Impact of equity, credit risk on financial stability of Vietnamese commercial banks

ratio of equity to total assets (EQTA) could help to increase the financial stability of Vietnamese commercial banks but only to a certain extent. If the ratio of equity to total assets (EQTA) exceeds this level, the increase in equity may reduce the financial stability of Vietnamese commercial banks due to the decreased business performance. . The ratio of equity to total assets at the point of reversing the financial stability of Vietnamese commercial banks is the optimal ratio of equity to total assets, where at this level the financial stability of Vietnamese commercial banks is the highest. Third, the study points to the effects of the financial crisis on bank financial stability, the statistically significant 5% statistically significant and negative, indicating that in a crisis situation increasing the volatility of Vietnamese commercial banks. In addition, the study also shows the specific impact of equity on the financial stability of commercial banks under the influence of crisis conditions: in times of crisis, the increase in equity ratio The total assets will increase the volatility of Vietnamese commercial banks. Fourthly, besides looking for evidence on the impact of credit risk on bank financial stability, the study also looked at this impact in the context of the financial crisis in 2008 and 2009. The regression results show that the regression coefficient of the crisis variable is statistically significant at 5% and the negative sign indicates that in the context of crisis, the adverse effect of credit risk on stability The increase in the NPL ratio on total outstanding loans will reduce the financial stability of Vietnamese commercial banks when other factors remain unchanged. , this is consistent with the results of previous studies of countries around the world. Finally, through the estimation results of the regression model, the author has proposed capital management and credit risk management for Vietnamese commercial banks in order to increase financial stability of commercial banks. 1.8. Structural thesis. To achieve the objectives of the study, excluding the table of contents, the list of acronyms, the list of tables, the list of references, and the annex, the thesis is designed into five chapters, including The main contents are as follows: - Chapter 1: Introduction - Chapter 2: Theoretical bases on the impact of equity and credit risk on the financial stability of commercial banks. - Chapter 3: Research Methods and Data - Chapter 4: Results of Study on the Impact of Equity and Credit Risk on Financial Stability of Vietnamese Commercial Banks. - Chapter 5: Conclusions and solutions to enhance financial stability of Vietnamese commercial banks. CHAPTER 2: THEORETICAL MECHANISM OF THE IMPACT OF OWNERSHIP AND CREDIT RISK WITH THE FINANCIAL STABILITY OF COMMERCIAL BANKS. 