Research On Calculation Of Commercial Bank’s Credit Risk Based On Kmv Model

Credit risk is one of the major risks faced by our country’s commercial banks. For most commercial banks, the loan is the most important resource of credit risk. In fact, credit risk exists in all banking activities, which include bank account, trading account, off-balance Sheet activities and on-balance sheet items. Banking is facing credit risk contained in other financial instruments except loans. The financial instruments embrace acceptance, trader’s transaction, trade finance, foreign exchange trading, financial futures, swaps, bonds, equity, option, undertaking, guarantee, settlement of trading, etc. As the main kind of risks in commercial bank activities, credit risk directly influences the various aspects of economic life in modern society, also a country’s macro economic policy-making, and the stability and coordinated development of global economy at large. As the carrier of credit risk, the credit management of commercial bank is directly related to the operation of commercial bank.As one of the Basel Committee, China must comply and implement the New Basle Accord, and should act according to international practice. It’s a necessity to join the international financial market and take part in the international finance competition. China’s large commercial banks will begin to implement Basel2at the end of2010. With the New Basel Accord gradually putting into effect, credit risk management, important component of bank management, will be the top priority in the capital management of China’s banking industry.This paper takes the calculation of commercial bank’s credit risk based on KMV model as the research direction. On the basis of analyzing KMV model’s basic theory, theoretical framework and measuring stages, this paper discusses the calculation of credit risk via KMV Model and its applicability in China. The writer makes the empirical analysis about the actual measurement effect of KMV model based of listed ST companies and non-ST companies. It carries out comparative analysis on the probability of default. Furthermore, joint probability of default is researched based on Copula function and KMV model. In the end of the thesis, the writer points out the improving measure on the KMV model calculation and the application prospect in the future in China. The main contributions of the research work are discussed in this thesis in detail and are summarized as follows:First, the paper analyzes KMV model’s basic theory, theoretical framework and measuring stages in detail. Asset value and asset volatility are solved by using dichotomy, a new iteration algorithm.Second, the KMV model with Copula functions is proposed. Several Copula functions are combined with KMV model to discuss joint credit risk of commercial banks against the weakness of KMV model. Euclidean distances between Copula function and empirical Copula function would be compared to pick up the optimal modle.Third, the research on calculation of KMV model to distinguished listed ST companies and non-ST companies are discussed, and the results indicate KMV model is effective in measurement of credit risk of listed companies in China. By using data of listed companies in China, joint probability density is simulated by choosing appropriate Copula model. The modified optimal KMV model can be generated by comparing the Euclidean distances between Copula function and empirica Copula function. This calculation research provides the investors a method to choose the appropriate portofolio with low credit risk and a reference to prevent credict risk to ensure the safty of funds and maximize the returns.