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

Nội dung text: Impact of equity, credit risk on financial stability of Vietnamese commercial banks

1. MINISTRY OF EDUCATION AND TRAINING THE STATE BANK OFVIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY MAI BINH DUONG IMPACT OF EQUITY, CREDIT RISK ON FINANCIAL STABILITY OF VIETNAMESE COMMERCIAL BANKS SUMMARY OF DOCTORAL THESIS Major: Finance - Banking Code: 62.34.02.01 Academic advisor: Assoc. Prof. Dr. Nguyen Ngoc Thach HO CHI MINH CITY - 2017
2. CHAPTER 1: INTRODUCTION 1.1. The urgency of the subject The commercial banks bring into play a very important role for each economy, contributing to attracting capital and providing loans. Business activities of commercial banks must always ensure stability, safety and profitability. Along with capital markets through the stock market, the money market through the banking system is the place to provide capital to the economy. With active mobilization of temporary idle funds in all organizations, individuals, all economic sectors (temporarily idle capital released from the production process, from the source of savings of the population ) through commercial credit, commercial banks have provided capital for the economy, fully meet the timely reproduction process. Thanks to the operation of the commercial banking system, especially the credit business, enterprises have the conditions to improve their business activities, contributing to improving the efficiency of the whole economy. Therefore, we can assert that the main subject to meet capital needs for business activities is commercial banks. In addition, commercial banks are tools to regulate the macro economy. In the operation of the market economy, the operation of commercial banks if effective will really become an effective tool for the State to regulate the macro economy. Through credit and payment activities between commercial banks in the system, commercial banks have contributed to expanding or reducing the amount of money in circulation. Moreover, by granting credits to the economy, commercial banks carry out the flow of money, gather and divide the capital of the market effectively. Thus, stabilization of the commercial banking system plays an important role in the financial system of Vietnam. Since the financial crisis of 2008-2009, many experts have been interested in studying financial instability that could lead to bankruptcy in many areas such as Altman (1968), Altman & GCG (1977) ), Zavgren (1985). Particularly in the banking sector there are researchs by Boyd & Graham (1986), De Nicolo (2000), Hesse & Cihak (2007), Soedarmono & ctg (2011), Rahman & ctg (2012), Fu & ctg
3. (2014), Chiaramonte & ctg (2015), Strobel (2015). These studies find the impact of many factors on the financial stability of commercial banks. However, an issue that is being debated is the impact of equity and credit risk on the financial stability of commercial banks. In theory, equity plays an important role for a bank. Equity funds not only finance the bank's investments but also help banks to be proactive in their business operations, increasing their competitive capacity and securing their credibility. In addition, the theory also shows that credit risk occurs will affect immediately earnings of commercial banks. Since then, affecting the business activities of commercial banks, creating instability. Some studies by Furlong and Keeley (1989), Keeley (1990), Van and Roy (2003), Jacob Oduor et al. (2017) show that equity helps reduce risk and increase stability. Finance of banks. On the other hand, empirical studies have also shown that the credit risks faced by banks with loans have led to the bank's loss of liquidity and forced banks to bankruptcy. This result is also supported by recent research by Bjửrn Imbierowicz and Christian Rauch (2013). In Vietnam, since the crisis of 2008-2009, the banking system of Vietnam has been gradually recovering due to its active efforts in dealing with bad debts of each bank in particular and the Government in general. Looking back at the instability of the Vietnamese banking system over time, equity and credit risk play an important role. Therefore, it can be said that, in the current context of Vietnam, the consideration of the impact of equity, credit risk on the financial stability of banks is necessary, especially in the mid-crisis period. by. Because determining the level and direction of the impact of equity, credit risk on the financial stability of banks will help to develop sound and sustainable banking governance policies. Starting from the above, the topic "Impact of equity, credit risk on financial stability of Vietnamese commercial banks" is necessary. 1.2. Gap in research Based on the results of the empirical study, which will be presented in the next, the research expects to fill some of the research gaps:
4. Firstly, based on prior research, research has focused on both the impact of equity and credit risk on the financial stability of commercial banks. However, the research goes in two different directions: the first one examines the effect of equity on the financial stability of commercial banks such as Jacob Oduor et al. (2017), Aggrawal et Jacques ( 2001); Rime (2001); Godlewski (2004); Hakenes and Schnabel (2010); Abba et al. (2013); Vu Thi Hong (2015); Le Thanh Ngoc et al. (2015) the second direction of studying the impact of credit risk on the financial stability of commercial banks Bjửrn Imbierowicz and Christian Rauch (2013); Beck & ctg (2009); Consuelo Silva Buston (2012). Domestic research studies to measure the impact of both equity and credit risk on the financial stability of Vietnamese commercial banks are limited. Second, the theories of research on the impact of equity on the financial stability of banks reveal many contradictions. In the first place, the theory is that increasing the equity will reduce profits, thereby reducing the financial stability of the bank. 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. Secondly, higher equity will allow banks to make better choices in their businesses while at the same time better controlling credit activity, thereby increasing bank financial stability (Jensen and Meckling, 1976). These theories show that the direction of the impact of equity on the bank's financial stability over time, and the likely impact of equity to The financial stability of Vietnamese commercial banks is non-linear and inverted U. This implies that increasing the equity ratio could help increase the financial stability of Vietnamese commercial banks but only to a certain extent. If the equity ratio exceeds this level, the increase in equity can reduce the financial stability of Vietnamese commercial banks due to the decrease in business performance. Equity ratio at the point of reversing the financial stability of Vietnamese commercial banks is the optimal ratio of equity, at which the financial stability of Vietnamese commercial banks is the
