the model assumptions). In this context, we use relative entropy as a pre-metric in order to quantify these two sources of …

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 …

This paper explores the use of neural networks to reduce the computational cost of pricing and hedging variable annuity … the tasks of pricing as well as hedging four different varieties of variable annuity guarantees. We demonstrated a …

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

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 …

We show that the recent results on the Fundamental Theorem of Asset Pricing and the super-hedging theorem in the … context of model uncertainty can be extended to the case in which the options available for static hedging (hedging options … be equivalent to no-arbitrage under the additional assumption that hedging options with non-zero spread are non …