#### Conference abstracts

Session A7 - Stochastic Computation

July 12, 15:30 ~ 15:55 - Room B2

## On the approximation of pathdependent BSDEs driven by the Brownian motion

### Department of Mathematics and Statistics, University of Jyväskylä, Finland, Finland   -   stefan.geiss@jyu.fi

In this talk we present recent results about the $L_p$-approximation of the $Y$-process of path-dependent quadratic and sub-quadratic backwards stochastic differential equations driven by the Brownian motion of the form $Y_t = \xi + \int_t^T f(s,Y_s,Z_s) ds - \int_t^T Z_s dB_s.$ In this approximation we use adapted time-nets where the adaptation is based on certain quantitative properties of the initial data $(\xi,f)$ (the terminal condition and the generator) that are related to differential properties (in the Malliavin sense) of $(\xi,f)$. The talk is mainly based on [1].

[1] S. Geiss and J. Ylinen: Decoupling on the Wiener Space, Related Besov Spaces, and Applications to BSDEs. ArXiv:1409.5322v3

Joint work with Juha Ylinen (University of Jyväskylä).

FoCM 2017, based on a nodethirtythree design.