5. highest. . A study to prove this non-linear impact exists and find optimal equity thresholds that will increase the financial stability of Vietnamese commercial banks. Third, in the context of the global financial crisis that took place in 2008 and 2009, the economies of many countries were sharply reduced. In Vietnam, the world economic crisis has also been affecting a lot: on the stock market, foreign investors have the ability to recover capital and sell securities. Hence, it will negatively affect foreign exchange reserves and stock market prices. Exports will decline, which both affects the balance of international payments, trade deficit; It has also increased labor force loss, negative impact on the labor market; The real estate market will tend to stagnate and this market downturn will negatively affect other markets. Some banks have lost their liquidity and withdraw their credit, which makes it difficult for businesses to access the capital market; Increasing interest rates, increasing capital costs, thus affecting business operations (Dinh Son Hung, 2010). Empirical studies by Consuelo Silva Buston (2012); Jacob Oduor et al. (2017) found that, under the influence of the economic crisis, the impact of equity and credit risk on bank financial stability was altered. However, there are no studies in the country that compare the impact of equity and credit risk on the financial stability of Vietnamese commercial banks during and after the crisis. The global financial crisis took place between 2008 and 2009. These theories show that the direction of the impact of equity on the bank's financial stability over time, and the likely impact of equity to The financial stability of Vietnamese commercial banks is non-linear and inverted U. This implies that increasing the equity ratio could help increase the financial stability of Vietnamese commercial banks but only to a certain extent. If the equity ratio exceeds this level, the increase in equity can reduce the financial stability of Vietnamese commercial banks due to the decrease in business performance. Equity ratio at the point of reversing the financial stability of Vietnamese commercial banks is the optimal ratio of equity, at which the financial stability of Vietnamese commercial banks is the
6. highest. . A study to prove this non-linear impact exists and find optimal equity thresholds that will increase the financial stability of Vietnamese commercial banks. Third, in the context of the global financial crisis that took place in 2008 and 2009, the economies of many countries were sharply reduced. In Vietnam, the world economic crisis has also been affecting a lot: on the stock market, foreign investors have the ability to recover capital and sell securities. Hence, it will negatively affect foreign exchange reserves and stock market prices. Exports will decline, which both affects the balance of international payments, trade deficit; It has also increased labor force loss, negative impact on the labor market; The real estate market will tend to stagnate and this market downturn will negatively affect other markets. Some banks have lost their liquidity and withdraw their credit, which makes it difficult for businesses to access the capital market; Increasing interest rates, increasing capital costs, thus affecting business operations (Dinh Son Hung, 2010). Empirical studies by Consuelo Silva Buston (2012); Jacob Oduor et al. (2017) found that, under the influence of the economic crisis, the impact of equity and credit risk on bank financial stability was altered. However, there are no studies in the country that compare the impact of equity and credit risk on the financial stability of Vietnamese commercial banks during and after the crisis. The global financial crisis took place between 2008 and 2009. 1.3. Objectives of the study. The study has a general purpose of assessing the impact of equity, credit risk on the financial stability of Vietnamese commercial banks, based on the results of research to propose solutions, A proposal to increase the financial stability of Vietnamese commercial banks. In addition, with the expectation of filling the research gap in Vietnam, the study also conducted: (i) examine whether or not the existence of non- linear effects of equity on financial stability of The Vietnamese commercial bank and, if so, find the optimal equity threshold at which the level of financial stability of Vietnamese commercial banks is highest and (ii) compare the impact of the equity
7. capital ratio risk and credit risk to the financial stability of Vietnamese commercial banks during and after the global financial crisis in 2008-2009. To achieve the overall goal, the thesis focuses on addressing the following specific objectives: - Measuring the financial stability of Vietnamese commercial banks in the period of 2008 - 2016; - Studying the direction of the impact of equity capital, credit risk on the financial stability of Vietnamese commercial banks; - Measure and evaluate the impact of equity, credit risk on the financial stability of Vietnamese commercial banks; - Check whether or not the existence of non-linear impact of equity on the financial stability of Vietnamese commercial banks and, if so, find the optimal equity threshold at which the degree of financial stability Vietnam's commercial banks are the highest - Comparison of changes in the ratio of equity and credit risk to the financial stability of Vietnamese commercial banks during and after the global financial crisis in 2008-2009. . Based on the results of research and proposals on solutions and proposals to increase the financial stability of Vietnamese commercial banks. 1.4. Research question To achieve these objectives, the thesis responds to the following questions: - How was financial stability of commercial banks in Vietnam in the period 2008 - 2016? - What are the implications of equity, credit risk to the financial stability of Vietnamese commercial banks? - What is the impact of equity, credit risk on the financial stability of Vietnamese commercial banks?
