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Modern Computational Finance
book

Modern Computational Finance

by Antoine Savine, Leif Andersen
November 2018
Intermediate to advanced content levelIntermediate to advanced
592 pages
15h 36m
English
Wiley
Content preview from Modern Computational Finance

Conclusion

After an introduction to parallel computing, and the construction of a parallel simulation library, we explored in detail the theory and implementation of AAD. As a result, we could compute accurate market and model risk sensitivities over parallel simulations in fractions of a second.

We don't believe that such results could be achieved with a free or commercial AAD library applied as a black box over instrumented code. This kind of speed is only obtained with an intimate understanding of AAD and its implementation, combined with a deep expertise in the differentiated algorithms. Selective instrumentation, a clever path-wise back-propagation, and a systematic application of check-pointing are the key ingredients, along with an efficient AAD library, boosted with expression templates, and an efficient instrumented simulation code. That is why we covered both AAD and financial simulations in this publication. We also provided computationally efficient C++ code, one that is not meant to be used as a black box, but instead provides a flexible interface for expert users to accommodate many types of designs and applications. (Readers who made it to the conclusion are, by definition, expert users.)

While AAD over parallel simulations is central to effective, modern derivatives systems, it is not by itself sufficient for the efficient calculation and differentiation of complex derivatives books and xVA adjustments.

Other key technologies are at play there. In particular, ...

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Publisher Resources

ISBN: 9781119539452Purchase book