprise liabilies scale and liabily structure, and have a negative correlation wh profabily and operation abily, have no obvious linear correlation wh enterprise debt interest rates and solvency. From the studies above, we can find that most scholars research mainly focuse on the concept of financial risk for SMEs, warning models, strategies, management of financial risk. there has been some scholars make empirical research at present, but relatively less. After the financial crisis, what the financial risk condion of small and medium-sized enterprises will be? how about the influence factors? All these are worthy to be discussed and further studied for us. 3. Variables Definion and Research Hypothesis Generally speaking, financial risk includes broad and narrow risk. Broad risk refers to the possibily of the actual financial condions deviation from the expected; is all risk factors reflected in the enterprise financial, including financing risk and investment risk and prof distribution risk, etc. Narrow risk refers to the possibily of debt that cannot be afforded, which is caused by financing liabilies when matures (Cao Defang, 2005). The financial risk in this paper is narrow financial risk. Based on the data choice, this paper took 216 small and medium-sized board listed enterprises and used the 2010 annual financial statements as a sample. At the same time, considering the particulary of the small and medium-sized enterprises, Alexander Bathory model was used to measure the size of the financial risk. 3.1 Definion of dependent variable From the previous research, methods of measuring the financial risks include the asset-liabily ratio method, probabilistic analysis, financial leverage coefficient, etc. Asset-liabily ratio method measuring financial risk is vague,while need Combine return on assets. Probabily analysis is greatly subjective during the calculation, and the Operation is also difficulty. Financial leverage factor is a common method used many scholars, Because of s simple calculation.but taking into the much specification of the SMEs into account, in this paper, Alexander Bathory model was used to measure the financial risk. 381

This model can be expressed as below: FR = SZL + SY + GL + YF + YZ FR is the value measuring financial risk of index, We took as dependent variable in this paper. SZL = (prof before tax + depreciation + deferred tax) / current liabilies, SY = Pre-tax prof/operating capal, GL = Shareholders' interests / current liabilies, YF = Net tangible assets / total liabilies, YZ = Working capal / total assets. The characteristics of the model is applicable to all industries, and calculation is simple.it also can be used to predict the possibily of bankruptcy,as well as measure corporate strength. In Alexander Bathory s view, the smaller the value of FR is, the more weak the enterprise strength is and the more financial risks of enterprise have. 3.2 Definion of independent variables We Summarized in five main factors that affect SME's financial risk, in this article, were debt structure, solvency, performance, operation abily, and capal structure, set 12 indexs(x1~x12) as independent variables to express the the five main factors. The detail was shown in Table 1. Table 1: Definion of model variables Variable name Variable code Related definion Financial risk metric values FR Bathory s model metrics Debt structure x1 Current liabilies / non-current liabilies 3.3 Research hypothesis Solvency Performance Operation abily Capal structure x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 Current Ratio Quick Ratio Asset-liabily ratio Net prof rate Total asset returns Inventory turnover Fixed asset turnover Total asset turnover Accounts receivable turnover Net assets ratio Fixed assets ratio According to the related theory, hypothesis can be put forward as following: SMEs financial risk is posive wh debt structure. Debt structure is the ratio between current liabilies and long-term liabilies (non current liabilies) proportion in the total liabilies of the enterprise. Compared wh the long-term debt financing, Current liabilies financing is short-term, low costand more debt risk relatively. SMEs financial risk is negative wh solvency. Solvency refers to the solvency indicator that company repay maturing debt (including principal and interest). It can be divided into shortterm liquidy and long-term solvency indicators. The Stronger corporate solvency is, the more likely debt service is on schedule, and the less likely financial risks appear. SMEs financial risk is negative wh profabily. profabily refers to the profabily level of enterprise production and management. The more Corporate profabily is, the more profs get from the production and operation, the more able to guarantee of debt due for repaymenthe less likely financial risks appear. 382