2.1. The theory of equity of commercial banks 2.1.1. The concept of equity of commercial banks For commercial banks, basically, in the narrow sense, equity is money that shareholders, owners contribute (capital actually contributed) to enjoy the bank's income in the future. In broad terms, bank equity is viewed as the capital of the banker for supporting banking operations. Such definitions include the bank's reserve funds and are referred to as the capital of the shareholders. Throughout the course of operations, equity can accumulate up or down. However, for state managers, the issue of the adequacy of bank capital is crucial, especially after the global financial crisis has made one of the solutions that governments of some countries Used to rescue the banking system is to rescue and nationalize, using government funds to save the collapse of banks. 2.1.2. Owners' equity of commercial banks 2.2. Credit risk theory at commercial banks 2.2.1. Credit risk concept Credit risk is the potential loss that may occur as a result of customers not being able or able to fulfill their obligations fully or on time as committed. Credit risk is the likelihood of an unexpected difference between actual and expected returns, the full amount of principal and interest that results in financial loss ie a decrease in net income and a reduction in net income. market value of capital. Among the types of risks to banking operations, CIs most often face credit risks. When the credit risk occurs, the credit institution will not be able to recover fully and on time the credit granted because the customer fails to pay all debts to the credit institution as committed, for whatever reason. causing damage to CIs, causing loss of capital and impaired ability to pay and ability to pay debts. 2.2.2. Credit risk classification According to Rose (2012), based on the underlying causes of risk, credit risk is divided into transaction and portfolio risk Transaction risk consists of three main components: risk, risk, and operational risk. Portfolio risk: a form of credit risk that is caused by limitations in the management of a bank's loan portfolio, is divided into two categories: internal and collective risk. Medium. 2.2.3. Measurement of credit risk at commercial banks Credit risk measurement in credit activities is the calculation of the specific number of risk that the bank is facing and the losses it causes. There are many methods to measure credit risk, some typical methods include: Credit risk measurement based on reserve (Bangladesh Bank, 2010). Estimation of credit losses is based on the Internal Basis II (IRB) database. Due to the difficulty of data collection, the credit risk in this study was calculated by the credit risk measurement based on the reserve level. As such, the ratio of bad debt to total outstanding loans will be used by the author to represent credit risk. 2.3. Theoretical basis on financial stability of commercial banks 2.3.1. The concept of financial stability 2.3.2 The concept of financial stability of banks The financial stability of commercial banks is achieved when the banks operate smoothly, not affected by the current and future unwanted agents, which are firmly supported by economic shocks. The financial stability of banks may be interrupted by the operation of internal financial factors and strong shocks leading to vulnerabilities. Shocks can come from the external environment, macro factors, the role of creditors and debtors in banks, policies or changes in the institutional environment ... Any impact Shocks to vulnerabilities can lead to the collapse of commercial banks and disrupt banking intermediaries and intermediaries. To be more serious, it can lead to financial crisis and the implications for the economy. 