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Partner Since
2+ YearsPublisher | John Wiley & Sons Inc |
ISBN 13 | 9781119539452 |
ISBN 10 | 1119539455 |
Book Description | Arguably The Strongest Addition To Numerical Finance Of The Past Decade, Algorithmic Adjoint Differentiation (AAD) Is The Technology Implemented In Modern Financial Software To Produce Thousands Of Accurate Risk Sensitivities, Within Seconds, On Light Hardware. AAD Recently Became A Centerpiece Of Modern Financial Systems And A Key Skill For All Quantitative Analysts, Developers, Risk Professionals Or Anyone Involved With Derivatives. It Is Increasingly Taught In Masters And PhD Programs In Finance. Danske Bank Wide Scale Implementation Of AAD In Its Production And Regulatory Systems Won The In-House System Of The Year 2015 Risk Award. The Modern Computational Finance Books, Written By Three Of The Very People Who Designed Danske Bank Systems, Offer A Unique Insight Into The Modern Implementation Of Financial Models. The Volumes Combine Financial Modeling, Mathematics And Programming To Resolve Real Life Financial Problems And Produce Effective Derivatives Software. This Volume Is A Complete, Self-Contained Learning Reference For AAD, And Its Application In Finance. AAD Is Explained In Deep Detail Throughout Chapters That Gently Lead Readers From The Theoretical Foundations To The Most Delicate Areas Of An Efficient Implementation, Such As Memory Management, Parallel Implementation And Acceleration With Expression Templates. The Book Comes With Professional Source Code In C++, Including An Efficient, Up To Date Implementation Of AAD And A Generic Parallel Simulation Library. Modern C++, High Performance Parallel Programming And Interfacing C++ With Excel Are Also Covered. The Book Builds The Code Step-By-Step, While The Code Illustrates The Concepts And Notions Developed In The Book. From The Author∷ The Companion Code Is Freely Available On Github./Asavine And Readers May Want To Watch This Repository To Be Notified Of All Upcoming Updates. The Code Is Fully Explained And Commented In The Book.A Preview Is Available On Papers.Ssrn/Sol3/Papers.Cfm?Abstract_id=3281877, Including Leif Andersen Preface.AAD Was Named One Of The Greatest Algorithms Of The 20th Century. It Powers Machine Learning, Financial Risk Management And Many Other Scientific Applications. It Makes A Major Difference For Financial Software, Allowing To Compute Complex Risks In Minutes On A Laptop Instead Of Overnight In Data Centers. AAD Is Also Notoriously Mind-Twisting, And This Key Technology Is Still Misunderstood By A Majority Of Finance Professionals. I Wrote This Book To Explain This Technology Step By Step, Guide Readers Towards A Complete, Up To Date Implementation, And Use It To Accelerate A Generic Parallel Simulation Library (Which We Build In The First Parts). This Publication Is The Sum Of My Many Years Teaching AAD And Implementing It Professionally. My Colleagues In Danske Bank And I Implemented AAD In Production In The Early 2010s And Were Rewarded With Risk In-House System Of The Year 2015 Award. This Book Builds On Our Adventure And Provides All The Explanations And Guidance For A Practical, Effective Implementation In Words, Mathematics And Code. |
Language | English |
Author | Antoine Savine |
Publication Date | 2018 |
Modern Computational Finance Hardcover English by Antoine Savine - 2018