We investigate the performance of the Deep Hedging framework under training paths beyond the (finite dimensional …) Markovian setup. In particular, we analyse the hedging performance of the original architecture under rough volatility models in … capable of capturing the non-Markoviantity of time-series. We also analyse the hedging behaviour in these models in terms of …

hedging in markets for futures and higher-order derivatives. We supplement the vast statistical analysis of volatility …

This study proposes a structured product (SP) for hedging defined contribution pension fund members against capital …

applied to the conventional deep hedging training algorithm so as to enable obtaining a price through a single training run … for the two neural networks associated with the respective long and short hedging strategies. The accuracy of the neural …

This paper proposes a model-free approach to hedging and pricing in the presence of market imperfections such as market … incompleteness and frictions. The generality of this framework allows us to conduct an in-depth theoretical analysis of hedging … strategies with a wide family of risk measures and pricing rules, and study the conditions under which the hedging problem admits …

on modeling of defaultable markets, pricing and hedging of defaultable claims and results on the probability of default …

The possibility to use hedging strategies is an often neglected aspect in the literature on prediction/betting markets … paper, we derive the key mathematical results in using hedging strategies through taking opposite positions to an initial … probability of the outcomes. We also discuss two sources of inefficiency that can arise when using hedging strategies in practice …