2.3.3. The importance of banking and financial stability 2.3.4. The measure of financial stability of the bank Finding a way to measure the financial stability of the banking system and anticipating instability that could lead to bankruptcy is always one of the top concerns of researchers. financial sector. Historically, many methods have been developed to do this, such as: Method for measuring financial stability by Merton model Method for measuring stability by CAMEL model The method of measuring financial stability by Z-score 2.4. The theory of the impact of equity on the financial stability of banks Debates on the impact of equity on the financial stability of banks have recently formed two theoretical perspectives on this impact (Thakor, 2014). 2.4.1. The theory of increasing equity reduces the bank's financial stability The first theoretical view is that increasing equity will reduce profits thereby reducing the bank's financial stability. This view is rooted in the debate surrounding the capital structure theory of Modigliani and Miller (1958). Modigliani and Miller (1958) argue that capital structure does not affect the value of the business. However, this conclusion is only true in perfect market conditions and in reality this is unlikely. De Nicolo & Turk Ariss (2010) argue that capital is one of the inputs to the bank's operations. The increase in customer deposits in total capital, ie, the reduction in the equity ratio of total assets, will help increase the business capital for the bank to improve profitability thereby increasing the stability. the bank's financial position. Huang and Ratnovski (2009), based on OECD data, found no relationship between bank capital and business performance. In other words, it is impossible to conclude with certainty that bank capital will always extend financial stability. 2.4.2. The theory of increasing equity increases the financial stability of the bank The second theoretical view that higher equity will enable banks to make better choices in their businesses while at the same time better controlling credit performance, thereby increasing financial stability. Bank. This theoretical view supports the role of equity in the financial stability of banks in three respects (Matten, 1996). 2.5. Theory of the impact of credit risk on the financial stability of banks Credit risk affects the probability of bank default, which reduces the bank's financial stability in three ways: First, the risk of undermining the credibility of a bank, a big risk bank, is a bank that does not operate effectively. Second, Berger, AN, and partner (1997), Boyd, J. H, and cs. (1988), Salas, V., and cs. (2002) show that the risk of insolvent partially bank The reason is that the risky credits make repayment difficult, while the deposits and savings of the people still have to pay on time, while not mobilizing capital. Due to the loss of prestige, so the withdrawers see the situation of the Bank as the withdrawal of more money, resulting in difficulties in the payment phase, resulting in financial instability. Commercial banks. Third, according to Cai, J., and partner (2008), He, Z., and partner (2012), Eklund, T and partner (2001), Dermine, J. (1986). Blair and partner (1978), the risk that results in declining returns due to the risk of financial loss. The explanation of the impact of credit risk on the bank's financial stability is considered by the author through this transmission effect. Some of the theoretical explanations for this effect may be as follows: Asymmetric Information Theory, Representation Theory. 