*Corresponding author. Keywords: Corporate Bond, Credit Rating, Profitability, Credit Rating Quality.

Transcription

1 2017 4th International Conference on Economics and Management (ICEM 2017) ISBN: The Credit Rating of Listed Company Quality Inspection in China: Based on the Perspective of Corporate Profitability Sheng ZHANG 1 and Guo-gang HAO 1,a,* 1 School of Finance, Zhongnan University of Economics and Law, Wuhan, Hubei, China a haoguogang0513@163.com *Corresponding author Keywords: Corporate Bond, Credit Rating, Profitability, Credit Rating Quality. Abstract. Using a sample of bonds issued by non-financial listed companies during , we study the credit rating quality from the perspective of profitability. Results show that credit rating in China has a weak riskiness discriminatory power on company s profitability and it affects differently amid various sectors. Central state-owned companies have a strong riskiness discriminatory power, whereas this power is comparatively lower among local state-owned companies and private enterprises and other sectors needed to advance funds in the early stage, such as the real estate sector. 1. Introduction With the rapid development of China s corporate bond market, credit rating has become increasingly significant. Credit rating, the basis of bonds pricing, is an important measurement to evaluate the risk of corporate bonds. The quality of corporate credit rating has a direct impact on the investor s confidence in corporate bonds as well as the future development of China s bond market. The corporate s credit rating should be decided according to their financial information, while credit rating needs to consider the future profitability of the bond issuer in order to obtain the most appropriate one. The credit rating of issuers has a direct impact on the financing costs [3]. On the one hand, in order to obtain a better credit rating, issuers often use earnings management to window-dress its profitability. On the other hand, all credit rating fees are covered by the issuing company so they have the right to choose the credit rating agencies they prefer [2]. So what s the quality of China s corporate credit rating like? Can the corporate credit rating really reflect the profitability of the issuer? The discussion of these problems will be helpful to improve the overall quality of China s bond credit rating, ensure the healthy development of China s corporate bond market, and provide policy advice for regulators. This paper empirically studies the credit rating quality of Chinese companies from the perspective of corporate profitability. In order to test the rating quality more accurately, the corporate profitability has been fully considered from the aspects of profitability, liquidity, sustainability and accessibility. This paper uses a sample of bonds issued by listed non-financial companies during , and makes an empirical research on the credit rating quality of Chinese companies from the perspective of corporate profitability. 2. Research Hypothesis Based on the research of Ma Rong [4], this paper studies the credit rating quality from the perspective of corporate profitability. We mainly consider two types of participants, the bond issuers and bond rating agencies. In order to obtain a higher credit rating, reduce the cost of issuing and provide more options for the companies making decisions on capital structure, bond issuers usually window-dress their financial status through earnings management to get a higher credit rating. Therefore, this paper proposes hypothesis 1: H1: Corporate credit rating in China has a week screening ability on the corporate profitability. For those companies engaged in different industries, the capital structures are not always the 26

2 same. For example, companies (central state-owned companies, local state-owned companies, private companies, etc.) owned or controlled by different entities, owing to the different capital structures and credit qualifications, have distinctive funding gaps; on the other hand, the real estate sector, in order to advance high funds, will possibly obtain financing through the bond market which has a relatively lower cost, leading to a more obvious result of overrated credit ratings. Based on this, the paper proposes the hypothesis 2 and 3: H2: the overestimation of the credit rating in China differs from the properties of the companies. H3: the overestimation of the credit rating in China varies from the industries. 3. Empirical Model The asset quality of the companies can fully reflect the companies profitability. The higher the asset quality is, the stronger the profitability and the solvency are. On the contrary, a relatively lower profitability indicates that the profits of operating assets are less than the value gained from replacing assets for other purposes [5], as the companies future solvency has a tendency to decrease. The heterogeneity of profitability reflects the difference in the companies future profitability, which indicates the future solvency of the companies further. Therefore, we construct model 1 to test the hypothesis 1, model 2 to examine the hypothesis 2 and model 3 to further verify the hypothesis 3. Model 1: Ratings = β0 + β 1AQ + controls + µ Model 2: Ratings = β0 + β 1AQ + AQ maturity + controls + µ Model 3: Ratingsi = β 0 + β 1AQi + controls + µ i In this paper, we consider the credit rating as a dependent variable. Owing to the order of credit ratings which need to be numbered, we use the Ologit model in regression analysis. Ologit model is the one of main approaches to analyze the data, in which case the credit rating is considered as the dependent variable [1]. The stochastic disturbance term of the Ologit model is assumed to be subject to the Logitstic distribution and the likelihood function of it is obtained by using the latent variable method. Based on this, the maximum likelihood estimator can be inferred and then we can know the function s point and coefficient, which all of them meet the condition that the dependent variable must be ordered and discrete [4]. 3.1 Credit rating (Rating) In this paper, we use the corporate bonds credit rating provided at the time of issuing as a measure. As most of credit ratings of bonds issuers are above the A, we assign the credit ratings from A to AAA the values 1 to 5, and the credit ratings below the A are negligible 3.2 Profitability (AQ) This paper refers to the approach of Song Xianzhong [6] which takes corporate asset quality as a measure of corporate earnings. Song Xianzhong [6] pointed that there was a positive correlation between the enterprise assets quality, corporate profitability and the persistence of profitability. The future profitability of the company is the main factor to consider in the rating process. Therefore, this paper uses the asset quality to measure the profitability, which can reflect future profitability accurately. We learn about the method of Tang Guoping [5] and determine 15 financial indicators from 5 dimensions) to evaluate the asset quality according to the property of the cash flow generated by the assets in the future. In order to process the dependencies between the above indicators, this paper uses dynamic factor analysis to reduce the dimension (limited to the length of the article, the process is not described), and the results conducted by the final dynamic factor analysis are used as the final measurement of asset quality. 3.3 Control Variable As mentioned above, the regression function has involved a large amount of dependent variables 27

