End of the bumping grind?

In quest for processing power, banks are choosing 'unnatural' calculus over fancy chips

duncan-wood

If you were trying to dramatically speed up risk and sensitivity calculations – a process that traditionally involves thousands of repetitive sums, with the inputs being changed marginally, or ‘bumped' each time – the output of a single calculation may not seem the most promising place to start. In the slightly odd world of adjoint algorithmic differentiation (AAD), though, it is the key to running calculations tens, hundreds or even thousands of times faster than the most popular rival methods

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Calibrating interest rate curves for a new era

Dmitry Pugachevsky, director of research at Quantifi, explores why building an accurate and robust interest rate curve has considerable implications for a broad range of financial operations – from setting benchmark rates to managing risk – and hinges on…

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