8. - Is there a non-existent impact of equity on the financial stability of Vietnamese commercial banks? And if so, what is the optimal threshold of equity in which the level of financial stability of Vietnamese commercial banks is highest? - How is the impact of equity and credit risk on the financial stability of Vietnamese commercial banks during and after the global financial crisis in 2008-2009? - In order to increase the financial stability, what commercial banks in Vietnam should implement solutions and recommendations? 1.5. Object and scope of the research Research subjects: impact of equity, credit risk on financial stability of Vietnamese commercial banks. Scope of research: research conducted in 24 joint stock commercial banks in Vietnam. The study wanted to cover all of Vietnam's commercial banks. However, because the data used to calculate the variables in the research model was derived mainly from the audited financial statements, data collection is limited. The audited financial statements of commercial banks are mostly available only from 2008 onwards. Therefore, the author selected the study period from 2008 to 2016 with 24 commercial banks in Vietnam. Besides, due to the topic of reviewing the 2008-2009 financial crisis period, it is appropriate to select the period from 2008 to 2016 by considering the 2008-2009 crisis. 1.6. Data and research methods Research data Research using micro data of 24 commercial banks in Vietnam. Source of data: Data is collected from reliable sources such as: State Bank of Vietnam, General Statistics Office of Vietnam (GSO), Annual financial report of 24 commercial banks in Vietnam. Research Methods The author uses a quantitative method based on studies by Bjửrn Imbierowicz and Christian Rauch (2013), Jacob Oduor et al. (2017) to model the effects of equity,
9. credit risk to the financial stability of commercial banks in Vietnam using Stata software with Panel Data data. Estimation methods for table data such as Fixed Effects, Random Effects, Feasible General Least Square (FGLS) for engraving This phenomenon. In addition to the above estimation methods, the study also regression models using the SGMM method for table data. 1.7. Scientific contribution of the research topic ❖ Theoretically Research on the methodology of equity and credit risk and the financial stability of banks and analyze the impact of equity and credit risk on financial stability. The bank is linked to the context of the world financial crisis and its impact on the banking system in the country. ❖ Methodically First, the author assessed the effects of equity, credit risk on the financial stability of Vietnamese commercial banks by quantitative research method with the support of Stata 12.0 software. Use table data with Random Effects and Fixed Effects. Test Hausman to choose between Random Effects and Fixed Effects. The author uses the Feasible General Least Square (FGLS) method to overcome self-correlation or variance across entities if they exist. In addition, the estimation by the System General Method of Moments is also used to ensure that the results are reliable. Second, the study also opened the door for further research. The author's study uses the quantitative model of the impact of equity, credit risk on financial stability in Vietnamese commercial banks. Further studies may further expand this study in two directions by expanding the breadth or depth of the study. In terms of depth, further research could increase sample size in other countries and regions such as ASEAN, Asia, and use other quantitative measurement tools to test the impact of equity, credit risk on financial stability in commercial banks. In terms of breadth, further studies may examine the impact of other factors on the financial stability of
10. Vietnamese commercial banks such as liquidity risk, financial management, ratio capitalization, profit, ❖ Practical meaning Firstly, based on the study by Jacob Oduor et al. (2017), Bjửrn Imbierowicz and Christian Rauch (2013), , the study uses the econometric models that measure the magnitude of impact the combination of both equity and credit risk to the financial stability of Vietnamese commercial banks. Estimates show that the regression coefficients of equity variables and credit risk are statistically significant. This suggests that the increase in equity will increase the financial stability of Vietnamese commercial banks and the increased credit risk will reduce the financial stability of Vietnamese commercial banks. This is an empirical contribution supplemented by empirical research in the country that is very limited in research on this subject. Secondly, the results of the study are empirical evidence of the direction of the impact of equity on the financial stability of the bank over time, the results of the study examining the relationship between the two This variable shows that the impact of equity to asset ratio (EQTA) on the financial stability of Vietnamese commercial banks is non-linear and inverted U. This implies that the increase in the 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
11. 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.
