IAQF Innovation Award 2026

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IAQF Innovation Award 2026
Differential Machine Learning at Bloomberg
Differential Machine Learning at Bloomberg
I will be delivering the keynote at Bloomberg’s Quant Seminar in NYC next week, June 22th 2022, 17:00. The event can be followed in person or virtually. Registration is free but mandatory. Here is the registration link: https://go.bloomberg.com/attend/invite/bloombergquant-bbq-seminar-june2022/ In this event hosted by Bruno Dupire at Bloomberg’s headquarters, I will present advances in…
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Risk podcast : Differential Machine Learning
Risk podcast : Differential Machine Learning
Co-author Brian Huge and I were interviewed by Risk Magazine last week and got a chance to present differential ML and related algorithms in non-technical terms. The podcast is publicly available https://www.risk.net/cutting-edge/views/7880346/podcast-huge-and-savine-on-turbo-charging-derivatives-pricing Podcast: Huge and Savine on turbo-charging derivatives pricing
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Axes that matter: PCA with a difference, Risk, 2021
Axes that matter: PCA with a difference, Risk, 2021
Brian Huge and Antoine Savine, Risk, October 2021
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Dimension Reduction Done Right
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’
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Differential Regression
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
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Differential Dimension Reduction from Antoine Savine on Vimeo.
Brian Huge and Antoine Savine of Fuperfly Analytics at Danske Bank extend differential machine learning (ML) to unsupervised models and design a new breed of principal component analysis (PCA) to correctly reduce dimension for risk management of financial Derivatives. Applications include the specification and calibration of pricing models, the automatic identification of regression features, and the preprocessing of simulated datasets for (differential) machine learning.
Dimension Reduction from Antoine Savine on Vimeo.
General considerations about dimension reduction in finance and machine learning
PCA.mp4 from Antoine Savine on Vimeo.
Differential PCA is introduced with a brief recall of classic PCA and why it is inadequate for risk management
DiffReg from Antoine Savine on Vimeo.
Modern Computational Finance: Parts I and II free on SSRN for a limited time
Modern Computational Finance: Parts I and II free on SSRN for a limited time
Free on SSRN for a limited time: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3735414
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…
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Differential Machine Learning in Production -- 5min Lightning Talk from Antoine Savine on Vimeo.
Differential Machine Learning: Live production demo for Bloomberg's BBQ Seminar Novermber 18, 2020
Complimentary Preview: Modern Computational Finance Volume 2
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.
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Differential Machine Learning (Risk, 2020) — Live Production Demo We have just presented our latest Risk paper Differential Machine Learning at QuantMinds International 2020. The presentation includes a live demo of how differential ML is implemented in production, and combined with cash-flow scripting to provide truly general means of learning the pricing and risk function of arbitrary financial instruments. See the 5min demonstration below:
Differential ML in Risk.net
Differential ML in Risk.net
Danske quants discover speedier way to crunch XVAs by Mauro Cesa, October 2020
See https://www.linkedin.com/feed/update/urn:li:activity:6718791331742937088/
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Differential Machine Learning, Risk, 2020
Differential Machine Learning, Risk, 2020
Brian Huge and Antoine Savine, Risk, October 2020
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Differential Machine Learning: 5min video overview Differential ML tutorial on YouTube In this lightning talk delivered for Bloomberg's BBQ seminar 28th May 2020, we expose the main ideas of differential machine learning and application to derivatives pricing and risk management. Complete presentation slides here: