General large deviations and functional iterated logarithm law for multivalued McKean-Vlasov stochastic differential equations

TL;DR

This paper develops large deviation principles and a functional iterated logarithm law for solutions of multivalued McKean-Vlasov SDEs, using weak convergence methods under non-Lipschitz conditions.

Contribution

It introduces new criteria for large deviations and iterated logarithm laws for multivalued McKean-Vlasov SDEs without requiring Lipschitz continuity.

Findings

Established large deviation principles for multivalued McKean-Vlasov SDEs.

Derived the functional iterated logarithm law for these SDE solutions.

Provided criteria applicable under non-Lipschitz conditions.

Abstract

In this paper, we present sufficient conditions and criteria to establish general large and moderate deviation principles for multivalued McKean-Vlasov stochastic differential equations (SDEs in short) by means of the weak convergence approach, under non-Lipschit assumptions on the coefficents of the equations. Furthermore, by applying the large deviation estimates we obtain the functional iterated logarithm law for the solutions of multivalued McKean-Vlasov SDEs.