Credit Risk Modeling And Valuation: An Review

Credit risk is the distribution of financial losses due to unexpected changes in the credit quality of a counterparty in a financial agreement. There are many classic credit risk management methods, including experts assessment, credit rating, loan class. In recent years, CreditMetrics, CreditRisk+, CreditPortfolioView and KMV come forth. Although they can identify , measure, and manage credit risk , and what's more they reflect risk concentration, they can not compare with market risk models due to the limit of data availability.Generally speaking, domestic researchers are introducing credit risk management from the view of commercial bank's risk management. We argue that issuing corporate bond and gaining loans from the financial intermediate are two important ways from the view of corporate asset structure and finance. In our country, investors are boring with equity finance. So we have to develop our corporate bond market. This paper give an review on credit risk modeling and valuation. We hope it can be useful to present commercial bank's credit risk management creation and our development of corporate bond market.In this paper, we review the structural, reduced form and incomplete information approaches to estimating joint default probabilities and prices of credit sensitive securities. The ultimate characteristic of structural approach is that it uses corporate's special financial information as the input variable, and considers corporate liabilities as contingent claims on the assets of a firm. Structural approach argue that the value of corporate won't jump. If the value of corporate fall below of its liability, then default occurs. So the market value of the firm is the fundamental source of uncertainty driving credit risk.The reduced form approach is not based on a model definition of default. It assumes that default occurs without warning at an exogenous default rate, or intensity. The dynamics of the intensity are specified under the pricing probability. Instead of asking why the firm defaults, the intensity model is calibrated from market prices.The incomplete information framework provides a common perspective on the structural and reduced form approaches to analyzing credit. Instead of focusing on the default intensity and making assumptions about its dynamics, incomplete information models seek to specify the trend based on a model definition of default. We use this trend to estimate default probabilities and price credit sensitive securities. The incomplete information models share many of the good properties of both structural and reduced form models while avoiding their difficulties.