Singular mean-field backward stochastic Volterra integral equations in infinite dimensional spaces

Abstract

This paper investigates the well-posedness of singular mean-field backward stochastic Volterra integral equations (MF-BSVIEs) in infinite-dimensional spaces. We consider the equation: \[X(t) = \Psi(t) + \int_t^b P\big(t, s, X(s), \aleph(t, s), \aleph(s, t), \mathbb{E}[X(s)], \mathbb{E}[\aleph(t, s)], \mathbb{E}[\aleph(s, t)]\big) ds - \int_t^b \aleph(t, s) dB_s, \] where the focus lies on establishing the existence and uniqueness of adapted M-solutions under appropriate conditions. A key contribution of this work is the development of essential lemmas that provide a rigorous foundation for analyzing the well-posedness of these equations. In addition, we extend our analysis to singular mean-field forward stochastic Volterra integral equations (MF-FSVIEs) in infinite-dimensional spaces, demonstrating their solvability and unique adapted solutions. Finally, we strengthen our theoretical results by applying them to derive stochastic maximum principles, showcasing the practical relevance of the proposed framework. These findings contribute to the growing body of research on mean-field stochastic equations and their applications in control theory and mathematical finance.