Credit derivatives: the past, the present and the future
The determinants of credit spread returns
What’s driving the default swap basis?
What is the value of modified restructuring?
The debt and equity linkage and the valuation of credit derivatives
Nth to default swaps and notes: all about default correlation
Portfolio credit risk models
Credit derivatives as an efficient way of transitioning to optimal portfolios
Overview of the CDO market
Synthetic securitisation and structured portfolio credit derivatives
Integrating credit derivatives and securitisation technology: the collateralised synthetic obligation
Considerations for dynamic and static, cash and synthetic collateralised debt obligations
CDOs of CDOs: art eating itself?
Valuation and risk analysis of synthetic collateralised debt obligations: a copula function approach
Extreme events and multi-name credit derivatives
Reduced-form models: curve construction and the pricing of credit swaps, options and hybrids
Modelling and hedging of default risk
ISDA’s role in the credit derivatives marketplace
Credit linked notes
Using guarantees and credit derivatives to reduce credit risk capital requirements under the New Basel Capital Accord
In the analysis of credit risk, it is often assumed that a default event is triggered when firm assets fall to a sufficiently low level relative to the notional of outstanding debt. In this line of thinking, models of credit risk naturally involve joint assumptions of the stochastic evolution of the individual components of the firm capital structure – ie, assets, debt, and equity. Such an approach is clearly “deep” in the sense that the analysis aims not only to quantify the credit risk itself, but also to understand the causal factors behind it.
The description of credit risk through an analysis of balance sheet information and other fundamental factors is the domain of the so-called structural models. While such models have their uses (see Chapters 5, 7, 14 and 15), it is often more practical to work at a higher level of abstraction and simply treat credit events as point processes with parameters that can be inferred from observations. This approach is known as reduced-form modelling. While reduced-form models are, in a sense, less fundamental than structural models, they offer the financial engineer large advantages in terms of implementation, analytic