12. 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
13. 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
14. 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
15. 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 Tựng & Bựi Thị Len (2015), Hoàng Cụng Gia Khỏnh & Trần Hựng Sơn (2015).
16. 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), Lờ Thanh Ngọc and partner (2015), Hoàng Cụng Gia Khỏnh and Trần Hựng Sơn (2015), Nguyễn Minh Hà & Nguyễn Bỏ 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 Bjửrn Imbierowicz and Christian Rauch (2014). CHAPTER 3: METHODOLOGY AND RESEARCH DATA 3.1. Research process Diagram 1: Research Process
17. 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: 푅 푖푡 + 푄 푖푡 푍푠 표 푒푖푡 = 훿푅 푖 푍푠 표 푒푖푡 is the Z-score measures the bank's financial volatility in year t 푅 푖푡 is the return on total assets of bank i in year t, calculated as the after-tax profit divided by total assets.
18. 푄 푖푡 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. 훿푅 푖 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: ln푍푠 표 푒푖,푡 = 훽0 + 훽1 푄 푖,푡 + 훽2 퐾푆 푍 푖,푡 + 훽3퐿 푖,푡 + 훽4푅 푖,푡 + 훽 푅 푖,푡 + 훽6 푃푖,푡 + 훽7 퐹푖,푡 + 휖푖 (1) ln푍푠 표 푒푖,푡 = 훽0 + 훽1 푄 푖,푡 + 훽2 퐾푆 푍 푖,푡 + 훽3퐿 푖,푡 + 훽4푅 푖,푡 + 2 훽 푅 푖,푡 + 훽6 푃푖,푡 + 훽7 퐹푖,푡 + 훽8 푄 푖,푡 + 휖푖 (2) ln푍푠 표 푒푖,푡 = 훽0 + 훽1 푄 푖,푡 + 훽2 퐾푆 푍 푖,푡 + 훽3퐿 푖,푡 + 훽4푅 푖,푡 + 훽 푅 푖,푡 + 훽6 푃푖,푡 + 훽7 퐹푖,푡 + 훽8퐾 푈 푖,푡 + 휖푖 (3) ln푍푠 표 푒푖,푡 = 훽0 + 훽1 퐾푆 푍 푖,푡 + 훽2퐿퐿푃푖,푡 + 훽3퐿 푖,푡 + 훽4 푅푖,푡 + 훽 푅 푖,푡 + 훽6 푃푖,푡 + 훽7 푃퐿푖,푡 + 훽8 퐹푖,푡 + 휖푖 (4) ln푍푠 표 푒푖,푡 = 훽0 + 훽1 퐾푆 푍 푖,푡 + 훽2퐿퐿푃푖,푡 + 훽3퐿 푖,푡 + 훽4 푅푖,푡 + 훽 푅 푖,푡 + 훽6 푃푖,푡 + 훽7 푃퐿푖,푡 + 훽8퐾 푈 + 훽9 퐹푖,푡 + 휖푖 (5) ln푍푠 표 푒푖,푡 = 훽0 + 훽1 퐾푆 푍 푖,푡 + 훽2퐿퐿푃푖,푡 + 훽3퐿 푖,푡 + 훽4 푅푖,푡 + 훽 푅 푖,푡 + 훽6 푃푖,푡 + 훽7 푃퐿푖,푡 + 훽8 푃퐿푖,푡 ì 퐾 푈 + 훽9 퐹푖,푡 + 휖푖 (6) Table 3.1. Synthesis of variables in the research model Expectations Variable name Symbol Measure about accents Dependent variable
19. 푙푛푍푠 표 푒푖푡 Financial lnZscorei,t 푅 푖푡 + 푄 푖푡 stability = ln ( ) 훿푅 푖 Independent variables Equity ratio of Equity EQTA + total assets Total assets NPL ratio of total Nonperforming loans NPLi,t - outstanding Total loans loans The size of the BANKSIZEi,t Logarithm (Total assets) - bank Ratio of total outstanding Total loans LTD - loans to total Total deposits deposits Provision for Loan loss provisions LLPi,t + credit losses Total loans Lending rate on Total loans LOANTAi,t +/- total assets Total assets Net profit on Net income ROE + total equity Equity The ratio of operating Operating expenses expenses to net CIR3.2 - Net operating income operating income
20. Credit growth Total loans − Total loans CRE t t−1 - Total loanst−1 Growth of GDP GDP − GDP GDP t t−1 + GDPt−1 Inflation rate CPI − CPI INF t t−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 Đỡnh 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:
21. - 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 Mean Standard Min Max observations error 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
22. ROE 216 0,0837954 0,0867394 - 0,2846455 0,08200214 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 zscore banksize llp loanta cir roe npl gdp inf zscore 1.0000 banksize -0.2458 1.0000 llp 0.0111 0.0716 1.0000 loanta 0.2662 0.2149 0.0317 1.0000 cir 0.1289 -0.0730 0.0354 -0.0320 1.0000 roe -0.0151 0.3066 -0.0035 0.1766 -0.2332 1.0000 npl -0.0624 -0.1044 -0.0120 0.0208 0.2057 -0.1553 1.0000 gdp -0.0687 0.1922 0.0838 0.0533 0.0073 -0.0362 -0.1839 1.0000 inf 0.0483 -0.3291 -0.0921 -0.1533 -0.0673 0.0822 -0.0185 -0.2286 1.0000 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
23. CRE 1,29 0,777268 LTD 1,12 0,890348 LOANTA 1,08 0.923829 LLP 1,02 0.984787 VIF Trung bỡnh 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
24. 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 Coefficients (b) (B) (b-B) sqrt(diag(V_b-V_B)) fe1 . Difference S.E. SIZE -.1533421 -.0582665 -.0950756 .0914387 EQTA 2.784412 2.394527 .3898853 .433441 LTD .3598966 .359359 .0005377 .0713883 ROE -1.001225 -1.037827 .0366015 .2440212 GDP 5.068301 2.212541 2.85576 2.257929 INF -1.323078 -.9815084 -.3415694 .3590954 CRE -1.072158 -.761137 -.3110206 .2800944 b = consistent under Ho and Ha; obtained from xtreg B = inconsistent under Ha, efficient under Ho; obtained from xtreg Test: Ho: difference in coefficients not systematic chi2(7) = (b-B)'[(V_b-V_B)^(-1)](b-B) = 3.75 Prob>chi2 = 0.8086 Source: Calculated results from STATA 12.0 software Table 4.7. Modified Wald test results
