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).
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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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