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Random neural networks for rough volatility
The reservoir approach allows us to formulate the optimisation problem as a simple least-square regression for which we prove theoretical convergence properties.
Large and moderate deviations for importance sampling in the Heston model
We provide a detailed importance sampling analysis for variance reduction in stochastic volatility models.
Deep Hedging under Rough Volatility
We investigate the performance of the Deep Hedging framework under training paths beyond the (finite dimensional) Markovian setup.
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