25. Breusch and Pagan Lagrangian multiplier test for random effects lnz[id,t] = Xb + u[id] + e[id,t] Estimated results: Var sd = sqrt(Var) lnz .220037 .469081 e .0515631 .2270751 u .06949 .2636096 Test: Var(u) = 0 chibar2(01) = 261.37 Prob > chibar2 = 0.0000 Source: Calculated results from STATA 12.0 software Table 4.8. Wooldridge test results Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 23) = 14.875 Prob > F = 0.0008 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
26. 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
27. 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 banks is non-linear and inverted U shape. So the H2 hypothesis is true. Next, the author examines the effects of the financial crisis on the financial stability of commercial banks through model estimation (3). Estimated results are presented in the following table: Table 4.11. Estimation of model (3) by Feasible General Least Square – FGLS Zscore Coefficient Standard error t P>t BANKSIZE 0,030254 0,0251462 1,20 0,229 EQTA 4,072566 0,8997567 4,53 0,000 EQTA2 -2,497539 1,560521 -1,60 0,109 LTD 0,3348959 0,0817167 4,10 0,000 ROE 0,9120701 0,4097033 2,23 0,026
28. GDP -8,03854 4,047036 -1,99 0,047 INF -0,6649901 0,3399631 -1,96 0,050 CRE -0,0693354 0,0743565 -0,93 0,351 KHUNGHOANG -0,1537518 0,0619094 -2,48 0,013 Constant 2,461848 0,5896103 4,18 0,000 Source: Calculated results from STATA 12.0 software The results in Table 4.11 shows that the regression coefficient of KHUNGHOANG variable is -0,1537518 which is statistically significant at 5% and negative. This result is consistent with the original author's expectation of the author. This suggests that the crisis will increase the volatility of commercial banks. Thus, the H4 hypothesis is true. Table 4.12. Estimation of model (3) by Feasible General Least Square – FGLS Zscore Coefficient Standard error t P>t BANKSIZE 0,0425786 0,0247657 1,72 0,086 EQTA 4,568761 0,8960716 5,10 0,000 EQTA2 -1,729014 1,611795 -1,07 0,283 LTD 0,3538981 0,0820256 4,31 0,000 ROE 0,7877247 0,4069262 1,94 0,053 GDP -6,752806 3,775256 -1,79 0,074 INF -0,6729156 0,3367356 -2,00 0,046 CRE -0,0646742 0,0740766 -0,87 0,383
29. KHUNGHOANGx -1,13509 0,4127006 -2,75 0,006 EQTA Constant 2,090462 0,5578487 3,75 0,000 Source: Calculated results from STATA 12.0 software The results in Table 4.12 show that the regression coefficient of KHUNGHOANGxEQTA variable is -1,13509 which is statistically significant at 5% and negative. This result shows that in the context of the crisis, the increase in the ratio of equity to total assets will increase the volatility of commercial banks. 4.3.2. Results of the study on the impact of credit risk on the financial stability of Vietnamese commercial banks Using the STATA software with 216 observation balance panel data (n = 216), the time period from 2008 to 2016 for 24 banks was presented in Chapter 3. The model estimation results ( 4) in terms of two fixed effects methods (FE) and the general feasible least squares estimation method (FGLS) are shown as follows: Table 4.13. Estimation of the model (4) by fixed effects LnZscore Coefficient Standard error t P>t BANKSIZE -.1650859 .0418999 -3.94 0.000 LLP -.0134528 .2016315 -0.07 0.947 LOANTA -.1356525 .2044858 -0.66 0.508 CIR -1.13897 .3998413 -2.85 0.005 ROE .4476776 .3110988 1.44 0.152 GDP -5.012935 3.86494 -1.30 0.196 NPL -4.148806 1.874085 -2.21 0.028 INF -1.110172 .3311887 -3.35 0.001 Constant 7.561158 .6834501 11.06 0.000 Source: Calculated results from STATA 12.0 software
