Modern Computational Finance: Parts I and II free on SSRN for a limited time

SSRN link now expired — download parts I and II here for a limited time:

part III to follow

parts i and ii free for a limited time on SSRN

The first two parts (out of three) of my book Modern Computational Finance (Wiley, 2018) are complimentarily available on SSRN only in December 2020.

Part I teaches necessary C++ foundations with a focus on parallel computing. Part II summarizes the theory of financial Derivatives and develops serial and parallel Monte-Carlo pricing and risk management engines.

Part III, not included in this preview, discusses and develops the critical adjoint differentiation (AD) technology, its professional implementation in C++ and its deployment in risk management platforms.

In recent years, AD revolutionized the field of quantitative finance. It brought us real-time risk reports and instantaneous calibration. It also enabled extremely promising new directions of research. For instance, the Risk article Differential Machine Learning by Brian Huge and I (also available on arXiv and SSRN) leverages pathwise gradients computed with AD to train a novel breed of deep learning models to effectively approximate pricing and risk functions of arbitrary financial products.

I implemented AD in production at Danske Bank with my colleagues of the Quantitative Research department. I also teach AD at Copenhagen University in the context of my graduate course on Computational Finance and Machine Learning in Finance. My book gives an exhaustive and pedagogical account of AD, its implementation in C++ and its deployment for the risk management of financial Derivatives.

Parts I and II are necessary pre-requisites to make the most of the critical part III.

Follow me on SlideShare

https://www.slideshare.net/AntoineSavine/presentations

For those of you who like my posts and stories, I am working on a few nice talks and workshops on introductory automatic differentiation, deep learning, Monte-Carlo simulations and parallel programming that will land on my SlideShare page soon. Please follow me to be notified of updates.

Right now, my page has my volatility lecture notes from Copenhagen University, my interest rate modeling slides from a course internal to Danske Bank, an introduction to multi-curve and collateral consistent discounting, some material on AAD and scripting, and a personal favorite about risk smoothing and fuzzy logic.

Comments, suggestions and questions are welcome, of course.

Fuzzy Logic
Danske Bank
Smoothing a barrier
6
• Spread notional across barriers in (B-e/2,B+e/2)
• Example: 1y 110-120 RKO...

Modern Computational Finance book pages

Please post your questions, suggestions, comments or reviews of the book Modern Computational Finance: AAD and Parallel Simulations on the author’s page:

https://antoinesavine.com/books-by-antoine-savine

or the book’s GoodReads page:

http://www.goodreads.com/book/show/40244920-modern-computational-finance

A public preview, including Leif Andersen’s preface, is available on SSRN:

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=3281877