Deep hedging: learning to remove the drift

Removing arbitrage opportunities from simulated data used for training makes deep hedging more robust

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Hans Buehler, Phillip Murray, Mikko S. Pakkanen and Ben Wood present a machine learning approach for finding minimal equivalent martingale measures for market simulators of tradable instruments, eg, for a spot price and options written on the same underlying. They extend their results to markets with frictions, where they find ‘near martingale measures’ under which the prices of hedging instruments are martingales within their bid-ask spread

A long-standing

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