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Research On Credit Default Risk Of Bank Of Nanjing

Posted on:2021-04-06Degree:MasterType:Thesis
Country:ChinaCandidate:Y S WangFull Text:PDF
GTID:2439330620471399Subject:Financial
Abstract/Summary:PDF Full Text Request
According to the latest data from the National Bureau of Statistics,China 's GDP in 2019 exceeded 99 trillion yuan,and the added value of the financial industry was 7.70777 trillion yuan,an increase of 7.2% over the previous year and accounting for 7.8% of GDP.The financial industry has become an important part of the national economy and has developed rapidly in serving the real economy.In China's current financial system,commercial banks occupy a central position.Urban commercial banks have developed rapidly in recent years and have become an increasingly important part of the banking system and even the financial system.As a special enterprise with operational risks,commercial banks often carry out their business with risks.Among them,credit risk refers to the risk that the counterparty of the transaction fails to perform its related obligations in accordance with the agreed terms,and the commercial bank will suffer losses.Among the several types of risks,it is the most common risk faced by the daily operation of commercial banks,and has become the face of commercial banks in China The most important financial risk.Since China's securities market is not yet mature,China's enterprises have relatively single financing channels,relying on banks' indirect financing methods,and commercial bank assets mainly exist in the form of loans.When the SME operation has a capital chain problem,more indirect financing methods of commercial banks are used,and city commercial banks serve the local economy and local SMEs and residents,so the credit risk they face is greatly increased.Domestic and foreign scholars have experienced the development process from qualitative to quantitative research on the credit risk of commercial banks.After the financial crisis in 2008,quantitative research on the credit risk of commercial banks has become the focus of commercial banks.Bank of Nanjing is an urban commercial bank established and listed earlier in China and has a good credit risk management system.As of the end of 2018,Bank of Nanjing had opened 191 sub-branches in 17 cities including Nanjing,Taizhou,Shanghai,Wuxi,and Beijing,with assets of RMB 1,234.269 billion,10,721 employees,and operating outlets covering Beijing,Shanghai,Hangzhou and Jiangsu provinces.As the "leader" of China's urban commercial banks,although Nanjing Bank has a better credit risk management system,there is still much room for growth in the quantitative analysis of credit risk.Based on the analysis of the credit risk analysis of commercial banks by domestic and foreign scholars,combined with the current unique national conditions in China and the analysis and research of Bank of Nanjing,this paper revises the KMV model to carry out financial and stock data of Bank of Nanjing.Quantitative Study.Since 2008,the international financial situation has changed significantly.China 's stock market has also developed in recent years.The stock price has also fluctuated greatly.At the same time,China 's policies have also undergone more adjustments.Bank of Nanjing has been listed since 2007.This article uses the financial data and stock data of Bank of Nanjing to the end of 2018.The time span is large,covering the bull and bear markets in China's stock market.It can find the essential factors and reasons from the data for many years,and has a certain reference value for the research on the credit risk of the same type of city commercial banks at this stage.This article mainly uses excel formula calculation and Matlab to perform model data operation,and obtains the default distance DD and theoretical expected default probability EDF of Bank of Nanjing.This article also analyzes the main influencing factors of Nanjing Bank's credit risk,and puts forward corresponding suggestions for its management.
Keywords/Search Tags:credit risk, city commercial bank, KMV
PDF Full Text Request
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