Cutting edge introduction: Adjoints - maintaining the legacy
The adjoint method for calculating sensitivities may be quick and cheap, but it requires a top-to-toe overhaul of pricing code. A new technique developed by quants at UBS allows it to be deployed with minimal coding changes. Nazneen Sherif introduces this month’s technical articles
Adjoint algorithmic differentiation (AAD) has been gathering momentum over the past two years, with an increasing number of banks ditching more traditional ways to speed up the calculation of risk sensitivities – such as graphics processing units (GPUs) – for the cheaper and more tractable mathematical technique.
Members of the AAD club already include Banca IMI, Barclays, Credit Suisse, Danske Bank, Natixis and Nomura, and more are exploring its potential (Risk January 2015).
It is, of course
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