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Research Our Country Commercial Banks’non-performing Loan Ratio Influencing Factors

Posted on:2016-12-07Degree:MasterType:Thesis
Country:ChinaCandidate:R LiuFull Text:PDF
GTID:2309330467974995Subject:Finance
Abstract/Summary:PDF Full Text Request
Non-performing loans not only affect the safety, stability and profitability of bank’s operation, and sometimes even become the fuse of the financial crisis. After years of reforming and innovation, non-performing loan ratio has dropped dramatically. Non-performing loan problem seems to be saved, but there are still many hidden troubles, and since the third quarter of2011non-performing loans and non-performing loan ratio has presented from the "double down" to "double up" trend. So researching the influencing factors of the country’s commercial bank non-performing loans and making practical and feasible management strategies becomes the urgent task of China’s banking industry, and it is also of great significance to the development of China’s banking sector and financial markets.In this paper, first of all, define the concept of Chinese non-performing loans and non-performing loan ratio, and introduce the classification of non-performing loans in two stages:"a stay more than two" and "the five classification" phase, and the latter is our country’s mainly method of classification. Second summary the theoretical basis of non-performing loans including financial fragility theory, theory of credit, loan customer relationship theory. Then analyze the current situation of commercial banks’ non-performing loans and non-performing loan ratio and revealing the problems of our country commercial banks’ non-performing loans by analyzing the cause of the "double down" to the "double up" development tendency, the structure of the non-performing loan ratio distribution, organization distribution characteristics, industry distribution characteristics and forms of non-performing loans.Then the article analyzes the influencing factors of our country commercial banks’ non-performing loans from the theoretical and empirical perspective. According to the above of the non-performing loans theoretical basis and previous researching results. This article summaries three aspects including macro environment, banks and loan enterprise doing theoretical analysis, embarking from the credit activity participation roles. The macro environment factors consists of macro economy, financial market development degree and government regulation; Bank factors including bank profitability and risk control; Loan enterprise factors are divided into enterprise’s operating and risk controlling.Choose six representative variables from the three aspects:the GDP growth rate, the broad money supplying growth rate, commercial banks’ asset-liability ratio, total loans of commercial banks, commercial banks’relative scale, total industries’climate index, and the non-performing loan ratio, a total of seven variables to make the cointegration test and to build the VAR model to carry on the empirical analysis. The innovation points in this paper are as follows:most previous papers research the influencing factors of bad loans only from macro economic aspect, the data selecting only form a commercial bank,and mostly use the theory analysis and linear regression model, but this paper have selected the CBRC website statistics of the entire banking industry and use VAR model analyzing the influencing factors’dynamic measurement comprehensively.Researching results show that in the longer term, the growth rate of DGP, broad money supplying growth, commercial banks’asset-liability ratio and commercial banks’ relative size appears to have negative relationship with non-performing loan ratio. The contribution of the asset-liability ratio to the non-performing loans is small, the contribution of the growth rate of DGP and broad money supplying growth to the non-performing loan ratio is larger, and the contribution rate of the commercial banks’relative size to non-performing loans is the biggest. Commercial banks’ total and industries’total climate index appears to have positive relationship with the non-performing loan ratio. The contribution rate of total loans to commercial banks’non-performing loans is small. But in the short term, an impact of the GDP growth rate and the broad money supplying growth rate could has a positive impact on the non-performing loan ratio, and a shock of total loans has a negative effect on bad loans. Reason is that when taking the loosing monetary policy, some enterprises will expand investment blindly, which increasing the demand for bank loans, the investment behaviors lack rational expectations and perfect planning, causing loss of investment funds, so that the non-performing loan ratio increases. Non-performing loans in total new loans in the short term will not appear, so the increase of total loans would dilute the original non-performing loan ratio at first leading to the banks’ non-performing loan ratio decreasing, and in the short term the impacts of total loans and total industries’ climate index on the non-performing loan ratio is larger.After theoretical analysis and empirical analysis of the influencing factors of bad loans, the end of the article proposes targeted measures to guard against and dissolve the bad loans from the aspects of national macros environment policy, management of commercial bank itself and the loan enterprise. Preventive measures are:learning the operation of the overall economic situation, formulating perfect laws and regulations about non-performing loans, improving the social credit system, changing the property mechanism of state-owned banks, improving the bank’s own management systems and internal control systems, redistricting bank credit risk, establishing modern enterprise legal systems, etc. Resolving measures are:setting up asset management companies, banks and companies actively taking measures such as the bank creditor’s rights "shift" equity", selling non-performing packaging assets, etc.
Keywords/Search Tags:Non-performing Loan, macro factors, the VAR model, managementstrategy
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