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.

RiskMinds 2019

Flying Monday to Amsterdam with my colleagues from Superfly Analytics of Danske Bank, including Brian Huge and Ove Scavenius, to attend the RiskMinds 2019 risk management conference and the award ceremony, where our group is nominated for ‘Excellence in risk management and modeling’.

EDIT: Superfly Analytics now won the award:

Excellence in Risk Management and Modelling, winner: Superfly Analytics at Danske Bank

We will be presenting our vision of modern risk management systems and the ‘One Analytics’ platform: full front to back consistency with scripting of cash-flows , model hierarchies and AAD. Further, we will present ‘Deep Analytics’: leveraging risk management systems with AI to learn revaluation and risk analytics on the fly. For those unable to attend, we posted our slides online here:

click on the picture to see the presentation