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Model free Deep Hedging

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If you have a question about this talk, please contact Randolf Altmeyer .

Deep Hedging is a simple machine learning inspired algorithm, which produces risk management strategies, which is built upon a given market environment and a given preference structure. In this talk we introduce a novel algorithm inspired by Moritz Duembgen’s and Chris Rogers’ Bayesian approach, which can additionally deal with model uncertainty. We discuss a machine learning implementation of it, and provide a universality proof when it can be successful (joint work with Matteo Gambara and Thorsten Schmidt).

Join Zoom Meeting https://maths-cam-ac-uk.zoom.us/j/98775083754?pwd=aUhteExxNEgrWW5mMkd0TGw2SlhQUT09 Meeting ID: 987 7508 3754 Passcode: 837932

This talk is part of the CCIMI Seminars series.

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