2.6. Overview of related studies 2.6.1. Studies use the Z-score to measure the financial stability of commercial banks The use of Z-scores to measure the financial stability of commercial banks has attracted many domestic and foreign researchers. Studies such as Boyd & Partner (2006), Soedarmono & partner (2011), Rahman & gcg (2012). Local researches include Nguyễn Đăng Tùng & Bùi Thị Len (2015), Hoàng Công Gia Khánh & Trần Hùng Sơn (2015). 2.6.2. Studies on the impact of equity on the financial stability of commercial banks. International studies on the impact of equity on the financial stability of commercial banks can be cited as: Aggrawal and Jacques (2001), Rime (2001), Godlewski (2004) ), Aggrawal and Jacques (2001), Abba et al. (2013), Jacob Oduor et al. (2017). Domestic studies on the impact of equity on the financial stability of commercial banks include Vũ Thị Hồng (2015), Lê Thanh Ngọc and partner (2015), Hoàng Công Gia Khánh and Trần Hùng Sơn (2015), Nguyễn Minh Hà & Nguyễn Bá Hướng (2016). 2.6.3. Studies on the impact of credit risk on the financial stability of commercial banks Studies on the impact of credit risk on the financial stability of commercial banks are relatively few. These include Beck & GCG (2009), Consuelo Silva Buston (2012). The first study examining the impact of credit risk on the financial stability of commercial banks is the study by Björn Imbierowicz and Christian Rauch (2014). CHAPTER 3: METHODOLOGY AND RESEARCH DATA 3.1. Research process Diagram 1: Research Process 3.2. Research Methods 3.2.1. Measure the financial stability of commercial banks Inheritance of the Z-score calculation method for the banks of Boyd & Graham (1986), Hannan & Hanweck (1988), Boyd & partner (1993), this study calculates the Z-score for Banks are as follows: 𝑍𝑠𝑐𝑜𝑟𝑒𝑖𝑡 = 𝑅𝑂𝐴𝑖𝑡 + 𝐸𝑄𝑇𝐴𝑖𝑡 𝛿𝑅𝑂𝐴𝑖𝑝 𝑍𝑠𝑐𝑜𝑟𝑒𝑖𝑡 is the Z-score measures the bank's financial volatility in year t 𝑅𝑂𝐴𝑖𝑡 is the return on total assets of bank i in year t, calculated as the after-tax profit divided by total assets. 𝐸𝑄𝑇𝐴𝑖𝑡 is the ratio of equity to total assets of bank i in year t, calculated by the average equity divided by the total average assets. 𝛿𝑅𝑂𝐴𝑖𝑝 is the standard deviation of the bank's ROA during the study period p. 3.2.2. Model and hypothesis 3.2.2.1. Research models Based on the study by Jacob Oduor et al. (2017), the authors use models demonstrating the impact of equity on the financial stability of Vietnamese commercial banks under different research conditions. . Specific research models are as follows: ln𝑍𝑠𝑐𝑜𝑟𝑒𝑖,𝑡 = 𝛽0 + 𝛽1𝐸𝑄𝑇𝐴𝑖,𝑡 + 𝛽2𝐵𝐴𝑁𝐾𝑆𝐼𝑍𝐸𝑖,𝑡 + 𝛽3𝐿𝑇𝐷𝑖,𝑡 + 𝛽4𝑅𝑂𝐸𝑖,𝑡 + 𝛽 𝐶𝑅𝐸𝑖,𝑡 + 𝛽6𝐺𝐷𝑃𝑖,𝑡 + 𝛽7𝐼𝑁𝐹𝑖,𝑡 + 𝜖𝑖 (1) ln𝑍𝑠𝑐𝑜𝑟𝑒𝑖,𝑡 = 𝛽0 + 𝛽1𝐸𝑄𝑇𝐴𝑖,𝑡 + 𝛽2𝐵𝐴𝑁𝐾𝑆𝐼𝑍𝐸𝑖,𝑡 + 𝛽3𝐿𝑇𝐷𝑖,𝑡 + 𝛽4𝑅𝑂𝐸𝑖,𝑡 + 𝛽 𝐶𝑅𝐸𝑖,𝑡 + 𝛽6𝐺𝐷𝑃𝑖,𝑡 + 𝛽7𝐼𝑁𝐹𝑖,𝑡 + 𝛽8𝐸𝑄𝑇𝐴 2 𝑖,𝑡 + 𝜖𝑖 (2) ln𝑍𝑠𝑐𝑜𝑟𝑒𝑖,𝑡 = 𝛽0 + 𝛽1𝐸𝑄𝑇𝐴𝑖,𝑡 + 𝛽2𝐵𝐴𝑁𝐾𝑆𝐼𝑍𝐸𝑖,𝑡 + 𝛽3𝐿𝑇𝐷𝑖,𝑡 + 𝛽4𝑅𝑂𝐸𝑖,𝑡 + 𝛽 𝐶𝑅𝐸𝑖,𝑡 + 𝛽6𝐺𝐷𝑃𝑖,𝑡 + 𝛽7𝐼𝑁𝐹𝑖,𝑡 + 𝛽8𝐾𝐻𝑈𝑁𝐺𝐻𝑂𝐴𝑁𝐺𝑖,𝑡 + 𝜖𝑖 (3) ln𝑍𝑠𝑐𝑜𝑟𝑒𝑖,𝑡 = 𝛽0 + 𝛽1𝐵𝐴𝑁𝐾𝑆𝐼𝑍𝐸𝑖,𝑡 + 𝛽2𝐿𝐿𝑃𝑖,𝑡 + 𝛽3𝐿𝑂𝐴𝑁𝑇𝐴𝑖,𝑡 + 𝛽4𝐶𝐼𝑅𝑖,𝑡 + 𝛽 𝑅𝑂𝐸𝑖,𝑡 + 𝛽6𝐺𝐷𝑃𝑖,𝑡 + 𝛽7𝑁𝑃𝐿𝑖,𝑡 + 𝛽8𝐼𝑁𝐹𝑖,𝑡 + 𝜖𝑖 (4) ln𝑍𝑠𝑐𝑜𝑟𝑒𝑖,𝑡 = 𝛽0 + 𝛽1𝐵𝐴𝑁𝐾𝑆𝐼𝑍𝐸𝑖,𝑡 + 𝛽2𝐿𝐿𝑃𝑖,𝑡 + 𝛽3𝐿𝑂𝐴𝑁𝑇𝐴𝑖,𝑡 + 𝛽4𝐶𝐼𝑅𝑖,𝑡 + 𝛽 𝑅𝑂𝐸𝑖,𝑡 + 𝛽6𝐺𝐷𝑃𝑖,𝑡 + 𝛽7𝑁𝑃𝐿𝑖,𝑡 + 𝛽8𝐾𝐻𝑈𝑁𝐺𝐻𝑂𝐴𝑁𝐺 + 𝛽9𝐼𝑁𝐹𝑖,𝑡 + 𝜖𝑖 (5) ln𝑍𝑠𝑐𝑜𝑟𝑒𝑖,𝑡 = 𝛽0 + 𝛽1𝐵𝐴𝑁𝐾𝑆𝐼𝑍𝐸𝑖,𝑡 + 𝛽2𝐿𝐿𝑃𝑖,𝑡 + 𝛽3𝐿𝑂𝐴𝑁𝑇𝐴𝑖,𝑡 + 𝛽4𝐶𝐼𝑅𝑖,𝑡 + 𝛽 𝑅𝑂𝐸𝑖,𝑡 + 𝛽6𝐺𝐷𝑃𝑖,𝑡 + 𝛽7𝑁𝑃𝐿𝑖,𝑡 + 𝛽8𝑁𝑃𝐿𝑖,𝑡 × 𝐾𝐻𝑈𝑁𝐺𝐻𝑂𝐴𝑁𝐺 + 𝛽9𝐼𝑁𝐹𝑖,𝑡 + 𝜖𝑖 (6) Table 3.1. Synthesis of variables in the research model Variable name Symbol Measure Expectations about accents Dependent variable Financial stability lnZscorei,t 𝑙𝑛𝑍𝑠𝑐𝑜𝑟𝑒𝑖𝑡 = ln ( 𝑅𝑂𝐴𝑖𝑡 + 𝐸𝑄𝑇𝐴𝑖𝑡 𝛿𝑅𝑂𝐴𝑖𝑝 ) Independent variables Equity ratio of total assets EQTA Equity Total assets + NPL ratio of total outstanding loans NPLi,t Nonperforming loans Total loans - The size of the bank BANKSIZEi,t Logarithm (Total assets) - Ratio of total outstanding loans to total deposits LTD Total loans Total deposits - Provision for credit losses LLPi,t Loan loss provisions Total loans + Lending rate on total assets LOANTAi,t Total loans Total assets +/- Net profit on total equity ROE Net income Equity + The ratio of operating expenses to net operating income CIR3.2 Operating expenses Net operating income - Credit growth CRE Total loanst − Total loanst−1 Total loanst−1 - Growth of GDP GDP GDPt − GDPt−1 GDPt−1 + Inflation rate INF CPIt − CPIt−1 CPIt−1 - 3.2.2.3. Research hypothesis The author makes the following assumptions: Hypothesis H1: The ratio of equity to total assets is positively correlated with the financial stability of the bank. Hypothesis H2: the effect of the ratio of equity on total assets to the bank's financial stability is nonlinear. Hypothesis H3: The higher the ratio of bad debt to total outstanding loans, the lower the financial stability of the bank. Hypothesis H4: The impact of the financial crisis on the financial stability of negative banks. Hypothesis H5: In the context of financial crisis, the negative impact of credit risk on the financial stability of the bank will increase. 3.3. Collect and process data ❖ Sample size In principle, the sample size must be at least 5 times the number of variables in the model (Nguyễn Đình Thọ, 2011). The empirical model contains at most 10 variables, so the minimum sample size is 50 observations. With the table data consisting of 24 commercial banks collected from 2008 to 2016, the sample consisted of 9 x 24 = 216 observations and met compliance requirements. Over time, this data is the balance sheet data. ❖ Data collection and processing Secondary data on the variables in the research model are collected by the author from reliable sources, namely: - GDP: data on the annual growth rate of GDP are taken from the General Statistics Office of Vietnam from 2008 to 2016. - INF: Annual CPI inflation data is taken from the General Statistical Office of Vietnam from 2008 to 2016. - CRE: annual credit growth calculations are taken from the State Bank of Vietnam from 2008 to 2016. - Calculated data for the indicators: Financial stability of the bank (Zscore), NPL ratio of total outstanding loans (NPL), Owners' equity ratio (EQTA), Regulation BANKSIZE, LLP, LOANTA, CIR, CIRCULAR Net Profit Owners' Equity (ROE), Outstanding Balance on Total Deposits (LTD) is derived from audited financial statements of 24 commercial banks. 