Modern Computational Finance
Modern Computational Finance: AAD and Parallel Simulations, published with Wiley, is out November 13, 2018 (ebook) and November 20 (hardcover) on Amazon, Apple Books and many other places including your favorite book store.
It covers the principles, professional implementation and interaction of three of the key technologies powering modern derivatives systems: parallel computing, Monte-Carlo simulations and automatic adjoint differentiation (AAD), a powerful algorithm that computes thousands of differentials with outstanding speed and accuracy. It is the combination of these technologies, among others, that earned Danske Bank the In-House System of the Year 2015 Risk award.
“It would not be much of an exaggeration to say that Antoine Savine’s book ranks as the 21st century peer to Merton’s ‘Continuous-Time Finance’:
It makes modern computational techniques such as multi-threaded parallel AAD as accessible to finance professionals as Merton’s introduction of stochastic calculus into finance. A first in a three book series authored by Danske Bank’s powerhouse quant team makes intricate concepts inherent to production-quality implementation of AAD easy to understand and follow through.
No other quant finance focused book has gone so deeply into parallel C++ and AAD with such clarity, level of detail and thoroughness. I can hardly wait for the remaining two volumes to see what else the wizards of AAD have up their sleeves.”
Vladimir V. Piterbarg,
Head of Quantitative Analytics and Development at NatWest Markets,
Co-author of the three-volume set “Interest Rate Modeling”
“A passion to instruct
A knack for clarity
An obsession with detail
A luminous writer
An instant classic.”
Head of Quantitative Research, Bloomberg L.P.
A public preview including Leif Andersen’s preface is freely available on SSRN and ResearchGate. A number of excerpts are also freely available on Wiley’s page, including a self-contained section explaining quasi-random Monte-Carlo simulations and Sobol.
The book comes with complete, professional C++ code for generic, parallel Monte-Carlo simulations and AAD. The code is freely available on GitHub. It is advised to watch the repo and follow the author on GitHub to be notified of updates and fixes.
The GitHub repo also contains lecture slides with a more gentle introduction to AAD in Machine Learning and Finance. See Lectures by Antoine Savine.
Please leave your own reviews, along questions, comments and suggestions at the bottom of this page, or on the book’s page on GoodReads.
Exercises and assignments
Exercises and assignments are being produced and will be posted separately. In the meantime, interested readers will find below the final hand-in for the computational finance lecture of autumn 2018 at Copenhagen University, where the book is used as curriculum: