We  extend the scope of the vol-of-vol expansion given in 27%DIFDELCMD < ] %%% from finite dimensional stochastic volatility models to infinite dimensional (rough) forward variance modelsand provide newexplicit representations of the  push-down Malliavin weights that simplifies the computations and provides new insights into their structure. This will validate the Bergomi-Guyon expansion for a large class of forward variance models .
We introduce an asymptotic small noise expansion, a so called vol-of-vol expansion, for potentially infinite dimensional and rough stochastic volatility models. Thereby we extend the scope of %DIFDELCMD < ] %%% existing results for finite dimensional models and validate claims for infinite dimensional models. Furthermore we provide new, explicit (in the sense of non-recursive) representations of the so-called push-down Malliavin weights that utilizes a precise understanding of the terms of this expansion .
A
introduce an asymptotic small noise expansion, a so called vol-of-vol expansion, for potentially infinite dimensional and rough stochastic volatility models. Thereby we
D
the vol-of-vol expansion given in
D
27
R
from finite dimensional stochastic volatility models to infinite dimensional (rough) forward variance modelsand provide newexplicit
existing results for finite dimensional models and validate claims for infinite dimensional models. Furthermore we provide new, explicit (in the sense of non-recursive)
A
so-called
R
simplifies the computations and provides new insights into their structure. This will validate the Bergomi-Guyon expansion for a large class of forward variance models
utilizes a precise understanding of the terms of this expansion