FINCAD: Algorithmic differentiation: Shattering the myths
Lately I’ve noticed some inaccurate ideas regarding Algorithmic Differentiation (AD) floating around in the press. And so, I feel obliged to set the record straight.
For those unfamiliar with AD, it is a mathematical technique that helps firms with derivatives on their books rapidly solve complex pricing and analytics problems. In fact, firms utilizing AD typically experience staggering improvements in speed and accuracy when compared to traditional risk methods such as “bumping.”
One
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