Pricing Of CDS With Counterpart Risk

2015 in China's bond market appeared a series of credit risk events, and even some state-owned enterprises have failed to survive. In the future, China's economic downward pressure will continue to increase, there may be more and more bonds default. Under this background, it is very important for our country's financial market to be able to carry on the effective credit risk management. Credit derivatives represented by credit default swap is the most effective tool to manage, transfer and spread risk.Credit default swap (CDS) is a kind of credit derivatives. In accordance with the provisions of the contract, the buyer shall have the right to receive compensation for the loss when the subject of the assets of the contract default, the buyer shall, in accordance with the provisions of the contract to the seller a one-time or periodic payment of the cost of a certain amount of CDS. In essence, CDS is a kind of credit derivatives, the buyer can reduce the possible loss according to their own risk appetite, the seller can be based on their own risk to gain income.In financial crisis, CDS in some extent accelerated the development crisis and spread, a series of credit event also in some extent reflects the CDS valuation system exist some defects, especially without taking into account the counterparty credit risk. This paper bases on the assumption of CDS seller might default to construct to a more accurate CDS valuation system.In October 2010, after a long period of preparation, National Association of Financial Market Institutional Investors (NAFMII) launched a Chinese version of CDS, said the credit risk mitigation tool (CRM). The invention of CRM filling the blank of credit derivatives, but CRM trading is not active and there are few transactions after 2011, the main reason is the lack of mature CRM pricing system. In this paper, the application of CDS pricing in traditional intensity model to calculate the fair pricing of CRM in our country, and through the method of Copula function to calculate the seller of CRM and the underlying asset default correlations, to obtain based on the seller's default risk pricing of CRM.Selection of the data:In this paper, the underlying assets of the excess rate of return will be used to calculate the default intensity. Then through stock return rate data, using non-parametric kernel estimation method, calculated various copula functions corresponding to the parameters and the maximum likelihood estimates, ultimately determine the obeying the distribution function of stock returns in the two kinds of Copula functions. Using Monte Carlo simulation to generate a sequence of distribution functions and stock return distribution function with parameters, calculating the probability of default is simulated, and then through the no arbitrage pricing theory to determine the CRM equilibrium pricing of counterparty risk.The first chapter of this paper is the introduction. It mainly introduces the CDS pricing model, and reviews the domestic and foreign scholars' research on CDS pricing model, considering the counterparty default risk of the CDS pricing model, and the application of Copula function in the study of the correlation of financial assets.The second chapter is the introduction part mainly introduces the types and history of credit derivatives, characteristics of the parties involved in credit derivatives. Then this part focuses on the analysis of a series of changes in the credit derivatives market in regulation and system design. At the end of this chapter introduces in detail the characteristics and current situation on China's credit risk mitigation tool.The third chapter and the fourth chapter are the theoretical foundation of the thesis. The third chapter mainly bases on the intensity model of non-counterparty risk, then calculates the equilibrium price of CDS by no arbitrage principle. The fourth chapter is divided into two parts, the first is the introduction of the theory of Copula function. The second part extends the previous chapter of the model, getting a more accurate and close to the actual CDS pricing model.The fifth chapter is the part of empirical research. The main purpose is based on CRMW data to find the equilibrium price of CRMW. The experimental results show that the results of using t-Copula function and Clayton Copula function to estimate are similar, so this paper uses this two kinds of Copula function to calculate. The results show that the CRMW of considering counterparty risk is lower than without considering this.The sixth chapter is the final conclusion of this paper, innovation and deficiencies and suggestions. Mainly through the introduction and analysis of the previous part, summarize the influence factors of CDS pricing. Then, the main innovation of this paper and the deficiencies, and pointed out the direction of future research can be improved. This paper summarizes the problems of CRM market in China and puts forward some suggestions for China's future development of credit derivatives marketThe main innovations of this thesis include:1. This paper uses non-parametric kernel density estimation method to get more accurate copula model, and firstly applied this method to CDS pricing, in order to get the more accurate pricing of CDS.2 This paper is the first study on pricing in CRM into account counterparty default risk, to get a more accurate standard CRM pricing.Of course, there are some deficiencies in this paper. Such as the pricing model did not consider the effects of macroeconomic factors and contract elements, such as interest rates, the macroscopic policy, the settlement mechanism, clearing mechanism. And this paper only considers the default possibility of seller, in fact, buyers of CDS protection also exists default possibility, and established on the basis of based on both the default possibility research will be able to more accurately in CDS pricing.