30. Variance testing varies with the entities performed through the modified Wald test. The results are shown in the following table: Table. xtt e4.14.st3 Modified Wald test results Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i . xttest3 chi2 (24) = 316.38 PMrobd>icfhiie2d =W a l d t 0e.s0t0 0f0or groupwise heteroskedasticity in fixed effect regression model Source: Calculated results from STATA 12.0 software .H 0xt:s esriigamla (lin)z^ 2b an=k ssiizgem al^l2p floran taal l ciir roe gdp npl inf Wooldridge test is used to test self-correlation in table data. The results are shown Wooldridge test for autocorrelation in panel data inc thehi2 following (24) =table: 316.38 H0: no first-order autocorrelation Prob>chi2 = 0.0000 Table F (4.15. 1, Wooldridge 23) = test results 36.0 85 Prob > F = 0.0000 . xtserial lnz banksize llp loanta cir roe gdp npl inf Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 23) = 36.085 Prob > F = 0.0000 Source: Calculated results from STATA 12.0 software Thus, the model (4) is estimated by the fixed-effect method with variable variance and self-correlation. To overcome this phenomenon, the author proceeds to recalculate the model (4) using the Feasible General Least Square (FGLS) method. Estimated results are as follows: Table 4.16. Estimation of model (4) by Feasible General Least Square – FGLS LnZscore Coefficient Standard error t P>t BANKSIZE -.1032217 .0308784 -3.34 0.001 LLP -.0112449 .0867974 -0.13 0.897 LOANTA .2536402 .1874519 1.35 0.176
31. CIR .1321644 .2470444 0.53 0.593 ROE .9313156 .3104374 3.00 0.003 GDP -7.680243 2.605883 -2.95 0.003 NPL -4.836314 1.295788 -3.73 0.000 INF -.2859408 .2125008 -1.35 0.178 Constant 5.253815 .5874777 8.94 0.000 Source: Calculated results from STATA 12.0 software Based on Table 4.16, the results of model estimation (4) using the Feasible General Least Square (FGLS) model show the regression coefficients of four variables: BANKSIZE, ROE, NPL, Gross Domestic Product (GDP), have a statistically significant impact on the financial stability of Banks in the research sample at the 5% significance level. The regression coefficients of BANKSIZE, ROE, NPL, GDP as estimated by FGLS are in line with the expectation of the sign. Estimated results show that the regression coefficient of the NPL variable is -4.84 which is statistically significant and negative. This shows that when the ratio of NPLs to total loans increases, it will reduce the Z ratio, which means that the increase in credit risk will reduce the financial stability of commercial banks. Thus, the H3 hypothesis is true. Table 4.17. Model estimation results (4) by GMM method LnZscore Coefficient Standard error t P>t LnZscore(-1) .0545457 .0492743 1.11 0.279 BANKSIZE -.1224771 .0577995 -2.12 0.045 LLP -2.21697 1.343885 -1.65 0.112 LOANTA .7041662 .3784957 1.86 0.075 CIR 3.016098 1.281217 2.35 0.027 ROE 4.289359 1.124326 3.82 0.001
32. GDP -7.096544 3.237069 -2.19 0.038 NPL -3.666684 1.97384 -1.86 0.076 INF -1.064525 .2524065 -4.22 0.000 Hansen test (p- 0.190 value) Sargan test (p- 0.852 value) AR(1) (p- 0.020 value) AR(2) (p- 0.830 value) Source: Calculated results from STATA 12.0 software As a result, the model estimation (1) shows that when the ratio of non-performing loans increased, there would be a negative impact on the financial stability of commercial banks in the sample. The above results show that the estimates obtained from different methods are convergent. The author continues to examine the effects of the financial crisis on the financial stability of commercial banks through model estimation (5). Estimated results are presented in the following table: Table 4.18. Model estimation results (5) by GMM method LnZscore Coefficient Standard error t P>t LnZscore(-1) .0514644 .0492398 1.05 0.306 BANKSIZE -.1710579 .0595984 -2.87 0.008 LLP -1.58318 1.555328 -1.02 0.319 LOANTA .2201793 .3954531 0.56 0.583 CIR 2.209164 1.16478 1.90 0.070 ROE 3.803015 1.012018 3.76 0.001
33. GDP -2.24637 3.745266 -0.60 0.554 NPL -3.758318 1.865278 -2.01 0.055 INF -1.538221 .3362277 -4.57 0.000 KHUNGHOANG -.1458208 .0578329 -2.52 0.019 Hansen test (p- 0.178 value) Sargan test (p- 0.890 value) AR(1) (p-value) 0.097 AR(2) (p-value) 0.763 Source: Calculated results from STATA 12.0 software The results in Table 4.18 show that the regression coefficient of KHUNGHOANG variable is -0.15 which is statistically significant at 5% and negative. This result is consistent with the original author's expectation of the author. This suggests that the crisis will increase the volatility of commercial banks. Thus, the H4 hypothesis is true. In addition, the author examines the specific impact of NPLs on total outstanding loans on the financial stability of commercial banks in the context of crisis by adding NPLxKHUNGHOANG variables and models. Estimated results are presented in the following table: Table 4.19. Model estimation results (6) by GMM method LnZscore Coefficient Standard error t P>t LnZscore(-1) .0316622 .0520772 0.61 0.549 BANKSIZE -.183283 .0622716 -2.94 0.007 LLP -1.640796 1.616858 -1.01 0.320 LOANTA .1144544 .4075005 0.28 0.781
34. CIR 2.712727 1.065427 2.55 0.018 ROE 4.325074 .9431445 4.59 0.000 GDP -2.584333 3.81374 -0.68 0.504 NPL -4.899792 1.832611 -2.67 0.013 INF -1.88019 .418922 -4.49 0.000 NPLxKHUNGHOANG -10.47738 3.764156 -2.78 0.010 Hansen test (p-value) 0.253 Sargan test (p-value) 0. 927 AR(1) (p-value) 0.078 AR(2) (p-value) 0.732 Source: Calculated results from STATA 12.0 software The results in Table 4.19 show that the six variables proposed in the model affect the financial instability of Vietnamese commercial banks: bank size (BANKSIZE), net profit on total equity (ROE), NPL ratio, NPL ratio, Inflation Rate (INF); The impact of credit risk on financial stability during crisis (NPLxKHUNGHOANG). There are 3 variables: LLP, LOANTA, GDP growth rate is not statistically significant. The results in Table 4.19 also show that the regression coefficient of NPLxKHUNGHOANG variable is -10.48 statistically significant at 5% and negative. This result shows that in the context of the crisis, the increase of NPL ratio on total outstanding loans will reduce the financial stability of commercial banks. At the same time, the absolute value of the regression coefficient corresponding to the NPLxKHUNGHOANG variable is 10.48 higher than the absolute value of the regression coefficient corresponding to the NPL variable of 4.9. Thus, the H5 hypothesis is true. 4.3.3. Summary of the study on impact of equity, credit risk on financial stability of Vietnamese commercial banks
35. The results of the thesis on the impact of equity, credit risk on the financial stability of Vietnamese commercial banks conclude that: Firstly, the results of empirical research show that as the ratio of equity to total assets increases positively, it will increase the financial stability of Vietnamese commercial banks. The main reason is that equity is one of the inputs to the bank's operation, and higher equity will help banks to make better choices in their operations. Better control of credit activity, thereby generating a profit, increasing the financial stability of the bank. In addition, higher capital creates stronger motivation for banks to track their clients and there is an interaction between bank capital and borrowing. High equity is a buffer against the risk of bankruptcy by improving the bank's ability to absorb risk. Higher-capitalization banks are more likely to absorb risk and increase risk tolerance than banks with lower equity, risk tolerance of banks In turn, it will help increase the financial stability of banks. Secondly, the increase in the equity ratio of total assets can help increase the financial stability of Vietnamese commercial banks but only to a certain percentage. If the ratio of equity to total assets exceeds this level, the increase in equity can reduce the financial stability of commercial banks due to reduced business performance. The ratio of equity to total assets at the point of reversing the financial stability of the major commercial banks is the optimal ratio of equity to total assets, at which the financial stability of Commercial banks are the highest. A quantitative change requires qualitative, qualitative change, where the owner's equity is too great, expanding asset investments, facilities, and business operations that can make the cost. The increase in the level of management, human resources and technological level did not keep pace with the development of the scale, causing the bank's risk to increase, thus reducing the financial stability of the banking system. Secondly, banks with large equity will have moral hazard problems, which may lead to moral hazard. Banks are said to be "too big to fail" because of the large amount of equity that tends to take on more risk in their business that will cause more instability.
