**risk assessment**is the weak link on the credit risk assessment, the assessment of technical requirements are relatively high. In this paper, the the KMV model combined with the reality of China's

**listed companies**, the measure of the credit risk of listed companies in China. Can use the default database because there is not yet publicly traded company, the the KMV model output distance to default measure the credit risk of listed companies.

[Key words] KMV model listed company credit risk assessment

KMV model theoretical basis and methods of computation

KMV model to evaluate the credit risk of the Company's basic idea is: distance to default (DD), the expected market value of assets (V) from the default point (DP) of the distance, the greater the distance, the smaller the possibility of default occurs, whereas the more large. Distance to default (DD) to a multiple of the standard deviation of the market value of assets. Default point (DPT) is usually at a point between the nominal value of current liabilities and total liabilities. EDF measure is carried out in three steps: First, the estimated value of the assets and the assets of the company volatility: Then we calculated the distance to default DD (Distance-to-Default), it is the risk of default values ??expressed in index form, and finally use the distance to default t-test, draw the corresponding credit risk of listed companies live.

According to Merton and Black-Scholes option concept, the company's stock value can be expressed as:

the (1)

Where E is the enterprise's equity market value, V the nominal value of the corporate debt market for corporate assets value, D, r the risk-free rate, T is the debt repayment terms, N (d) is the standard normal cumulative distribution function 考v corporate assets value volatility, 考E value of corporate equity market volatility.

The value of the assets of the company V and asset value volatility 考v implicit variables two unknown variables, apparently can not be solved from the equation of option pricing model, which also need to use the volatility of the equity market value of the Company can be observed 考E unobservable to the relationship that exists between the value of the assets volatility 考v simultaneous solution. The 考E and assets of the company by the company stock returns standard deviation income standard deviation 考v relationship between type:

灰E, V is the value of the stock the flexibility of the company's assets, and dE / dV for the option value of Delta, that the derivative of both sides of the equation, then the expectation to the following formula:

Can be obtained by solving the simultaneous equations of 1.1 and 1.3, the value of the assets and the asset value volatility.

In the KMV model, DD is defined as the mean of the future market value of corporate assets from the distance between the point of default, the market value of the assets deviate from the standard deviation of the number of default point (DPT). Or, in other words, to achieve the default point value of the assets to be declining percentage multiples of the standard deviation is called distance to default. In practical applications, the KMV model DD is calculated as follows:

For example: A borrower enterprise asset value E (V) 500 million, the value of the assets volatility 考V 5% penalty points (or default execution price) $ 450 million. The distance from the point of default then the business is:

DD = (500-450) / (500 ℅ 5%) = 2 standard deviation

The economic implications of the Borrower default to appear only if the value of the assets within one year decreased by 2 standard deviation level (ie $ 100,000).

KMV model assessment of listed companies Empirical Analysis of credit risk

Firstly adjust the KMV model market value of equity method of calculating the flow of non-tradable shares at different prices to calculate, and then calculate the market value and volatility of assets of listed companies, and then calculate the distance to default of listed companies; final sample distance to default for the mean t-test to test the the KMV model on the overall credit risk of listed companies the ability to identify. There is not yet publicly traded company default database can use the default distance of the KMV model output only to measure the credit risk of listed companies, the ability of the test parameter adjustment model to identify the credit risk of listed companies in China, for the model in China credit risk evaluation of listed companies to make some preliminary discussion. The same time, considering the interference of sample comparability, the gap between industry and company size on the empirical results, we selected new pairs of non-ST and ST follow the following principles: 1 selected stocks try to cover most sectors of the Chinese stock market, able to the overall credit risk of the listed companies to make judgments; 2 ST companies from the same industry and non-ST companies of similar size, try to eliminate the size of the company results; 3.2007 last trading day of each month the data research to ensure adequate data to support the findings; selected stock are listed in the Mainland. This paper selects 24 stocks, they were taken from five sectors, according to the Commission by the real estate industry (8 stocks), manufacturing (four stocks), wholesale and retail trade (two stocks), energy production and supply industry (four stocks), other manufacturing (stocks). 24 stock of non-ST 12, ST's 12. Analysis of financial data and equity structure of listed companies and historical volatility to estimate the market value of shares of listed companies; calculation of the market value of listed companies is combined with the characteristics of China's securities market, to take the market value of outstanding shares of non-tradable shares were calculated method; nominal value of the company's debt to the nominal value of the total liabilities of the company's financial annual report; we assume that the distance to default calculation time for one year, risk-free interest rate is the People's Bank of China announced a one-year lump sum time deposit rate (4.14%) ; default point calculation for the company long-term liabilities plus short-term liabilities. Derived by the formula 1.1-1.4 Table 1, Table 2 of the selected listed companies related calculations are as follows:

Distance to default DD of listed companies using equation (5) is calculated. Use (5), we get 2007 sample of the results of the distance to default as follows:

The overall credit risk of listed companies the ability to identify the t-test, t-test, the mean of the distance to default of non-ST and ST, the results are as follows:

The test degrees of freedom V = 22, alpha = 0.05, corresponding to t = 1.717, statistic value falls refused to domain, so reject the null hypothesis, the 2005 to 2007 period, non-ST and ST breach of contract from the difference in the alpha = 0.05 level of significance is statistically significant, that is, non-ST's distance to default on the whole is greater than the ST, that ST's probability of default than non-ST, which also in line with the realities of the securities market. In addition, it can be drawn: the value of the assets of the company by the company's stock market value greater impact, and the volatility of the value of the assets of the company is slightly lower than the stock price volatility. KMV model is more appropriate in the overall measure of the credit risk of listed companies.

Third, the conclusion

With economic development, credit risk management techniques constant innovation and improvement, will also improve the credit risk assessment theory and technology. However, no matter what kind of risk management system and technology are not one size fits all. According to China's economic and social reality, we must establish or create credit risk management and assessment theory apply to Chinese characteristics, the only applicable tools and mechanisms in order to benefit from. China's credit risk management and assessment model gap with developed countries, to learn foreign advanced model to grasp the characteristics and trends of its development, to absorb and learn from, and applied to China's credit risk management and assessment of the actual, become China's commercial banks, and credit risk management is an inevitable trend of the listed companies.

References:

[1] Michel Crouhy, Dan Galai, Rorbt Mark. "A Comparative Analysis of Current Credit Risk Models" [J]. Journal of Banking & Financial, 2000 (24): 59 ~ 117

[2] Andreas Charitou, Lenos Trigeorgis. "Option-Based Prediction". University of Cyprus Working Paper.Social Science Research Network Electronic Paper Collection.2000

[3] Xiao Xia: An Empirical Study KMV model based on the credit risk of listed companies in China [J] Financial Economics, 2008

[4] Li Pan: KMV model in China's listed companies credit risk evaluation and applied research [D]

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