Differential Machine Learning (Risk, 2020) — Live Production Demo

Machine Learning

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:

Published by Antoine Savine

Antoine Savine is a French mathematician, academic and a leading derivatives research professional with Danske Bank in Copenhagen. Antoine also teaches Volatility and Computational Finance at Copenhagen University. He is the author of Modern Computational Finance with John Wiley and Sons. Antoine holds a PhD in Mathematics, and is best known for his work on volatility and interest rate models. He was influential in the development of cashflow scripting, the application of generalized derivatives to volatility, and the wide adoption of AAD in financial systems.

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