36. Thirdly, in the special circumstance of crisis, the increase in the ratio of equity to total assets will increase the instability of Vietnamese commercial banks. The economic crisis is a slowdown in economic activity that has severely disrupted economic activity due to the decline in the aggregate demand of the economy as a whole. Banking is a service industry, in times of crisis, capital markets and money markets, as well as the ability of customers to repay high risk. In the case of goods and services, the demand has fallen, the market for product consumption has been decreasing, the cost of production has increased, especially for exporters because this is the most sensitive sector for fluctuations. In the world market, pushing businesses to high risk of default, banks are unable to recover debt. Investors and hedge funds tend to be more cautious in investing decisions when the market is struggling and has a strong impact on investors' sentiment. Strong depreciation and reduced liquidity quickly. In the real estate market, when the economy is in difficulty due to the impact of the crisis, forcing people to reduce spending, the real estate market freezes, real estate prices fall, real estate companies fall into difficulties, If you do not sell your product, you will be charged a higher interest rate. The value of collaterals at commercial banks decreased as banks' assets declined and bad debts increased, making the investment bank's capital structure in a disadvantageous situation. So, in a time of crisis, the profitability of many banks fell, even some small banks may suffer losses; bad debt rises. The impact of the crisis on the financial stability of the banking system in Vietnam has been reduced as banks continue to increase their capital and expand their investment scale. CHAPTER 5: CONCLUSIONS AND SOLUTIONS TO ENHANCE THE FINANCIAL STABILITY OF THE VIETNAM COMMERCIAL BANK 5.1. Conclusions In addition to presenting theoretical background, the author also conducts research on domestic and foreign studies related to the assessment of the impact of equity on total assets, the ratio of bad debt to total outstanding loans to financial stability of commercial banks. The study model is based on the results of previous studies.
37. Based on the results of previous studies, the authors used the panel data when conducting the study. In setting up a model for assessing the impact of bad debt to the financial stability of commercial banks, the authors use fixed effects, random effects, Feasible General Least Square (FGLS), and the SGMM estimation method for modeling with Panel data. The empirical results show that as the ratio of equity to total assets increases, the Zscore increases, thus increasing the financial stability of commercial banks. In addition, the impact of equity to total assets on the financial stability of Vietnamese commercial banks is nonlinear and inverted U. On the other hand, when the ratio of bad debt to total outstanding loans increases, it will reduce the Z ratio, ie reduce the financial stability of commercial banks. In addition, the results of the research models also show the impact of the financial crisis on the financial stability of Vietnamese commercial banks. Even in the context of the financial crisis, the increase of bad debt on total outstanding loans will lead to instability of Vietnamese commercial banks. In addition, the results of the study also show the size of the bank, the ratio of operating expenses to net operating income, net return on total equity, GDP growth rate, The ratio of loans to total assets affects the financial stability of commercial banks in the sample. 5.2. Solutions to improve the financial stability of Vietnamese commercial banks 5.2.1. Solutions to increase the equity of commercial banks 5.2.2. Solutions to manage credit risk at commercial banks 5.2.3. Other solutions to enhance the financial stability of commercial banks 5.3. Recommendation to the State Bank of Vietnam, the Government ❖ For the State Bank of Vietnam ❖ For the government: stabilizing macroeconomic policies and banking risk management laws 5.4. Limitations and research direction
38. The structure and operation of the financial system, as well as its interaction with the complex economy, economic models and research, are difficult to understand. Therefore, the author argues that the examination of the impact of equity, credit risk on the financial stability of commercial banks should be regarded as a continuous process, must be improved and develop non-stop, should not be interrupted at any time. Although the research goal has been achieved, the authors find that this research is still limited and needs to be improved in the future. Firstly, although the sample was conducted with most commercial banks in Vietnam, foreign bank branches, 100% foreign owned commercial banks, policy banks, or other commercial banks did not. research subjects. Since each scale and type of bank has different characteristics in terms of competition, human resources, and governance, the impact of credit risk on stability may not be the same. Thus, the study only test a part of the banking system in Vietnam should be generalized not high. Further research can be done on a broader scale, with more banks for greater overall results. Secondly, the thesis only focuses on the empirical study of the impact of equity, credit risk on the financial stability of commercial banks taken from financial reports published annually from 2008 to 2016. Further studies need to improve the data collection process, thereby improving both the quality and quantity of data. Evaluating the impact of economic variables is a process that requires a lot of data, including macro data for both the economy and the individual data of each bank. Long time series will make it easier for the operator to determine the scenario, the short numbers are often not very fluctuating and therefore difficult to visualize the effects. For data on bank operations, the more detailed the data, the more accurate the simulations will be, and the more accurate the results will be.