Mean-field forward and backward SDEs with jumps. Associated nonlocal quasi-linear integral-PDEs
Abstract: In this paper we consider a mean-field backward stochastic differential equation (BSDE) driven by a Brownian motion and an independent Poisson random measure. Translating the splitting method introduced by Buckdahn, Li, Peng and Rainer [6] to BSDEs, the existence and the uniqueness of the solution $(Y{t,\xi}, Z{t,\xi}, H{t,\xi})$, $(Y{t,x,P_\xi}, Z{t,x,P_\xi}, H{t,x,P_\xi})$ of the split equations are proved. The first and the second order derivatives of the process $(Y{t,x,P_\xi}, Z{t,x,P_\xi}, H{t,x,P_\xi})$ with respect to $x$, the derivative of the process $(Y{t,x,P_\xi}, Z{t,x,P_\xi}, H{t,x,P_\xi})$ with respect to the measure $P_\xi$, and the derivative of the process $(\partial_\mu Y{t,x,P_\xi}(y), \partial_\mu Z{t,x,P_\xi}(y), \partial_\mu H{t,x,P_\xi}(y))$ with respect to $y$ are studied under appropriate regularity assumptions on the coefficients, respectively. These derivatives turn out to be bounded and continuous in $L2$. The proof of the continuity of the second order derivatives is particularly involved and requires subtle estimates. This regularity ensures that the value function $V(t,x,P_\xi):=Y_t{t,x,P_\xi}$ is regular and allows to show with the help of a new It^{o} formula that it is the unique classical solution of the related nonlocal quasi-linear integral-partial differential equation (PDE) of mean-field type.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.