An Empirical Research On Extreme Credit Risk In The Financial Market

With the globalization and integration of financial markets, relation between countries is becoming increasingly close. Because of the proliferation of financial innovation, increasing the scale of derivative transactions, it ultimately leads risks to complexity and diversity. It needs this level of risks management of countries to a higher point. Finance is the core of a nation’s economy, various financial institutions are financial fundamentals. One country’s financial institutions will face a lot of risks, but in a wide variety of risks, financial markets of every nation take the credit risks to the most serious challenges. So people began to focus on credit risk management and avoiding, make ourselves can prepare prevention and risk aversion before risks coming.But since the late 20th century, the global financial crisis occurred many times. These crises give investors and risk managers serious challenges. It had begun to consider the presence and measure with extreme credit risk. But today’s measurement results of credit risk models are just average period of credit risk or credit risk at a particular point in value, most of these values are the use of risk distribution information drawn from the central region, ignores the situation of extreme credit risk occurrence. So this paper uses KMV credit risk measurement model and quantile regression model to measure the extreme credit risk.Firstly, this article summarized the various credit risk measurement models and compared their advantages and disadvantages as well as the applicability of China’s national conditions, draw KMV credit risk measurement model is more suitable for China’s national conditions. Later this paper used the GARCH model to correct KMV model, and with the results of conventional KMV model were analyzed. And finally with the results corrected KMV model to be quantile point, quantile regression analysis in blue chip stocks and ST shares, to compare the volatility of the situation, observed extreme risks were significantly different or not.Quantile point analysis show, both blue chip stocks or ST shares, risk of 0.95 quantile point, extreme risk higher than 0.5 quantile point. And in the same quantile point, two types of stocks in the risk of financial crisis are higher than the non-financial crisis period. In the same quantile point, the risk is higher in the ST shares than blue chip stocks.Quantile regression analysis show, either 0.5,0.7 or 0.95 quantile regression, both blue chip stocks or ST shares, volatility in the financial crisis are greater than the non-financial crisis period, with closer to 0.95 quantile regression, in other words, closer to the extreme risk, volatility will be more intense. No matter in which period or which quantile point, volatility is always greater in the ST shares than blue chip stocks.The purpose of this paper is to allow risk managers or investors doing risk analysis, investment forecasts, taking into account the difference between blue chip stocks and ST shares and their own characteristics, can not confuse the characteristic between blue chip stocks and ST shares. And in the course of the analysis to fully consider the case of the financial crisis period and extreme credit risk, investors and risk managers will prepare to deal with measures and make ready the program.