Adjoint credit risk management
Adjoint algorithmic differentiation is one of the principal innovations in risk management in recent times. Luca Capriotti and Jacky Lee show how this technique can be used to compute real-time risk for credit products, even those valued with fast semi-analytical methods, like credit default swaps, indexes and swaptions
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The aftermath of the recent financial crisis has seen a dramatic shift in the credit derivatives markets, with a conspicuous reduction in demand for complex, capital-intensive products, such as bespoke collateralised debt obligations (CDOs), and a renewed focus on simpler and more liquid derivatives, like credit default indexes and swaptions (Curien 2006; Pengelly 2010).
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