QuantAD® is an Automatic Differentiation tool targeted at Quantitative Finance and industries with similar requirements. It offers a robust and efficient alternative to finite difference (“bumping”) for computing sensitivities. With minor changes to the existing program in C++ or C#, the user is able to AD-enable the whole code base and automatically compute a large number of sensitivities with dramatic performance speedups compared to the traditional bumping approach. QuantAD has been designed from the ground up to cope with large code bases found in Quantitative libraries using numerical methods such as Monte-Carlo, Finite Difference, and Lattice-Based Schemes.
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