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Particle approximation for a conditional McKean--Vlasov stochastic differential equation by Du, Kai; Li, Yunzhang; Ye, Yuyang is a scholarly article available to read on EtoBox.

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In this paper, we construct a type of interacting particle systems to approximate a class of stochastic different equations whose coefficients depend on the conditional probability distributions of the processes given partial observations. After proving the well-posedness and regularity of the particle systems, we establish a quantitative convergence result for the empirical measures of the particle systems in the Wasserstein space, as the number of particles increases. Moreover, we discuss an Euler--Maruyama scheme of the particle system and validate its strong convergence. A numerical experiment is conducted to illustrate our results.

Author

Du, Kai; Li, Yunzhang; Ye, Yuyang

Published

2024

Language

EN