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
An nth to default swap is a credit default swap (CDS) that references a basket of underlying credits, typically three to five names. The protection seller under the swap is exposed to the default of the reference credit that defaults “nth” (first, second, third …). An nth to default note is a creditlinked note (CLN) that embeds this type of default swap in its terms. The purchaser of the note is the seller of credit protection in the embedded default swap. In this chapter, we delve into nth to default swaps and notes, define their characteristics and compare their risks with other derivative and funded instruments.
More than other financial instruments, nth to default swaps and notes are plays on default correlation. Simply put, default correlation measures whether credit-risky assets are more likely to default together or separately. For example, default correlation answers the following question: does a 10% probability of default mean that one out of 10 credits is going to default, or that, 10% of the time, all 10 credits are going to default? If the answer is “in between”, where in between?
Default correlation is essential to understanding the risk of nth to default swaps and