3.4. Estimation method ❖ Descriptive statistics ❖ Fixed Effects (FE) ❖ Feasible General Least Square (FGLS) ❖ System General Method of Moments (SGMM) CHAPTER 4: RESULTS OF IMPACT ON OWNERSHIP AND CREDIT RISK TO THE FINANCIAL STABILITY OF VIETNAM COMMERCIAL BANK 4.1. Statistics describe the research sample and correlations between variables ❖ Describe the sample Table 4.1. Descriptive statistics results Variables Number of observations Mean Standard error Min Max ZSCORE 216 24,54225 11,59947 1,949984 62,19548 BANKSIZE 216 18,06595 1,227456 14,69872 20,72988 LLP 216 0,0206197 0,00853452 0,0005517 0,247542 LOANTA 216 0,5037979 0,1519413 0,0046616 0,8516832 CIR 216 0,859185 0,190839 0,013187 1,218748 ROE 216 0,0837954 0,0867394 - 0,08200214 0,2846455 NPL 216 0,0324069 0,0116753 0,00351 0,1128462 GDP 216 0,0591846 0,004797 0,0524737 0,0668 INF 216 0,090399 0,0692676 0,0063061 0,2311632 LTD 216 0,8663509 0,2540645 0,1931 2,0911 CRE 216 0,3119722 0,7495143 -0,3129 10,5886 Source: Calculated results from STATA 12.0 software ❖ Correlation matrix Table 4.2. Correlation matrix Source: Calculated results from STATA 12.0 software ❖ Multi-collinear testing Table 4.3: Multi-collinear testing between independent variables Variables VIF 1/VIF BANKSIZE 1,33 0.750691 ROE 1,25 0.801947 INF 1,23 0.814705 GDP 1,12 0.890429 NPL 1,11 0.903331 CIR 1,10 0.912241 inf 0.0483 -0.3291 -0.0921 -0.1533 -0.0673 0.0822 -0.0185 -0.2286 1.0000 gdp -0.0687 0.1922 0.0838 0.0533 0.0073 -0.0362 -0.1839 1.0000 npl -0.0624 -0.1044 -0.0120 0.0208 0.2057 -0.1553 1.0000 roe -0.0151 0.3066 -0.0035 0.1766 -0.2332 1.0000 cir 0.1289 -0.0730 0.0354 -0.0320 1.0000 loanta 0.2662 0.2149 0.0317 1.0000 llp 0.0111 0.0716 1.0000 banksize -0.2458 1.0000 zscore 1.0000 zscore banksize llp loanta cir roe npl gdp inf CRE 1,29 0,777268 LTD 1,12 0,890348 LOANTA 1,08 0.923829 LLP 1,02 0.984787 VIF Trung bình 1,15 Source: Calculated results from STATA 12.0 software 4.3. Model estimation results: 4.3.1. Findings on the impact of equity on the financial stability of Vietnamese commercial banks Using STATA software with 216 observation balance panel data (n = 216) covering the period from 2008 to 2016 of 24 banks presented in Chapter 3. Estimation of the model (1) by Fixed effects (FE) and random effects (RE) are as follows: Table 4.4. Estimation of the model (1) by fixed effects: Zscore Coefficient Standard error t P>t BANKSIZE 0,0344532 0,0464373 0,74 0,459 EQTA 2,769679 0,2956981 9,37 0,000 LTD 0,2197508 0,0921098 2,39 0,018 ROE 0,5075539 0,2274639 2,23 0,027 GDP -2,425598 3,34603 -0,72 0,469 INF -0,8579331 0,3085808 -2,78 0,006 CRE 0,0375023 0,0241674 1,55 0,122 Constant 2,191053 0,8565131 2,56 0,011 Source: Calculated results from STATA 12.0 software Table 4.5. Estimation of the model (1) by random effects: Zscore Coefficient Standard error t P>t BANKSIZE 0,0421743 0,0392828 1,07 0,283 EQTA 2,706582 0,3000437 9,02 0,000 LTD 0,2791259 0,0920599 3,03 0,002 ROE 0,581493 0,237232 2,45 0,014 GDP -3,176133 3,42147 -0,93 0,353 INF -0,8791432 0,3069873 -2,86 0,004 CRE 0,0220938 0,025174 0,88 0,380 Constant 2,051648 0,7426073 2,76 0,006 Source: Calculated results from STATA 12.0 software Table 4.6. Hausman test Source: Calculated results from STATA 12.0 software Table 4.7. Modified Wald test results Prob>chi2 = 0.8086 = 3.75 chi2(7) = (b-B)'[(V_b-V_B)^(-1)](b-B) Test: Ho: difference in coefficients not systematic B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg CRE -1.072158 -.761137 -.3110206 .2800944 INF -1.323078 -.9815084 -.3415694 .3590954 GDP 5.068301 2.212541 2.85576 2.257929 ROE -1.001225 -1.037827 .0366015 .2440212 LTD .3598966 .359359 .0005377 .0713883 EQTA 2.784412 2.394527 .3898853 .433441 SIZE -.1533421 -.0582665 -.0950756 .0914387 fe1 . Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients Source: Calculated results from STATA 12.0 software Table 4.8. Wooldridge test results Source: Calculated results from STATA 12.0 software Table 4.9. Model estimation results (1) by Feasible General Least Square – FGLS Zscore Coefficient Standard error t P>t BANKSIZE 0,0182613 0,0239508 0,76 0,446 EQTA 2,464614 0,5302192 4,65 0,000 LTD 0,3385358 0,0857626 3,95 0,000 ROE 0,7097366 0,4222151 1,68 0,093 GDP -3,688005 3,682989 -1,00 0,317 INF -0,9334238 0,3443416 -2,71 0,007 CRE -0,1158166 0,0728402 -1,59 0,112 Prob > chibar2 = 0.0000 chibar2(01) = 261.37 Test: Var(u) = 0 u .06949 .2636096 e .0515631 .2270751 lnz .220037 .469081 Var sd = sqrt(Var) Estimated results: lnz[id,t] = Xb + u[id] + e[id,t] Breusch and Pagan Lagrangian multiplier test for random effects Prob > F = 0.0008 F( 1, 23) = 14.875 H0: no first-order autocorrelation Wooldridge test for autocorrelation in panel data Constant 2,57371 0,5295018 4,86 0,000 Source: Calculated results from STATA 12.0 software Estimates show that the regression coefficient of the EQTA variable is 2.464614 which is statistically significant and has a positive value. This shows that as the ratio of equity to total assets increases, it increases the Z ratio. This increases the financial stability of commercial banks. So the H1 hypothesis is true. This finding is consistent with studies by Godlewski (2004), Abba et al. (2013), Jacob Oduor et al. (2017). In addition, the ratio of outstanding loans to total deposits, inflation rate, and the ratio of net profit to equity also have an impact on the financial stability of commercial banks in the sample. Estimation of the model (1) shows that as the ratio of equity to total assets increases, it will have a positive impact on the financial stability of commercial banks in the sample. The author continues to look for evidence on the non-linear effects of the ratio of equity to total assets and the financial stability of commercial banks through model (2). The results of model estimation (2) are presented in the following table: Table 4.10. Model estimation results (2) by Feasible General Least Square (FGLS) Zscore Coefficient Standard error t P>t BANKSIZE 0,0419644 0,0249983 1,68 0,093 EQTA 4,262651 0,9049482 4,71 0,000 EQTA2 -2,851388 1,552827 -1,84 0,066 LTD 0,3071051 0,0821945 3,74 0,000 ROE 0,7808059 0,4114113 1,90 0,058 GDP -3,328564 3,577966 -0,93 0,352 INF -0,8714559 0,3351736 -2,60 0,009 CRE -0,1205175 0,0713157 -1,69 0,091 Constant 1,990378 0,5624984 3,54 0,000 Source: Calculated results from STATA 12.0 software The regression result in Table 4.10 shows that the authors' original expectations about the non-linear effects between equity-asset ratio (EQTA) and financial stability of commercial banks are perfectly reasonable. . It can be seen that the regression coefficients of EQTA and EQTA2 variables have a p-value of less than 5%. Therefore, these regression coefficients are statistically significant. At the same time, the regression coefficient of the EQTA2 variable is negative and the regression coefficient of the EQTA variable is positive, providing evidence that the effect of the equity-to-asset ratio (EQTA) on the Financial stability of commercial