SMEs financial risk is negative wh Operation abily. Operation abily depends on the strength of the turnover rate of assets, asset operation, asset management and other factors. The strong Operation abily can contribute to the growth in profabily, which in turn guarantee enterprises of good solvency, reduce financial risk. SMEs financial risk is negative wh Capal structure. The higher net assets ratio in total assets is, the more secure credors debt is. In the same way, the ratio of fixed assets can effectively protect the interests of credors, so as to reduce financial risk. 4. Empirical Analysis The research data of this paper was based on 2010 annual reports of 216 listed enterprises, which were randomly selected from small and medium plate of Shenzhen stock exchange, china.then we eliminated 14 enterprises that non-current liabilies was zero. Statistical software excel2003 and spss16.0 were used to process the data. 4.1 Descriptive statistical analysis Firstly, we did descriptive statistics analysis.it showed that the Sample of SMEs, in the research, had a big differences in operating condion, capal formation and so on. The maximum value of Financial risk is 630 times of the minimum, the maximum of asset-liabily ratio was to 97.3%, minimum value was 1.83%, and the standard deviation reached 19.22. The average of Current Ratio and quick ratio were both above 1.5, to some extent, indicated that sample enterprises liquidation capacy is relatively strong. Insert table 2 here. 4.2 Correlation analysis Table 2: Descriptive statistical analysis of sample N min max mean stddev FR 199.06 37.85 5.3830 5.58819 x1 202.13 5931517.00 29494.5887 4.17331E5 x2 202.29 20.11 2.1774 2.14723 x3 202.19 16.83 1.6466 1.91181 x4 202 1.83 97.30 43.4368 19.21789 x5 190.59 66.81 11.1185 9.93859 x6 190.44 30.31 7.3168 5.42075 x7 184.29 1683.66 15.3014 124.36457 x8 202.11 94.30 5.4279 10.45860 x9 202.09 6.61.8435.63893 x10 201 1.23 7876.48 76.4729 579.02426 x11 202 2.70 93.40 55.1571 19.13594 x12 202.35 87.38 27.4230 15.23601 Then, we did Correlation analysis for the sample, the result was shown in table 3.The Correlation analysis indicated that FR had a significantly posive correlation wh Current ratio, quick ratio, net prof margin, return on total assets, net assets ratio,in other words, financial risk had a significantly negative correlation wh Current ratio, quick ratio, net prof margin, return on total assets, net assets ratio. FR was significantly negative wh total asset turnover, asset-liabily ratio, 383

fixed asset ratio, and no significant correlation wh debt structure, inventory turnover, fixedasset turnover, receivables turnover. Table 3: correlation analysis x1 x2 x3 x4 x5 x6 Pearson -.005.899.893 -.702.635.462 Sig..474.000.000.000.000.000 x7 x8 x9 x10 x11 x12 Pearson -.069 -.081 -.141 -.081.719 -.110 Sig..185.146.033.146.000.077 4.3 Multiple linear regression Taking FR as dependent variable and the value of x1~x12 as independent variables,we did Multiple linear regression.first time, the regression result was not very satisfactory when put all 12 independent variables into the model. considering there may have collineary problem between variables, we removed the variables of linear obvious: Quick ratio, debt ratio, return on total assets.then the regression result was better. Regression coefficients was shown below(table 4). Table 4: Regression coefficients a Nonstandardized coefficient standard coefficient B standard error t Sig. (constant) -4.864.684-7.114.000 debt structure(x1) -1.909E-7.000 -.016 -.601.549 Current Ratio(x2) 1.869.092.722 20.388.000 Net prof rate(x5).116.022.193 5.348.000 Inventory turnover(x7).000.001 -.017 -.608.544 Fixed asset turnover(x8).021.016.042 1.339.182 Total asset turnover(x9).322.238.039 1.350.179 Accounts receivable turnover(x10).000.000 -.018 -.676.500 Net assets ratio(x11).059.012.195 4.951.000 Fixed assets ratio(x12).048.012.135 4.127.000 a. dependent variable: FR From the Multiple linear Regression,we could see that the Sig of Current ratio, net prof rate, net assets ratio, the ratio of fixed assets were 0.000, indicated that the four variables had a significant linear relation wh Financial risk metric values FRand they were the main factors affecting financial risk. The Sig of Fixed asset turnover, total asset turnover were less than 0.200, had a certain significance, and a certain impact on the financial risk. The sig of debt structure, inventory turnover, accounts receivable turnover rate were less significant, the impact on financial risk is not obvious. 384