3 so we delete some of control variables selected by Shi Rong, Ma Xiaojun [4]. The dummy variables are mainly about the property of the companies and its owners. These are central state-owned company (owe = 1), local state-owned companies (owe = 2), private companies (owe = 3); cash flow ratio, Growth; debt assets ratio (equals to the total liabilities / total assets) ;Leverage; returns on asset (roa); the volume of corporate bond issue (Amount); bond maturity (Maturity). 3.4 Samples and Data In this paper, all A-share listed companies which issued credit-related corporate bonds (including short-term financing bills, mid-term financing bills, enterprises bonds, corporate bonds, etc) during are considered as samples and the credit ratings at the time of issuing are used as a measure. The sources of credit ratings and bond issuance data are from the wind database with financial data of listed companies from the Csmar Database. Table 1 presents the descriptive statistics of the main variables. As we can see, the credit ratings of our companies mainly concentrate on A to AAA level because of the strict requirements of the bond issuance posed by China Securities Regulatory Commission. The median of Chinese bond issuers profitability is 0.56, indicating that half of the bond issuers are below the average and their profitability is not very good. The average issue amount is 890 million yuan, but compared the median with the average we can find that the most of issue amounts in China are below the average. Table 1. The descriptive statistics of the main variables. Variable N mean Std maximum minimum median Credit rating 1, AQ 1, Owe 1, AQ*Owe 1, Amount 1, Maturity 1, Cash flow 1, Growth 1, Leverage 1, Empirical Analysis 4.1 The screening ability of corporate credit rating on corporate profitability The (1) in Table 2 reports the regression results of credit rating and profitability. The regression coefficient of profitability in (1) and (2) is significantly below zero at 1% confidence level, which shows that the profitability of company has a negative impact on credit rating. Profitability is an important measure of corporate profitability. The regression results (1) - (2) show that credit rating does not reflect profitability accurately and the hypothesis I is verified that credit rating can t effectively screen corporate profitability. In other words, the bond issuers window-dress its financial statements through earnings management in order to obtain a higher credit rating, which means that the screen ability of credit rating on profitability is very weak and can t accurately reflect the future profitability of bond issuers. In (3) - (5), we add the property of the companies into the regression function and then test the association between the credit rating and profitability. Results show that there is still a negative relationship between the profitability and the credit rating, and the significant level of the profitability variables is much higher than regression (2). The coefficient of property of the companies in the regression (3) is significant at the 1% confidence level and the absolute value of the profitability s coefficient is also greater, indicating that the company s property affects its credit rating and the hypothesis 2 is valid. Regression (4) tells that the profitability s coefficient is significant at the 5% confidence level as we add the cross-terms in the empirical analysis which further support the hypothesis 2. 28

4 Table 2. The credit rating of profitability of the whole samples regression results. (1) (2) (3) (4) (5) Credit rating AQ (3.93)*** (2.97)*** (2.81)*** (3.36)*** Owe (6.75)*** (6.51)*** AQ*Owe (2.77)*** (1.98)** Amount (12.44)*** (12.41)*** (12.38)*** (12.45)*** Maturity (4.90)*** (5.03)*** (4.86)*** (5.08)*** Cash folw (2.04)** (2.45)** (2.22)** (2.36)** Growth (2.41)** (2.86)*** (2.64)*** (2.74)*** Leverage (2.44)** (2.91)*** (2.68)*** (2.79)*** Net assets income rate N 1,086 1,086 1,086 1,086 1,086 Note * p<0.1; ** p<0.05; *** p<0.01 As the regression results of the control variables show, the issuing volume of the bonds and the maturity of bond are all negative at the 1% significance level, noting that the larger the volume is and the longer the maturity is, the higher the credit rating is. In order to reduce the issue costs and obtain a high credit rating, companies tend to window-dress their financial statements to whitewash, which is also confirmed in the regression results of growth and debt-assets ratios. The growth is significantly negative at the 1% confidence level as the debt-asset ratio is significantly positive at the 1% confidence level, indicating that firms with poor growth potential and high financial leverage are easy access to greater credit rating. It is because of the strict evaluation and supervision on the bonds, especially those with large issuing volume and long maturity, so it s difficult to window-dress financial statements and to obtain higher credit ratings. Thus, credit rating has strong screen ability on bonds with large issuing volume and long maturity. However, all the regression results shows the return on net assets is not significant, indicating that the credit rating can not accurately reflect the level of return on net assets, further shows that credit rating quality in China is low and can t identify the profitability of companies. Then, coefficients of the cross terms in regression (4) - (5) are significant at the 5% confidence level, noting that the credit rating is affected by the company s property. 4.2 Screening ability of credit rating on corporate profitability among different industries The regression results (6) - (12) in table 6 report the credit rating of different industries on the ability of enterprises to distinguish capacity. Results (6) - (7) show that the coefficient of profitability is significantly negative at a 10% confidence level, indicating that credit rating has lower screen ability in the transportation, warehousing, postal services and real estate sectors. Most of those need to establish big logistics systems at the beginning while the real estate sector often advance high upfront costs, leading to a shortage of capitals and intensive financing needs. Thus, enterprises are more motivated to window-dress their operating performance to obtain a higher credit rating and solve capital problems by financing from the bond market as well as reduce financing costs. Regressions (9) - (12) show the coefficient of profitability in mining industry is not significant, meaning that the credit rating can reflect the profitability of this industry. 29

5 Credit rating Table 3. The credit rating of profitability divisions regression results. (6) (7) (8) (9) (10) (11) (12) Transporta The The Electricity, tion, The estate Manufac-t constructi Wholesale mining heat, gas warehousi industry uring on and retail industry et. ng et. industry AQ (1.83)* (3.20)*** Owe (2.84)*** (3.44)*** (3.50)*** (3.69)*** (4.00)*** Amount (4.62)*** (3.97)*** (9.76)*** (3.89)*** (4.47)*** (1.76)* (6.54)*** Maturity (2.09)** (3.67)*** (2.32)** (1.69)* Cash folw (1.94)* Growth Leverage (2.55)** Net_rate (2.58)*** N Note: * p<0.1; ** p<0.05; *** p< Conclusion First, current credit ratings of bond issuers have a lower screening ability and they can t reflect the true operation situation of the companies. Overrated credit rating is a biggest obstacle to the health growth of China s bond market. As the direct financing is developing rapidly in China, solving the problem of overrated credit rating will be an important topic for China s regulators. Second, screening ability of credit rating among different properties and industries is not the same. The regression results of the profitability and credit rating show that for the central state-owned enterprises with good credit qualification and more available financing channels, their credit ratings have a strong screening ability on profitability, while for local state-owned enterprises, the screening ability is lower. Meanwhile, credit ratings of industries with high financing demand have a relatively weak screening ability. The main reason is the strict regulation measures of the bond issuance in China which means companies can t issue bonds unless they obtain an AAA credit rating. Therefore, companies are more likely to window-dress the operating results to obtain a higher credit rating and finance through the bond market at a lower cost. References [1] Altmana, Edward I. and Herbert A. Rijkenb. How Rating Agencies Achieve Rating Stability. Journal of Banking and Finance, No. 11, 2004, pp [2] Cornaggia, Alexander W. Butler and Kimberly J., Rating through the Relationship: Soft Information and Credit Ratings. working paper, [3] West, Richard R. Bond Ratings, Bond Yields and Financial Regulation: Some Findings. The Journal of Law and Economics, No. 1, [4] Rong Ma, Xiaojun Shi, Do the credit rating in China s bond market have the riskiness-discrimination power: An earning management perspective. China Economic Quarterly, No. 1, 2016, pp (In Chinese) 30

6 [5] Guoping Tang, Jun Guo, Dejun Wu. Asset Quality, Real Option and Value Embodiment. Journal of Management Science, No. 1, 2015, pp (In Chinese) [6] Xianzhong Song, Zhiwen Gao. Asset quality reflect the profitability of the empirical analysis. China Industrial Economics, No. 4, 2001 (04) (In Chinese) 31