#computational finance

Dimension Reduction Done Right -- presenting the upcoming (October 2021) Risk article: 'Axes that matter: PCA with a difference'

Differential Machine Learning: regression and PCA Presenting the upcoming (October 2021) Risk article ‘Axes that matter: PCA with a difference’

Differential regression illustrates the main ideas of differential machine learning, and demonstrates its power in a very simple context. We posted a small article with code on Google Colab, run it here: https://colab.research.google.com/github/differential-machine-learning/notebooks/blob/master/DifferentialRegression.ipynb

Modern Computational Finance Volume 2: Scripting for Derivatives and xVA by Jesper Andreasen and Antoine Savine -- free preview now available

read the draft now

See download link at the bottom of this page and leave your suggestions and comments on the linkedIn group Machine Learning in Quantitative Finance (you may need to request membership).

We count on the suggestions and comments left by advanced readers in the linkedIn thread to quickly complete this work with the quality expected from the Modern Computational Finance series.

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’. We will be presenting our vision of modern risk management systems and the ‘One Analytics’ platform: full front to…

By Brian Huge and Antoine Savine

Deep learning derivatives pricing, and risk, with differential regularisation

See our slides here:

http://www.deep-analytics.org

Deep learning derivatives pricing

I made two simplistic TensorFlow (1.x) notebooks for the benefit of my students at Copenhagen University, to demonstrate how vanilla neural nets (deeply) learn pricing of European calls and high dimensional basket options, together with a comparison with conventional polynomial regression models (a laLSM) and a quick, simple introduction to the implementation of deep learning models in TensorFlow.

Recorded workshop from Kings College London: AAD, Backpropagation and Machine Learning in Finance

Back in March, I gave a series of lectures at Kings College London on automatic adjoint differentiation, backpropagation and machine learning, and how it all connects and applies to risk management of financial derivatives.

The lectures were recorded and made freely available online, either from Kings own page:

https://nms.kcl.ac.uk/probability/workshopPages.php?id=8

or, on YouTube:

[yout…