Table 5: Regression testing model Sum of squares df mean square F Sig. R 2 Adjusted R 2 Standard error of estimate Regression 4491.259 9 499.029 144.201.000 a.890.884 1.86028 residual 553.703 160 3.461 Total 5044.962 169 The next, we did regression test, just as table 5. From the result of test, we could seef=144.029psignificance levelwas 0.000R 2 of regression model was 0.890, adjusted R 2 was 0.884. In the case of large samples (n=169)the fness (R 2 )of the model was well. Finallywe did multicollineary test for the nine variables to avoid multicollineary. The test index we used was tolerance (TOL) and variance inflation factor (VIF). The tolerance of variables X i can be 2 defined as: Toli = 1 R.When VIF was more than 10, in general, meaned that strong collineary i appeared in variables. The result of multicollineary test showed that the nine variables VIF were both less than 10, so the nine variables can be considered no significant multicollineary. 5. Conclusion and Analysis Through the above analysis of the sample data, we can get a conclusion as below: SMEs financial risk has a significant negative correlation wh solvency in china, especially flow ratio that reflects short-term debt paying abily, this is consistent wh the front assumption. From the front descriptive statics analysis, we know that the mean value of current liabilies is up to 29494 times of the long term liabilies. It fully explained that SMEs in china mainly choose short-term debt financing, certainly will need a lot of current assets to pay for interest and principal. So current ratio directly affects SMEs financing risk whether they could meet a lot of liquidy spending for short-term debt. SMEs financial risk has a significant negative correlation wh prof abily (net prof rate) in china. This conclusion is also consistent wh what we get front. All the funds of the enterprise need to get complement and expand through earnings, no matter is used to cover losses, or expand enterprise production scale or repay the debts. If an enterprise has no prof for long term, will face the repayment pressure of maturing debt, damage enterprises reputation, and also can not continue financing. Eventually,the enterprises will fall into financial risk inevably. The higher return on investment and the better profabily of the enterprise are, the less occurrence of the financial risk will be. SMEs financial risk has a significant negative correlation wh the capal structure in china. In this paper, we selected two indexs to react capal structure: net assets ratio and fixed assets ratio, which all have good linear correlation wh financial risk. Also can be understood easily from the realy that net assets is low in the total assets, then the size of debt is high.as a result, more principal and interest is due to repay. It will cause certain pressure for the enterprises capal flow, at the same time might affect other production activies. Especially when enterprises was under the circumstance of not-good management, s very easy to make enterprises sink into financial risk, even insolvent. Fixed assets is the foundation of enterprise deeper development, at the same time, s also the guarantee for debt financing of SMEs, such as mortgage financing, secured financing etc. In some extend, the size of fixed assets ratio of SMES indirectly react the size of continuing financing, especially when financial suation is not good. So fixed assets ratio of enterprise are crucial whether the enterprise can continue to finance or not. SMEs financial risk has no obvious linear correlation wh debt structure in china. this isn t consistent wh our front hypothesis. Seeing from the result of descriptive statistics, SMEs debt structure do exist imbalance status, current liabilies is major in total liabilies, and long-term debt ratio is very low. As what is analysed in this paper, this indicator didn't show a good significant. The reason may be due to s scale and other restriction reasons. SMEs mainly depend short-term debt financing, at the same time, s Current asset is good fluidy that can well ease payment pressure brought by short-term debt, thereby reducing the incidence of financial risk As interaction, debt structure does not become the main factor that influence the financial risk in the sample regression analysis. 385

SMEs financial risk has no significant linear correlation wh management abily in china. It is different from many other scholars' opinion, also different wh the foregoing hypothesis. Here we can only explain that the indexs we selected don't show obvious linear correlation to FR. Reasons might be on the selection of index, there are many indexes can be used to measure financial risk. Especially to SMEs financial risk research, more factors should be considered, s easy to out of control. Only by a few index, is often difficult to comprehensive and accurately reflect the relationship between them. 386

References Andes BarbroMiguel J Bagajewicz. (2004).Managing Finacial Risk in Planning under UncertaintyAIChE Journal,50,963 989 Mao Xinshu, & Yang Youhong.(2009).Account Research Study. Internal Control and Risk Management Journal, No.5,93-95. Wang Jining, & Chen Zhichao.(2010). Financing Constraints, Financial Risk and Empirical Study on the Growth of SMEs. Seeker Journal, No.9, 15-18. Zhu Xiping, & Wang Chun.(2004). Exploration of Financial Risk Measurement Methods. Monthly Finance and Accounting,No.8, 12-13 Hu Meihui.(2007). Exploration of Company's Financial Risk Warning Model - Example for Small and Medium Enterprises in Central Region of Taiwan. Whe Paper on SMEs, Taiwan. Liao Tingwei.(2006). Study of SME Cred Risk Models of Taiwan. Master's Thesis of International Trade Department, Soochow Universy, Taiwan. Cao Defang, & Zen Muli.(2005). An Empirical Analysis of Factors Influencing Financial Risk of Listed Companies in China. Technoeconomics & Management Research, No.6, 37-38 Zhou Chunsheng, & Zhao Duanduan.(2006). Empirical Research on Financial Risks of China's Private Enterprises. Soft Science of China. 387