The asset combination of the multi-target credit derivatives and the pricing model of credit risk, the dependence in credit default in credit derivatives is an important connection factor. Copula functions represent a methodology which has recently become the most significant new tool to handle in a flexible way the comovement between markets, risk factors and other relevant variables studied in finance. Besides, Copula functions have been applied to the solution of the need to reach effective diversification has led to new investment products, bound to exploit the credit risk features of the assets. It is particularly for the evaluation of these new products, such as securitized assets (asset-backed securities, such as CDO and the like) and basked credit derivatives (nth to default options) that the need to account for comovement among non-normally distributed variabes has become an unavoidable task. This article attempts utilizes the credit yield spread between the non-risk bond and the common corporation bond in the market and using Copula functions to make up the relation composition of asset combination. Then, penetrates through the Monte-Carlo Simulation to estimated the default time of asset combination and princing the credit risk spread in the tranche of the Collateralized Debt Obligation (CDO). Besides, this article aims at the asset default recovery rate, the discount rate and the correlation coefficient of asset combination and so on three factors makes the sensitivity analysis, we find that the most effect of the credit default spread in the Collateralized Debt Obligation is asset default recovery rate, next is the correlation coefficient of asset combination, the influence of discount rate is not obvious.

Under the current regulatory regime for insurance undertakings, Solvency I, the required capital margin does not depend on the allocation of investments, i.e. it is not sensitive to market risk arising from the volatility of market prices for e.g. equity, bond or real estate investments. To improve the protection of policyholders and create a unified regulatory regime in all countries of the European Economic Area (EEA), a risk-sensitive, forward-looking and principle-based regulatory accord for insurance undertakings called Solvency II will replace the current regime by 01.01.2016. Unlike Solvency I, Solvency II requires the backing up of any investment in risky assets with risk capital rather than imposing investment limits. Own funds eligible to cover the solvency capital requirements under Solvency II shall be based on the difference of market-consistently valuated assets and liabilities in the Solvency II balance sheet. In this thesis, I first summarize academic contributions as well as opinions from industry representatives on the expected consequences of the current calibration of the Solvency II standard formula. The accuracy of the calibration itself is another focal point of this work. This work contains four scientific papers. The first paper examines the presence of contagion effects between Eurozone countries in the period 2008-2012. In a market-consistent valuation approach like Solvency II contagion effects intensify the volatility of own funds and therefore of the solvency ratio of insurers. The intensity of contagion peaked in 2010 and first half of 2011 but decreased subsequently which is likely to be a consequence of bailout measures by the EU and the IMF and ECB interventions. The second and third paper address the zero risk charge for sovereign debt issued by EU member states assumed under the Solvency II standard formula. If one accepts German bond yields to be a risk-free asset, using modern cointegration techniques I showed that bonds of only one third of EU member countries can be perceived as risk-free as well. The fourth paper provides evidence for convergence in the shock-response-behavior of the stock indices of Germany, UK and France during the past decades, which in turn indicates support for the assumption of a perfect tail correlation between listed equity in the Solvency II standard formula.

本文建立了當違約機率及回收率為隨機變動，同時信用等級移動有記憶性，且回收率和無風險利率期間結構相關之信用風險價差期間結構模型。並評價信用價差選擇權及有對手違約風險普通選擇權之價值。 此模型產生的信用價差有更多的變化性，將可描述：信用價差的隨機波動行為，且即使信用等級沒變，價差仍可能發生改變；信用價差與無風險利率期間結構有相關性；公司特定或證券特定的價差及其變動行為；處於等級上升或下降趨勢公司債券之殖利率曲線，能更準確配適有風險債券的價格等實際現象。 並可應用至有對手違約風險之商品及多種信用衍生性商品等的評價與避險，且可進行風險管理方面的應用。 關鍵詞：信用風險；信用風險價差；馬可夫模型；信用衍生性商品 / In this thesis we develop a credit migration model with memory for the term structure of credit risk spreads. Our model incorporates stochastic default probability, stochastic recovery rate, and the correlation between the recovery rate and the term structure of risk-free interest rates. We derive valuation formulae for a credit spread option and a plain vanilla option with counterparty risk. This model provides greater variability in credit spreads, and it has properties in line with what have been observed in practice: (1) credit spreads show diffusion-like behavior even though the credit rating of the firm has not changed; (2) the model injects correlation between spreads and the term structure of interest rates; (3) the model enables firm-specific and security-specific variability of spreads to be accommodated; and (4) the model enables us to estimate the yield curves corresponding to the positive and negative trends of credit ratings and match the observed risky bond prices more precisely. This model is useful for pricing and hedging OTC derivatives with counterparty risk, for pricing and hedging credit derivatives, and for risk management. Key Words: Credit Risk, Credit Risk Spread, Markov Model, Credit Derivative.